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  • Curaçao, Dutch Antilles

    December 10-13, 2017

    The seventh IEEE International Workshop on
    Computational Advances in Multi-Sensor
    Adaptive Processing

Program



 

Sunday, December 10

Monday, December 11

Tuesday, December 12

Wednesday, December 13

7:00 - 8:30am

 

Breakfast

Breakfast

 

Breakfast

 

8:30 - 9:00 am

OC: Opening Ceremony

9:00 - 9:30 am

PL1: Plenary Talk 1: Sub-Nyquist Sampling without Sparsity and Phase Retrieval

PL3: Plenary Talk 3: Graph Signal Processing Methods and their Application to Sensor Networks

PL5: Plenary Talk 5: Artificial Intelligence for 5G : Challenges and Opportunities

9:30 - 10:00 am

T1: Tutorial 1: The Multiport Communication Theory

10:00 - 10:15 am

Coffee Break

Coffee Break

Coffee Break

10:15 – 12:15 pm

MM1: Exploiting Structure in Compressed Sensing
MM2: Advances in Multi-Sensor Processing With Coarse Quantization
MM3: Learning Representations for Tensor Data

TM1: Graph Signal Processing
TM2: Biomedical Signal Processing
TM3: Advances in Processing Faulty High-Dimensional Data

WM1: Signal Processing for mmWave Communication in Freqency Selective Channels
WM2: Low-dimension Dynamical Systems in Signal Processing and Data Analysis
WM3: Ill-Posed Inverse Problems in High Resolution Imaging

12:15- 12:30 pm

Lunch

Lunch

Lunch

12:15 - 1:30 pm

 

1:30 - 3:00 pm

 

 

 

2:00 - 3:30 pm

 

 

T2: Tutorial 2: Learning Nonlinear and Dynamic Connectivity and Processes over Graphs

 

 

 

3:30 - 4:30 pm

PL2: Plenary Talk 2: A Signal Processing and Optimization Perspective on Financial Engineering

PL4: Plenary Talk 4: Data Fusion through Matrix and Tensor Factorizations: Uniqueness, Diversity, and Interpretability

PL6: Plenary Talk 6: Tensors and Probability: An Intriguing Union

4:30 - 5:00 pm

 

Posters & Coffee

MP1: Array Processing
MP2: Sparsity
MP3: Advanced Computational Methods for Photon Limited Imaging and Sensing
MP4: Imaging

Posters & Coffee

TP1: Radar
TP2: Signal and information processing over networks
TP3: Tensor Signal Processing
TP4: Direction of Arrival Estimation

Posters & Coffee

WP1: Communication Systems
WP2: Beamforming
WP3: Computer-intensive methods in signal processing

 

5:00 - 6:00 pm

SC: Student Paper Contest

6:00 - 7:00 pm

MA1: Recent Advances in Tensor-Based Signal Processing and Applications
MA2: Global and Non-convex Optimization Methods for Signal Processing
MA3: Sparsity in Sensing and Inference

TA1: Algorithms for Big Data Analytics
TA2: Advances in Multi-Sensor Adaptive Processing for GNSS
TA3: Information Geometry Approaches for Signal Processing

WA1: Signal Processing for Smart Grids
WA2: Advances in Monte Carlo Methods for Optimization and Inference in High-dimensional Systems
WA3: Target Tracking

7:00 - 7:40 pm

Welcome Dinner

 

7:40 - 8:00 pm

 

 

8:00 - 10:00 pm

Dinner

 

Conference Banquet 

(with best student paper awards)

9:30 - 11:30 pm

 

 

During the tutorials on Sunday, we have a coffee break from 10:45 am – 11:00 am and 3:15 pm -3:30 pm.
All meals that appear on the program are included

 

Sunday, December 10

Sunday, December 10, 09:30 - 12:30

T1: Tutorial 1: The Multiport Communication Theorygo to top

Josef A. Nossek
Room: Arawak A

Information theory serves well as the mathematical theory of communication. However, it contains no provision that makes sure its theorems are consistent with the physical laws that govern any existing realization of a communication system. Therefore, it may not be surprising that applications of information theory or signal processing, as currently practiced, easily turn out to be inconsistent with fundamental principles of physics, such as the law of conservation of energy. It is the purpose of multiport communication theory to provide the necessary framework ensuring that applications of signal processing and information theory actually do comply with physical law. This framework involves a circuit theoretic approach where the inputs and outputs of the communication system are associated with ports of a multiport black-box. Thanks to each port being described by a pair of two instead of just one variable, consistency with physics can be maintained. The connection to information theory and signal processing is then obtained by means of isomorphisms between mathematical (formal) symbols of the latter and the physical quantities of the multiport model. In this tutorial, the principles of the multiport communication theory are presented and accompanied by a discussion of a number of interesting results of its application to single and multi-antenna radio communications in single- and multi-user contexts. Among these results are a new mapping from uplink to downlink channel matrices of TDD systems based on reciprocity of the physical propagation channel and physical limitations of massive MIMO systems

Sunday, December 10, 14:00 - 17:00

T2: Tutorial 2: Learning Nonlinear and Dynamic Connectivity and Processes over Graphsgo to top

Georgios B. Giannakis
Room: Arawak A

Learning the topology of graphs as well as processes evolving over graphs are tasks emerging in application domains as diverse as gene-regulatory, brain, power, and social networks, to name a few. Scalable approaches to deal with such high-dimensional settings aim to address the unique modeling and computational challenges associated with data-driven science in the modern era of big data analytics. Albeit simple and tractable, linear time-invariant models are limited as they are incapable of modeling changing topologies, as well as nonlinear and dynamic dependencies between nodal processes. To this end, novel approaches are presented to leverage nonlinear counterparts of partial correlation and partial Granger causality, as well as nonlinear structural equations and vector auto-regressions, along with attributes such as low rank, sparsity, and smoothness to capture even directional dependencies with abrupt change points, as well as dynamic processes over possibly time-evolving topologies. The unifying framework inherits the versatility and generality of kernel-based methods, and lends itself to batch and computationally affordable online learning algorithms, which include novel Kalman filters and smoothers over graphs. Real data experiments highlight the impact of the nonlinear and dynamic models on gene-regulatory and functional connectivity of brain networks, where connectivity patterns revealed exhibit discernible differences relative to existing approaches.

Sunday, December 10, 17:00 - 19:00

SC: Student Paper Contestgo to top

Room: Poster Hall
Fundamental Limits of PhaseMax for Phase Retrieval: A Replica Analysis
Oussama Dhifallah and Yue M. Lu (Harvard University, USA)
Distributed Big-Data Optimization via Block Communications
Ivano Notarnicola (Universita of Salento, Italy); Ying Sun and Gesualdo Scutari (Purdue University, USA); Giuseppe Notarstefano (University of Salento, Italy)
Understanding the Role of Positive Constraints in Sparse Bilinear Problems
Heng Qiao and Piya Pal (University of California, San Diego, USA)
Maximally Economic Sparse Arrays and Cantor Arrays
Chun-Lin Liu (California Institute of Technology, USA); P. p. Vaidyanathan (Cal Tech., USA)
Correlation-based Ultrahigh-dimensional Variable Screening
Talal Ahmed (Rutgers University, USA); Waheed U. Bajwa (Rutgers University-New Brunswick, USA)
Simultaneous Target State and Sensor Bias Estimation: Is More Better
Michael Kowalski and Peter Willett (University of Connecticut, USA)
Face Recognition as a Kronecker Product Equation
Martijn Boussé, Nico Vervliet and Otto Debals (KU Leuven, Belgium); Lieven De Lathauwer (K.U.Leuven, Belgium)
Nonlinear Dimensionality Reduction on Graphs
Yanning Shen, Panagiotis A. Traganitis and Georgios B. Giannakis (University of Minnesota, USA)
STARK: Structured Dictionary Learning Through Rank-one Tensor Recovery
Mohsen Ghassemi, Zahra Shakeri and Anand D. Sarwate (Rutgers University, USA); Waheed U. Bajwa (Rutgers University-New Brunswick, USA)
Distributed Edge-Variant Graph Filters
Mario Coutino, Elvin Isufi and Geert Leus (Delft University of Technology, The Netherlands)

Monday, December 11

Monday, December 11, 08:30 - 09:00

OC: Opening & Awards Ceremonygo to top

Room: Arawak A

Monday, December 11, 09:00 - 10:00

PL1: Plenary Talk 1: Sub-Nyquist Sampling without Sparsity and Phase Retrievalgo to top

Yonina Eldar
Room: Arawak A

In recent years there has been an explosion of work on exploiting sparsity in order to reduce sampling rates in a wide-range of applications. In this talk, we consider several examples in which sub-Nyquist sampling is possible without assuming any structure on the signal being sampled. This is possible by careful design of the measurement scheme, together with nonlinear recovery methods. We then show how these concepts of measurement design and optimization-based recovery can be used to tackle a very different set of problems: phase retrieval from Fourier measurements. We begin by considering sampling a signal when we are interested in recovering its power spectrum. Next, we develop the minimal sampling rates required to achieve minimal distortion when representing an arbitrary signal by quantized samples. We then treat sampling of ultrasound signals where the goal is to create a beamformed image from the given samples. Finally, we propose several new measurement techniques in optical imaging that enable phase retrieval even in 1D problems from Fourier measurements.

Monday, December 11, 10:15 - 12:15

MM1: Exploiting Structure in Compressed Sensinggo to top

Special Session
Room: Arawak A
Chair: Marius Pesavento (Technische Universität Darmstadt & Merckstr. 25, Germany)
10:15 A Constrained Formulation for Compressive Spectral Image Reconstruction Using Linear Mixture Models
Jorge Bacca, Héctor Vargas and Henry Arguello Fuentes (Universidad Industrial de Santander, Colombia)
10:35 Efficient Recovery from Noisy Quantized Compressed Sensing Using Generalized Approximate Message Passing
Osman Musa (Vienna University of Technology (TU Wien), Austria); Gabor Hannak (Vienna University of Technology, Austria); Norbert Goertz (Vienna University of Technology (TU Wien), Austria)
10:55 One-bit Compressive Sampling with Time-Varying Thresholds for Multiple Sinusoids
Christopher D Gianelli, Luzhou Xu and Jian Li (University of Florida, USA); Petre Stoica (Uppsala University, Sweden)
11:15 Extended Defect Localization in Sparsity-based Guided Wave Structural Health Monitoring
Andrew Golato and Sridhar Santhanam (Villanova University, USA); Fauzia Ahmad (Temple University, USA); Moeness G. Amin (Villanova University, USA)
11:35 ANM-PhaseLift: Structured Line Spectrum Estimation from Quadratic Measurements
Zhe Zhang (Geroge Mason University, USA); Zhi Tian (George Mason University, USA)
11:55 Understanding the Role of Positive Constraints in Sparse Bilinear Problems
Heng Qiao and Piya Pal (University of California, San Diego, USA)

MM2: Advances in Multi-Sensor Processing With Coarse Quantizationgo to top

Special Session
Room: Arawak E
Chair: Josef A. Nossek (TU Munich, Germany & Federal University of Ceara, Fortaleza, Brazil)
10:15 Analysis of MRC for Mixed-ADC Massive MIMO
Hessam Pirzadeh (University of California, Irvine, USA); Lee Swindlehurst (University of California at Irvine, USA)
10:35 Performance Comparison of Hybrid and Digital Beamforming with Transmitter Impairments
Kilian Roth (Technische Universität München, Germany); Josef A. Nossek (TU Munich, Germany & Federal University of Ceara, Fortaleza, Brazil)
10:55 On the Achievable Rate of Multi-Antenna Receivers with Oversampled 1-Bit Quantization
Sandra Bender and Meik Dörpinghaus (TU Dresden, Germany); Gerhard Fettweis (Technische Universität Dresden, Germany)
11:15 Massive MIMO Downlink 1-Bit Precoding for Frequency Selective Channels
Hela Jedda (Technische Universität München, Germany); Amine Mezghani (University of California, Irvine, USA); Josef A. Nossek (TU Munich, Germany & Federal University of Ceara, Fortaleza, Brazil); Lee Swindlehurst (University of California at Irvine, USA)
11:35 Joint CFO and Channel Estimation in Millimeter Wave Systems with One-Bit ADCs
Nitin Jonathan Myers and Robert Heath (The University of Texas at Austin, USA)
11:55 Wideband Source Localization Using One-Bit Quantized Arrays
Ryan M Corey (University of Illinois at Urbana-Champaign, USA); Andrew C. Singer (University of Illinois at Urbana Champaign, USA)

MM3: Learning Representations for Tensor Datago to top

Special Session
Room: Arawak C
Chair: Waheed U. Bajwa (Rutgers University-New Brunswick, USA)
10:15 Locally Low-Rank Tensor Regularization for High-Resolution Quantitative Dynamic MRI
Burhaneddin Yaman, Sebastian Weingaertner, Nikos Kargas and Mehmet Akcakaya (University of Minnesota, USA); Nikolaos D Sidiropoulos (University of Virginia, USA)
10:35 Image Classification Using Local Tensor Singular Value Decompositions
Elizabeth Newman and Misha Kilmer (Tufts University, USA); Lior Horesh (IBM TJ Watson Research Center, USA)
10:55 Nonlinear Least Squares Algorithm for Canonical Polyadic Decomposition Using Low-Rank Weights
Martijn Boussé (KU Leuven, Belgium); Lieven De Lathauwer (K.U.Leuven, Belgium)
11:15 Identification of Kronecker-structured Dictionaries: An Asymptotic Analysis
Zahra Shakeri and Anand D. Sarwate (Rutgers University, USA); Waheed U. Bajwa (Rutgers University-New Brunswick, USA)
11:35 Low-rank Tensor Regression: Scalability and Applications
Yan Liu (University of Southern California, USA)
11:55 STARK: Structured Dictionary Learning Through Rank-one Tensor Recovery
Mohsen Ghassemi, Zahra Shakeri and Anand D. Sarwate (Rutgers University, USA); Waheed U. Bajwa (Rutgers University-New Brunswick, USA)

Monday, December 11, 15:30 - 16:30

PL2: Plenary Talk 2: A Signal Processing and Optimization Perspective on Financial Engineeringgo to top

Daniel P. Palomar
Room: Arawak A

Financial engineering and electrical engineering are seemingly different areas that share strong underlying connections. Both areas rely on statistical analysis and modeling of systems and the underlaying time series. Either modeling price fluctuations in the financial markets or modeling, say, channel fluctuations in wireless communication systems. Having a model of reality allows us to make predictions and to accordingly optimize the future strategies. It is as important to optimize our investment strategies in a financial market as it is to optimize the signal transmitted by an antenna in a wireless link. The foundations of both areas are the same in disguise and lie on signal processing and optimization. This talk provides a glimpse of financial engineering from a signal processing and optimization perspective, while exploring connections to other engineering disciplines.

Monday, December 11, 16:30 - 18:00

MP1: Array Processinggo to top

Room: Poster Hall - Sec. 1
Chair: Fauzia Ahmad (Temple University, USA)
Maximally Economic Sparse Arrays and Cantor Arrays
Chun-Lin Liu (California Institute of Technology, USA); P. p. Vaidyanathan (Cal Tech., USA)
Cramér-Rao-Induced Bound for Interference-to-Signal Ratio Achievable Through Non-Gaussian Independent Component Extraction
Václav Kautský (Czech Technical University in Prague, Czech Republic); Zbynek Koldovsky (Technical University of Liberec, Czech Republic); Petr Tichavsky (Academy of Sciences of the Czech Republic, Czech Republic)
Independent Low-Rank Matrix Analysis Based on Parametric Majorization-Equalization Algorithm
Yoshiki Mitsui, Daichi Kitamura, Norihiro Takamune and Hiroshi Saruwatari (The University of Tokyo, Japan); Yu Takahashi (Yahama Corporation, Japan); Kazunobu Kondo (Yamaha Corporation, Japan)
A Comparison of Iterative and DFT-Based Polynomial Matrix Eigenvalue Decompositions
Fraser K Coutts and Keith Thompson (University of Strathclyde, United Kingdom (Great Britain)); Ian Proudler (Loughborough University, United Kingdom (Great Britain)); Stephan Weiss (University of Strathclyde, United Kingdom (Great Britain))
An Adaptive Distributed Asynchronous Algorithm with Application to Target Localization
Rahul Mourya (Télécom ParisTech, Université Paris-Saclay & LTCI, France); Pascal Bianchi (Telecom Paristech - LTCI, France); Adil Salim (Telecom ParisTech, France); Cédric Richard (Université de Nice Sophia-Antipolis, France)
Adaptive ADMM in Distributed Radio Interferometric Calibration
Sarod Yatawatta (ASTRON, The Netherlands); Faruk Diblen and Hanno Spreeuw (Netherlands eScience Center, The Netherlands)

MP2: Sparsitygo to top

Room: Poster Hall - Sec. 2
Microkicking for Fast Convergence of Sparse Kaczmarz and Sparse LMS
Michael Lunglmayr and Mario Huemer (Johannes Kepler University Linz, Austria)
Compressive Sensing Seismic Acquisition by Using Regular Sampling in an Orthogonal Grid
Ofelia P Villarreal, Kareth León and Dayanna Espinosa (Universidad Industrial de Santander, Colombia); William Agudelo (Ecopetrol S.A. - Instituto Colombiano del Petróleo, Colombia); Henry Arguello Fuentes (Universidad Industrial de Santander, Colombia)
Sparse Array Imaging Using Low-Rank Matrix Recovery
Robin Rajamäki and Visa Koivunen (Aalto University, Finland)
Communication-Efficient Distributed Optimization for Sparse Learning via Two-Way Truncation
Jineng Ren, Xingguo Li and Jarvis D. Haupt (University of Minnesota, USA)
Sparse Bayesian Learning with Dictionary Refinement for Super-Resolution Through Time
Dmitriy Shutin (German Aerospace Center (DLR), Germany); Boris Vexler (Technische Universität München, Germany)
Sparsity-based Cholesky Factorization and Its Application to Hyperspectral Anomaly Detection
Ahmad W. Bitar (CentraleSupélec, France); Jean-Philippe Ovarlez (ONERA, France); Loong Fah Cheong (National University of Singapore, Singapore)
Spectral Image Fusion from Compressive Measurements Using Spectral Unmixing
Edwin Vargas (Universidad Industrial de Santander, Colombia); Jean-Yves Tourneret (University of Toulouse & ENSEEIHT, France); Henry Arguello Fuentes (Universidad Industrial de Santander, Colombia)
Greedy Phase Retrieval with Reference Points and Bounded Sparsity
Daniel Franz (Universität Rostock, Germany); Volker Kuehn (University of Rostock, Germany)

MP3: Advanced Computational Methods for Photon Limited Imaging and Sensinggo to top

Special Session
Room: Poster Hall - Sec. 3
Chairs: Yoann Altmann (Heriot-Watt University, School of Engineering and Physical Sciences, United Kingdom (Great Britain)), Steve McLaughlin (Heriot Watt University, United Kingdom (Great Britain))
Proximal-gradient Methods for Poisson Image Reconstruction with BM3D-based Regularization
Willem Marais and Rebecca Willett (University of Wisconsin-Madison, USA)
Restoration of Depth and Intensity Images Using a Graph Laplacian Regularization
Abderrahim Halimi, Peter Connolly and Ximing Ren (Heriot-Watt University, United Kingdom (Great Britain)); Yoann Altmann (Heriot-Watt University, School of Engineering and Physical Sciences, United Kingdom (Great Britain)); Istvan Gyongy (The University of Edinburgh, United Kingdom (Great Britain)); Robert Henderson (University of Edinburgh, United Kingdom (Great Britain)); Steve McLaughlin (Heriot Watt University, United Kingdom (Great Britain)); Gerald Buller (Heriot-Watt University, United Kingdom (Great Britain))
Photon-Limited Fluorescence Lifetime Imaging Microscopy Signal Recovery with Known Bounds
Omar DeGuchy, Lasith Adhikari, Arnold Kim and Roummel Marcia (University of California, Merced, USA)
Unsupervised Restoration of Subsampled Images Constructed from Geometric and Binomial Data
Yoann Altmann (Heriot-Watt University, School of Engineering and Physical Sciences, United Kingdom (Great Britain)); Miles Padgett (University of Glasgow, United Kingdom (Great Britain)); Steve McLaughlin (Heriot Watt University, United Kingdom (Great Britain))

MP4: Imaginggo to top

Room: Poster Hall - Sec. 4
Chair: Vishal Patel (Rutgers University, Piscataway, NJ USA, USA)
A Fast Algorithm Based on a Sylvester-like Equation for LS Regression with GMRF Prior
Qi Wei (Duke University, USA); Emilie Chouzenoux (Université Paris-Est Marne-la-Vallée, France); Jean-Yves Tourneret (University of Toulouse & ENSEEIHT, France); Jean-Christophe Pesquet (Center for Visual Computing, CentraleSupelec, France)
Generative Adversarial Network-Based Restoration of Speckled SAR Images
Puyang Wang and He Zhang (Rutgers Universiy, USA); Vishal Patel (Rutgers University, Piscataway, NJ USA, USA)
Online Deconvolution for Pushbroom Hyperspectral Imaging Systems
Yingying Song (University of Lorraine, France); El-Hadi Djermoune (Université de Lorraine & CRAN UMR 7039 CNRS, France); Jie Chen (Northwestern Polytechincal University, P.R. China); Cédric Richard (Université de Nice Sophia-Antipolis, France); David Brie (CRAN, Nancy Université, CNRS, France)
Fast and Accurate Radio Interferometric Imaging Using Krylov Subspaces
Shahrzad Naghibzadeh (Delft University of Technology, The Netherlands); Alle-Jan van der Veen (TU Delft, The Netherlands)
Boolean Approximation of a Phase-Coded Aperture Diffraction Pattern System for X-ray Crystallography
Samuel Pinilla, Tatiana Gelvez and Henry Arguello Fuentes (Universidad Industrial de Santander, Colombia)

Monday, December 11, 18:00 - 20:00

MA1: Recent Advances in Tensor-Based Signal Processing and Applicationsgo to top

Special Session
Room: Arawak A
Chair: Rémy Boyer (Université Paris-Sud (UPS), CNRS, CentraleSupelec, France)
6:00 Under-Determined Tensor Diagonalization for Decomposition of Difficult Tensors
Petr Tichavsky (Academy of Sciences of the Czech Republic, Czech Republic); Anh Huy Phan (RIKEN & Brain Science Institute, RIKEN, Japan); Andrzej S Cichocki (RIKEN BSI, Laboratory for Advanced Brain Signal Processing, Japan)
6:20 Broadband Beamforming via Frequency Invariance Transformation and PARAFAC Decomposition
Ricardo Kehrle Miranda (University of Brasilia, Brazil); João Paulo Carvalho Lustosa da Costa (Universidade de Brasília (UnB), Brazil); Giovanni Del Galdo (Fraunhofer Institute for Integrated Circuits IIS & Technische Universität Ilmenau, Germany); Florian Roemer (Ilmenau University of Technology, Germany)
6:40 Compressed Power Spectrum, Carrier and DOA Estimation via PARAFAC Decomposition
Jun Fang and Feiyu Wang (University of Electronic Science and Technology of China, P.R. China); Hongbin Li (Stevens Institute of Technology, USA)
7:00 Face Recognition as a Kronecker Product Equation
Martijn Boussé, Nico Vervliet and Otto Debals (KU Leuven, Belgium); Lieven De Lathauwer (K.U.Leuven, Belgium)
7:20 Intentional Islanding of Power Grids with Data Depth
Asim Dey and Yulia Gel (University of Texas at Dallas, USA); H. Vincent Poor (Princeton University, USA)
7:40 Generalized Tensor Contraction with Application to Khatri-Rao Coded MIMO OFDM Systems
Kristina Naskovska (TU Ilmenau, Germany); Martin Haardt (Ilmenau University of Technology, Germany); André de Almeida (Federal University of Ceará & Wireless Telecom Research Group - GTEL, Brazil)

MA2: Global and Non-convex Optimization Methods for Signal Processinggo to top

Special Session
Room: Arawak E
Chairs: Eduard Jorswieck (TU Dresden, Germany), Yang Yang (Intel Deutschland GmbH, Germany)
6:00 Energy Efficient Transmission in MIMO Interference Channels with QoS Constraints
Yang Yang (Intel Deutschland GmbH, Germany); Marius Pesavento (Technische Universität Darmstadt & Merckstr. 25, Germany)
6:20 Transmit Beamforming for Minimum Outage via Stochastic Approximation
Yunmei Shi (Harbin Institute of Technology Shenzhen Graduate School, Shenzhen, P.R. China); Aritra Konar (University of Minnesota, USA); Xing-peng Mao and Yong-Tan Liu (Harbin Institute of Technology, P.R. China); Nikolaos D Sidiropoulos (University of Virginia, USA)
6:40 Optimization Framework for Baseband Functionality Splitting in C-RAN
Alaa Alameer Ahmad (Ruhr-Universitaet Bochum, Germany); Aydin Sezgin (RUB, Germany)
7:00 Local Strong Convexity of Maximum-Likelihood TDOA-Based Source Localization and Its Algorithmic Implications
Huikang Liu, Yuen-Man Pun and Anthony Man-Cho So (The Chinese University of Hong Kong, Hong Kong)
7:20 EE Maximization for Massive MIMO with Fully Connected Hybrid Beamformers
Hans-Georg Engler (TU Dresden, Germany); Alessio Zappone (University of Cassino and Southern Lazio, Italy); Eduard Jorswieck (TU Dresden, Germany)
7:40 Multi-Agent Asynchronous Nonconvex Large-Scale Optimization
Loris Cannelli (Purdue University, USA); Francisco Facchinei (University of Rome "La Sapienza", Italy); Gesualdo Scutari (Purdue University, USA)

MA3: Sparsity in Sensing and Inferencego to top

Special Session
Room: Arawak C
Chairs: Sundeep Prabhakar Chepuri (Delft University of Technology, The Netherlands), Geert Leus (Delft University of Technology, The Netherlands)
6:00 Memory-Limited Stochastic Approximation for Poisson Subspace Tracking
Liming Wang (Duke University, USA); Yuejie Chi (The Ohio State University, USA)
6:20 Memory Efficient Low-Rank Non-Linear Subspace Tracking
Fatemeh Sheikholeslami and Dimitris Berberidis (University of Minnesota, Twin Cities, USA); Georgios B. Giannakis (University of Minnesota, USA)
6:40 Sparse Sensing for Composite Matched Subspace Detection
Mario Coutino, Sundeep Prabhakar Chepuri and Geert Leus (Delft University of Technology, The Netherlands)
7:00 Robust Detection of Random Events with Spatially Correlated Data in Wireless Sensor Networks via Distributed Compressive Sensing
Thakshila Wimalajeewa and Pramod Varshney (Syracuse University, USA)
7:20 Multi-Target Localization in Asynchronous MIMO Radars Using Sparse Sensing
Saeid Sedighi (University of Luxembourg, Luxembourg); Bhavani Shankar Mysore R (Interdisciplinary Centre for Security, Reliability and Trust & University of Luxembourg, Luxembourg); Sina Maleki (University of Luxembourg, Luxembourg); Björn Ottersten (University of Luxembourg, Luxembourg)
7:40 Online Topology Estimation for Vector Autoregressive Processes in Data Networks
Bakht Zaman, Luis M. Lopez-Ramos, Daniel Romero and Baltasar Beferull-Lozano (University of Agder, Norway)

Tuesday, December 12

Tuesday, December 12, 09:00 - 10:00

PL3: Plenary Talk 3: Graph Signal Processing Methods and their Application to Sensor Networksgo to top

Antonio Ortega
Room: Arawak A

Information gathering and processing in sensor networks was an early motivating application in the early 2000's for the study of transforms for graph signals. In this talk we start by providing a brief review of early work on signal representations for sensor data. Then we discuss how these methods have been extended to arbitrary graphs and summarize some key recent results in graph signal processing. Finally, we discuss how these results can be applied to sensor networks, focusing on problems such as graph identification, sensor selection, or distributed processing.

Tuesday, December 12, 10:15 - 12:15

TM1: Graph Signal Processinggo to top

Special Session
Room: Arawak A
Chairs: Antonio G. Marques (Universidad Rey Juan Carlos, Spain), Santiago Segarra (Massachusetts Institute of Technology, USA)
10:15 Graph Signal Processing: Filter Design and Spectral Statistics
Stephen Kruzick and Jose Moura (Carnegie Mellon University, USA)
10:35 Distributed Edge-Variant Graph Filters
Mario Coutino, Elvin Isufi and Geert Leus (Delft University of Technology, The Netherlands)
10:55 Design of Weighted Median Graph Filters
Santiago Segarra (Massachusetts Institute of Technology, USA); Antonio G. Marques (Universidad Rey Juan Carlos, Spain); Gonzalo Arce (University of Delaware, USA); Alejandro Ribeiro (University of Pennsylvania, USA)
11:15 Nonlinear Dimensionality Reduction on Graphs
Yanning Shen, Panagiotis A. Traganitis and Georgios B. Giannakis (University of Minnesota, USA)
11:35 Graph Topology Recovery for Regular and Irregular Graphs
Rohan Varma and Jelena Kovacevic (Carnegie Mellon University, USA)
11:55 Graph Recursive Least Squares Filter for Topology Inference in Causal Data Processes
Mahmoud Ramezani Mayiami and Baltasar Beferull-Lozano (University of Agder, Norway)

TM2: Biomedical Signal Processinggo to top

Special Session
Room: Arawak E
Chairs: Amar Kachenoura (University of Rennes1-LTSI & Inserm - UMR 1099, France), Laurent Albera (Université de Rennes1 & Inserm, France)
10:15 Statistical Modeling and Classification of Reflectance Confocal Microscopy Images
Abdelghafour Halimi (University of Toulouse, ENSEEIHT-IRIT, France); Hadj Batatia (University of Toulouse, France); Jimmy Le Digabel and Gwendal Josse (Pierre Fabre Laboratory, France); Jean-Yves Tourneret (University of Toulouse & ENSEEIHT, France)
10:35 Parameter Estimation in Block Term Decomposition for Noninvasive Atrial Fibrillation Analysis
Vicente Zarzoso (Université Côte d'Azur, CNRS, I3S)
10:55 Joint MEG-EEG Signal Decomposition Using the Coupled SECSI Framework: Validation on a Controlled Experiment
Kristina Naskovska (TU Ilmenau, Germany); Stephan Lau, Amr Aboughazala and Martin Haardt (Ilmenau University of Technology, Germany); Jens Haueisen (Technical University Ilmenau, Germany)
11:15 Optical Flow Estimation in Ultrasound Images Using a Sparse Representation
Nora Ouzir (University of Toulouse & INP-ENSEEIHT, France); Adrian Basarab (University of Toulouse, France); Jean-Yves Tourneret (University of Toulouse & ENSEEIHT, France)
11:35 Coded Aperture Design for Super-Resolution Compressive X-ray Tomography
Edson Mojica (Universidad Industrial de Santander & HDSP group, Colombia); Said Pertuz (Universitat Rovira i Virgili, Spain); Henry Arguello Fuentes (Universidad Industrial de Santander, Colombia)
11:55 Efficient Sparsity-Based Algorithm for Parameter Estimation of the Tri-Exponential Intra Voxel Incoherent Motion (IVIM) Model: Application to Diffusion-Weighted MR Imaging in the Liver
Jie Liu (LIST, Southeast University, France); Giulio Gambarota (Université de Rennes 1, France); Huazhong Shu (Southeast University, P.R. China); Longyu Jiang (LIST, Southeast University, P.R. China); Benjamin Leporq and Olivier Beuf (Université de Lyon, France); Ahmad Karfoul (Université de Rennes1 & INSERM U1099, France)

TM3: Advances in Processing Faulty High-Dimensional Datago to top

Special Session
Room: Arawak C
Chairs: Panos Markopoulos (Eindhoven University of Technology, The Netherlands), Dimitris A. Pados (The State University of New York at Buffalo, USA)
10:15 Reconstruction of Compressively Sampled Images Using a Nonlinear Bayesian Prior
Stefania Colonnese (Università La Sapienza di Roma, Italy); Mauro Biagi (Sapienza University of Rome, Italy); Roberto Cusani and Gaetano Scarano (Università La Sapienza di Roma, Italy)
10:35 Bi-Linear Modeling of Manifold-Data Geometry for Dynamic-MRI Recovery
Konstantinos Slavakis, Gaurav Shetty and Abhishek Bose (University at Buffalo (SUNY), USA); Ukash Nakarmi (SUNY, University at Buffalo, USA); Leslie Ying (University at Buffalo, USA)
10:55 Distributed Sketched Subspace Clustering for Large-scale Datasets
Panagiotis A. Traganitis and Georgios B. Giannakis (University of Minnesota, USA)
11:15 Computational Advances in Sparse L1-norm Principal-Component Analysis of Multi-Dimensional Data
Shubham Chamadia (State University at Buffalo, USA); Dimitris A. Pados (The State University of New York at Buffalo, USA)
11:35 On Canonical Polyadic Decomposition of Overcomplete Tensors of Arbitrary Even Order
Ali Koochakzadeh and Piya Pal (University of California, San Diego, USA)
11:55 L1-PCA Signal Subspace Identification for Non-sphered Data Under the ICA Model
Ruben Martin-Clemente (University of Sevilla, Spain); Vicente Zarzoso (Université Côte d'Azur, CNRS, France)

Tuesday, December 12, 15:30 - 16:30

PL4: Plenary Talk 4: Data Fusion through Matrix and Tensor Factorizations: Uniqueness, Diversity, and Interpretabilitygo to top

Tulay Adali
Room: Arawak A

Fusion of multiple sets of data, either of the same type as in multiset data or of different types and nature as in multi-modality data, is inherent to many problems in engineering and computer science. In data fusion, since most often, very little is known about the relationship of the underlying processes that give rise to such data, it is desirable to minimize the modeling assumptions, and at the same time, to maximally exploit the interactions within and across the multiple sets of data. This is one of the reasons for the growing importance of data-driven methods in data fusion tasks. Models based on matrix or tensor decompositions allow data sets to remain in their most explanatory form while admitting a broad range of assumptions among their elements. This talk will provide an overview of the main approaches that have been successfully applied for fusion of multiple datasets with a focus on the interrelated concepts of uniqueness, diversity, and interpretability. Diversity refers to any structural, numerical, or statistical inherent property or assumption on the data that contributes to the identifiability of the model, and for multiple datasets, provides the link among these datasets. Hence, diversity enables uniqueness, which is key to interpretability, the ability to attach a physical meaning to the final decomposition. The importance of these concepts as well as the challenges that remain are highlighted through a number of practical examples.

Tuesday, December 12, 16:30 - 18:00

TP1: Radargo to top

Room: Poster Hall - Sec. 1
Illuminator of Opportunity Selection for Passive Radar
Yang Li and Qian He (University of Electronic Science and Technology of China, P.R. China); Rick Blum (Lehigh University, USA)
Multi-scale Histogram Tone Mapping Algorithm for Display of Wide Dynamic Range Images
Jie Yang, Alain Horé, Ulian Shahnovich and Orly Yadid-Pecht (University of Calgary, Canada)
Joint Design of Co-Existing Communication System and Pulsed Radar
Le Zheng (Columbia University, New York, USA); Marco Lops (University of Cassino & CNIT - Consorzio Universitario Nazionale per le Telecomunicazioni, Italy); Xiaodong Wang (Columbia University, USA); Emanuele Grossi (University of Cassino and Southern Lazio & Consorzio Nazionale Inter-universitario per le Telecomunicazioni (CNIT), Italy); Junhui Qian (University of Electronic Science and Technology of China, P.R. China)
A General Class of Recursive Minimum Variance Distortionless Response Estimators
Jérôme Galy (LIRMM Montpellier, France); Eric Chaumette and François Vincent (ISAE, France)
Operational Characteristics of Wigner-Ville Accelerating Target Detector
Yuri Abramovich (W R Systems, Ltd, USA); Geoffrey San Antonio (US Naval Research Laboratory, USA); Stephen Mondschein (W R Systems, Ltd, USA)
A Bootstrapped Sequential Probability Ratio Test for Signal Processing Applications
Martin Gölz and Michael Fauß (Technische Universität Darmstadt, Germany); Abdelhak M Zoubir (Darmstadt University of Technology, Germany)

TP2: Signal and information processing over networksgo to top

Room: Poster Hall - Sec. 2
Chair: Waheed U. Bajwa (Rutgers University-New Brunswick, USA)
Byzantine-Resilient Locally Optimum Detection Using Collaborative Autonomous Networks
Bhavya Kailkhura (Syracuse University, USA); Priyadip Ray (IIT Kharagpur, USA); Deepak Rajan (LLNL, USA); Anton Yen (Space and Naval Warfare Systems Center Pacific, USA); Peter Barnes (LLNL, USA); Ryan Goldhahn (NATO STO Centre for Maritime Research and Experimentation, Italy)
Efficient Sensor Selection with Application to Time Varying Graphs
Buddhika Samarakoon, Manohar Murthi and Kamal Premaratne (University of Miami, USA)
Regularized LMS and Diffusion Adaptation LMS with Graph Filters for Non-Stationary Data
May Zar Lin, Manohar Murthi and Kamal Premaratne (University of Miami, USA)
Diffusion in Networks by Cooperative Particle Filtering
Hechuan Wang and Petar M. Djurić (Stony Brook University, USA)
Distributed Mirror Descent for Stochastic Learning over Rate-limited Networks
Matthew Nokleby (Wayne State University, USA); Waheed U. Bajwa (Rutgers University-New Brunswick, USA)
Penalty-Based Multitask Estimation with Non-Local Linear Equality Constraints
Fei Hua, Roula Nassif and Cédric Richard (Université de Nice Sophia-Antipolis, France); Haiyan Wang (Northwestern Polytechnical University, P.R. China)

TP3: Tensor Signal Processinggo to top

Room: Poster Hall - Sec. 3
Block Term Decomposition with Rank Estimation Using Group Sparsity
Xu Han (Université de Rennes 1, France); Laurent Albera (Université de Rennes1 & Inserm, France); Amar Kachenoura (University of Rennes1-LTSI & Inserm - UMR 1099, France); Hua Zhong Shu (Southeast University, P.R. China); Lotfi Senhadji (Université de Rennes 1 & Inserm, France)
Nonlinear System Identification: Finding Structure in Nonlinear Black-Box Models
Philippe Dreesen and Koen Tiels (Vrije Universiteit Brussel, Belgium); Mariya Ishteva (Vrije Universiteit Brussel (VUB), Belgium); Johan Schoukens (Vrije Universiteit Brussel, Belgium)
Performance Analysis of Least-Squares Khatri-Rao Factorization
Yao Cheng and Sher Ali Cheema (TU Ilmenau, Germany); Martin Haardt (Ilmenau University of Technology, Germany); Amir Weiss and Arie Yeredor (Tel-Aviv University, Israel)

TP4: Direction of Arrival Estimationgo to top

Room: Poster Hall - Sec. 4
Chair: Geert Leus (Delft University of Technology, The Netherlands)
Low Rank Matrix Recovery for Joint Array Self-Calibration and Sparse Model DoA Estimation
Cheng-Yu Hung and Mostafa Kaveh (University of Minnesota, USA)
Adaptive Channel Selection for DOA Estimation in MIMO Radar
David Mateos-Nunez and María Gonzalez-Huici (Fraunhofer FHR, Germany); Renato Simoni (Fraunhofer FHR, Germany); Stefan Bruggenwirth (Fraunhofer FHR, Germany)
Multi-Mode Antenna Specific Direction-of-Arrival Estimation Schemes
Robert Pöhlmann, Siwei Zhang, Kazeem A. Yinusa and Armin Dammann (German Aerospace Center (DLR), Germany)
Improved DOA Estimators Using Partial Relaxation Approach
Minh Trinh Hoang (TU Darmstadt, Germany); Mats Viberg (Chalmers University of Technology, Sweden); Marius Pesavento (Technische Universität Darmstadt & Merckstr. 25, Germany)
DOA Estimation and Beamforming Using Spatially Under-Sampled AVS Arrays
Krishnaprasad Nambur Ramamohan (Delft University of Technology & Microflown Technologies, The Netherlands); Mario Coutino and Sundeep Prabhakar Chepuri (Delft University of Technology, The Netherlands); Daniel Fernández Comesaña (Microflown Technologies, The Netherlands); Geert Leus (Delft University of Technology, The Netherlands)
Localization of Multiple Simultaneously Active Sources in Acoustic Sensor Networks Using ADP
Andreas Brendel (University Erlangen-Nürnberg, Germany); Walter Kellermann (University Erlangen-Nuremberg, Germany)
Performance Analysis of ESPRIT-Type Algorithms for Co-Array Structures
Jens Steinwandt, Florian Roemer and Martin Haardt (Ilmenau University of Technology, Germany)
The Mean-Squared-Error of Autocorrelation Sampling in Coprime Arrays
Dimitris G. Chachlakis and Panos P. Markopoulos (Rochester Institute of Technology, USA); Fauzia Ahmad (Temple University, USA)

Tuesday, December 12, 18:00 - 19:40

TA1: Algorithms for Big Data Analyticsgo to top

Special Session
Room: Arawak A
Chairs: Georgios B. Giannakis (University of Minnesota, USA), Gonzalo Mateos (University of Rochester, USA)
6:00 Robust Low-Complexity Methods for Matrix Column Outlier Identification
Xingguo Li and Jarvis D. Haupt (University of Minnesota, USA)
6:20 Correlation-based Ultrahigh-dimensional Variable Screening
Talal Ahmed (Rutgers University, USA); Waheed U. Bajwa (Rutgers University-New Brunswick, USA)
6:40 A Distributed Algorithm for Partitioned Robust Submodular Maximization
Ilija Bogunovic (Ecole Polytechnique Federale de Lausanne (EPFL), Switzerland); Slobodan Mitrović (École Polytechnique Fédérale de Lausanne, Switzerland); Jonathan Scarlett (EPFL, Switzerland); Volkan Cevher (Ecole Polytechnique Federale de Lausanne, Switzerland)
7:00 Distributed Big-Data Optimization via Block Communications
Ivano Notarnicola (Universita of Salento, Italy); Ying Sun and Gesualdo Scutari (Purdue University, USA); Giuseppe Notarstefano (University of Salento, Italy)
7:20 Recurrent Generative Adversarial Neural Networks for Compressive Imaging
Morteza Mardani (Stanford University); Enhao Gong, Joseph Cheng, Jonh Pauly and Xing Lei (Stanford University, USA)

TA2: Advances in Multi-Sensor Adaptive Processing for GNSSgo to top

Special Session
Room: Arawak E
Chair: Felix Antreich (Federal University of Ceara (UFC), Brazil)
6:00 Design of Optimum Sparse Array for Robust MVDR Beamforming Against DOA Mismatch
Xiangrong Wang (Beihang University, P.R. China); Moeness G. Amin (Villanova University, USA)
6:20 Time-Delay Estimation via CPD-GEVD Applied to Tensor-based GNSS Arrays with Errors
Daniel Valle de Lima and Joao Paulo Carvalho Lustosa da Costa (University of Brasília, Brazil); Felix Antreich (Federal University of Ceara (UFC), Brazil); Ricardo Kehrle Miranda (University of Brasilia, Brazil); Giovanni Del Galdo (Fraunhofer Institute for Integrated Circuits IIS & Technische Universität Ilmenau, Germany)
6:40 Multipath Mitigation Using OMP and Newton's Method for Multi-Antenna GNSS Receivers
Lorenz Weiland, Thomas Wiese and Wolfgang Utschick (Technische Universität München, Germany)
7:00 Estimation Bounds for GNSS Synthetic Aperture Techniques
Miguel Angel Ribot and Joaquín Cabeza (Ecole Polytechnique Federale de Lausanne (EPFL), Switzerland); Pau Closas (Northeastern University, USA); Cyril Botteron (EPFL, Switzerland); Pierre-Andre Farine (Ecole Polytechnique Federal de Lausanne, Switzerland)
7:20 On the Delay-Doppler Tracking Error for Sub-Nyquist Satellite-Based Synchronization
Manuel S. Stein (Vrije Universiteit Brussel, Belgium); Andreas Lenz (Technische Universität München, Germany); Lee Swindlehurst (University of California at Irvine, USA)

TA3: Information Geometry Approaches for Signal Processinggo to top

Special Session
Room: Arawak C
Chair: Charles Casimiro Cavalcante (Federal University of Ceará, Brazil)
6:00 Information Distances for Radar Resolution Analysis
Radmila Pribić (Thales Nederland BV Delft, The Netherlands); Geert Leus (Delft University of Technology, The Netherlands)
6:20 Multivariate Time-Series Analysis via Diffusion Maps
Pedro Luiz Coelho Rodrigues and Marco Congedo (GIPSA-lab, France); Christian Jutten (GIPSA-Lab, France)
6:40 Stochastic EM Algorithm for Mixture Estimation on Manifolds
Paolo Zanini (Gipsa-Lab, University of Grenoble Alpes, France); Salem Said (Université de Bordeaux, Laboratoire IMS, Signal and Image Group, France); Charles Casimiro Cavalcante (Federal University of Ceará, Brazil); Yannick Berthoumieu (University of Bordeaux, France)
7:00 Optimisation Geometry and Its Implications for Optimisation Algorithms
Michael Pauley (The University of Melbourne, Australia); Jonathan H. Manton (School of Engineering, The University of Melbourne, Australia)
7:20 Restricted Update Sequential Matrix Diagonalisation for Parahermitian Matrices
Fraser K Coutts and Keith Thompson (University of Strathclyde, United Kingdom (Great Britain)); Ian Proudler (Loughborough University, United Kingdom (Great Britain)); Stephan Weiss (University of Strathclyde, United Kingdom (Great Britain))

Wednesday, December 13

Wednesday, December 13, 09:00 - 10:00

PL5: Plenary Talk 5: Artificial Intelligence for 5G : Challenges and Opportunitiesgo to top

Mérouane Debbah
Room: Arawak A

Mobile cellular networks are becoming increasingly complex to manage while classical deployment/optimization techniques are cost-ineffective and thus seen as stopgaps. This is all the more difficult considering the extreme constraints of 5G networks in terms of data rate (more than 10 Gb/s), massive connectivity (more than 1000000 devices per km2), latency (under 1ms) and energy efficiency (a reduction by a factor of 100 with respect to 4G network). Unfortunately, the development of adequate solutions is severely limited by the scarcity of the actual resources (energy, bandwidth and space). Recently, the community has turned to a new resource known as Artificial Intelligence at all layers of the network to exploit the increasing computing power afforded by the improvement in Moore's law in combination with the availability of huge data in 5G networks. This is an important paradigm shift which considers the increasing data flood/huge number of nodes as an opportunity rather than a curse. In this talk, we will discuss through various examples how the recent advances in big data algorithms can provide an efficient framework for the design of 5G Intelligent Networks.

Wednesday, December 13, 10:15 - 12:15

WM1: Signal Processing for mmWave Communication in Freqency Selective Channelsgo to top

Special Session
Room: Arawak A
10:15 Position Aided Beam Alignment for Millimeter Wave Backhaul Systems with Large Phased Arrays
George C. Alexandropoulos (Huawei Technologies France, France)
10:35 Learning-based Pilot Precoding and Combining for Wideband Millimeter-wave Networks
Ehsan Olfat and Hossein Shokri-Ghadikolaei (KTH Royal Institute of Technology, Sweden); Nima N. Moghadam (ACCESS Linnaeus Center, KTH Royal Institute of Technology, Sweden); Mats Bengtsson (KTH Royal Institute of Technology, Sweden); Carlo Fischione (KTH, Sweden)
10:55 A Compressive Sensing-Maximum Likelihood Approach for Off-Grid Wideband Channel Estimation at mmWave
Javier Rodríguez-Fernández (University of Vigo, Spain); Nuria González-Prelcic (Universidad de Vigo, Spain); Robert Heath (The University of Texas at Austin, USA)
11:15 Channel Estimation for Hybrid Multi-Carrier MmWave MIMO Systems Using Three-Dimensional Unitary ESPRIT in DFT Beamspace
Jianshu Zhang and Martin Haardt (Ilmenau University of Technology, Germany)
11:35 Wideband Channel Tracking for mmWave MIMO System with Hybrid Beamforming Architecture
Han Yan and Shailesh Chaudhari (University of California, Los Angeles, USA); Danijela Cabric (University of California Los Angeles, USA)
11:55 Tensor-Based Compressed Estimation of Frequency-Selective mmWave MIMO Channels
Daniel Araújo (Federal University of Ceará, Brazil); André de Almeida (Federal University of Ceará & Wireless Telecom Research Group - GTEL, Brazil)

WM2: Low-dimension Dynamical Systems in Signal Processing and Data Analysisgo to top

Special Session
Room: Arawak E
Chairs: Adam Charles (Princeton, USA), Mark Davenport (Georgia Institute of Technology, USA)
10:15 Earth-Mover's Distance as a Tracking Regulaizer
Adam Charles (Princeton, USA); Nicholas Bertrand (Georgia Institute of Technology, USA); John Lee (Georgia Institute of Technology, Portugal); Christopher Rozell (Georgia Tech, USA)
10:35 Sequential Detection of Low-Rank Changes Using Extreme Eigenvalues
Liyan Xie and Yao Xie (Georgia Institute of Technology, USA)
10:55 Data-Driven Discovery of Governing Physical Laws and Their Parametric Dependencies in Engineering, Physics and Biology
J. Nathan Kutz, Steven Brunton and Samuel Rudy (University of Washington, USA); Alessandro Alla (Florida State University, USA)
11:15 Simultaneous Recovery of A Series of Low-rank Matrices by Locally Weighted Matrix Smoothing
Liangbei Xu and Mark Davenport (Georgia Institute of Technology, USA)
11:35 Structure-Exploiting Variational Inference for Recurrent Switching Linear Dynamical Systems
Scott Linderman (Columbia University, USA); Matthew Johnson (Google Brain, USA)
11:55 Network Estimation via Poisson Autoregressive Models
Benjamin Mark (UW-Madison, USA); Garvesh Raskutti (UW-Madison); Rebecca Willett (University of Wisconsin-Madison, USA)

WM3: Ill-Posed Inverse Problems in High Resolution Imaginggo to top

Special Session
Room: Arawak C
Chairs: Fauzia Ahmad (Temple University, USA), Piya Pal (University of California, San Diego, USA)
10:15 Super-Resolution of Complex Exponentials from Modulations with Known Waveforms
Zhihui Zhu, Manuel Lopez-Santillana and Michael Wakin (Colorado School of Mines, USA)
10:35 Joint Low-Rank and Sparse Based Image Reconstruction for Through-the-Wall Radar Imaging
Fok Hing Chi Tivive and Abdesselam Bouzerdoum (University of Wollongong, Australia)
10:55 Soft Extrapolation of Bandlimited Functions
Dmitry Batenkov (MIT); Laurent Demanet (MIT, USA)
11:15 Performance of Free-Space Tomographic Imaging Approximation for Shallow-Buried Target Detection
Davide Comite (Sapienza University of Rome, Italy); Fauzia Ahmad (Temple University, USA); Traian Dogaru (US Army Research Lab, USA)
11:35 On the Role of Sampling and Sparsity in Phase Retrieval for Optical Coherence Tomography
Pulak Sarangi, Heng Qiao and Piya Pal (University of California, San Diego, USA)
11:55 Fundamental Limits of PhaseMax for Phase Retrieval: A Replica Analysis
Oussama Dhifallah and Yue M. Lu (Harvard University, USA)

Wednesday, December 13, 15:30 - 16:30

PL6: Plenary Talk 6: Tensors and Probability: An Intriguing Uniongo to top

Nikos Sidiropoulos
Room: Arawak A

We reveal an interesting link between tensors and multivariate statistics. The rank of a multivariate probability tensor can be interpreted as a nonlinear measure of statistical dependence of the associated random variables. Rank equals one when the random variables are independent, and complete statistical dependence corresponds to full rank; but we show that rank as low as two can already model strong statistical dependence. In practice we usually work with random variables that are neither independent nor fully dependent -- partial dependence is typical, and can be modeled using a low-rank multivariate probability tensor. Directly estimating such a tensor from sample averages is impossible even for as few as ten random variables taking ten values each -- yielding a billion unknowns; but we often have enough data to estimate lower-order marginalized distributions. We prove that it is possible to identify the higher-order joint probabilities from lower order ones, provided that the higher-order probability tensor has low-enough rank, i.e., the random variables are only partially dependent. We also provide a computational identification algorithm that is shown to work well on both simulated and real data. The insights and results have numerous applications in estimation, hypothesis testing, completion, machine learning, and system identification. Low-rank tensor modeling thus provides a `universal' non-parametric (model-free) alternative to probabilistic graphical models.

Wednesday, December 13, 16:30 - 18:00

WP1: Communication Systemsgo to top

Room: Poster Hall - Sec. 1
Constellation Shaping for Rate Maximization in AWGN Channels with Non-linear Distortion
Hiroki Iimori (Ritsumeikan University, Japan); Andrei Stoica (Jacobs University Bremen, Germany); Giuseppe Abreu (Jacobs University Bremen, Germany & Ritsumeikan University, Japan)
Weighted Sum Rate Maximization for Non-Regenerative Multi-Way Relay Channels with Multi-User Decoding
Bho Matthiesen (Technische Universität Dresden, Germany); Eduard Jorswieck (TU Dresden, Germany)
Harvested Power Maximization in QoS-constrained MIMO SWIPT with Generic RF Harvesting Model
Deepak Mishra (Linköping University, Sweden); George C. Alexandropoulos (Huawei Technologies France, France)
Fast Converging Decentralized WSRMax for MIMO IBC with Low Computational Complexity
Jarkko Kaleva, Antti Tölli and Markku Juntti (University of Oulu, Finland)
Tracking Abruptly Changing Channels in mmWave Systems Using Overlaid Data and Training
Karthik Upadhya (Aalto University, Finland); Robert Heath (The University of Texas at Austin, USA); Sergiy A. Vorobyov (Aalto University, Finland)
GenS: A New Conflict-Free Link Scheduler for Next Generation of Wireless Systems
Zahra Naghsh and Shahrokh Valaee (University of Toronto, Canada)

WP2: Beamforminggo to top

Room: Poster Hall - Sec. 2
Chair: Shahram ShahbazPanahi (University of Ontario Institute of Technology, Canada)
Energy-Efficient Distributed Amplify-and-Forward Beamforming for Wireless Sensor Networks
Slim Zaidi (University of Quebec, INRS-EMT, Canada); Oussama Ben Smida (Institut National de la Recherche Scientifique, Canada); Sofiene Affes (INRS-EMT, Canada); Shahrokh Valaee (University of Toronto, Canada)
Bias-Compensated MPDR Beamformer for Small Number of Samples
François Vincent, Olivier Besson and Eric Chaumette (ISAE, France)
Network Beamforming for Asynchronous MIMO Two-Way Relay Networks
Razgar Rahimi and Shahram ShahbazPanahi (University of Ontario Institute of Technology, Canada)
An Improved Design of Robust Adaptive Beamforming Based on Steering Vector Estimation
Yongwei Huang (The Hong Kong University of Science and Technology, Hong Kong)
An ADMM Approach to Distributed Coordinated Beamforming in Dynamic TDD Networks
Khaled Ardah (Federal University of Ceará, Brazil); Yuri C. B. Silva (Federal University of Ceará & Wireless Telecom Research Group (GTEL), Brazil); Walter Freitas, Jr. (Federal University of Ceará & Wireless Telecom Research Group, Brazil); Francisco R. P. Cavalcanti (Federal University of Ceará & GTEL - Wireless Telecom Research Group, Brazil); Gabor Fodor (Ericsson Research & Royal Institute of Technology (KTH), Sweden)
Robust MDDR Beamforming for Sub-Gaussian Signals in the Presence of Fast-moving Interferences
Liang Zhang, Lei Huang, Peichang Zhang and Qiang Li (Shenzhen University, P.R. China)

WP3: Computer-intensive methods in signal processinggo to top

Room: Poster Hall - Sec. 3
Rapid System Identification for Jump Markov Non-Linear Systems
Andre R. Braga (Instituto Tecnológico de Aeronáutica & Universidade Federal do Ceara, Brazil); Carsten Fritsche and Fredrik Gustafsson (Linköping University, Sweden); Marcelo Bruno (ITA, Brazil)
Bayesian Bhattacharyya Bound for Discrete-Time Filtering Revisited
Carsten Fritsche and Fredrik Gustafsson (Linköping University, Sweden)
A Particle-based Approach for Topology Estimation of Gene Networks
Çağla Taşdemir, Monica F. Bugallo and Petar M. Djurić (Stony Brook University, USA)
Bayesian Selection of Models of Network Formation
Lingqing Gan and Petar M. Djurić (Stony Brook University, USA)
Deep Robust Regression
Tzvi Diskin (The Hebrew University of Jerusalem, Israel); Gordana Draskovic and Frederic Pascal (CNRS-Universit, France); Ami Wiesel (The Hebrew University of Jerusalem, Israel)
Robust-COMET for Covariance Estimation in Convex Structures: Algorithm and Statistical Properties
Bruno Mériaux (SONDRA, CentraleSupélec, France); Chengfang Ren (Centrale-Supelec, France); Mohammed Nabil El Korso (Paris 10 University & LEME-EA 4416, France); Arnaud Breloy (University Paris Nanterre, France); Philippe Forster (Universite Paris Ouest Nanterre, France)
Recursive Estimation of Time-Varying RSS Fields Based on Crowdsourcing and Gaussian Processes
Irene Santos Velázquez (University of Seville, Spain); Juan José Murillo-Fuentes (Universidad de Sevilla, Spain); Petar M. Djurić (Stony Brook University, USA)
A Fast Model for Solving the ECG Forward Problem Based on an Evolutionary Algorithm
Karim El Houari (University of Rennes 1 & Ansys Inc., France); Amar Kachenoura (University of Rennes1-LTSI & Inserm - UMR 1099, France); Laurent Albera (Université de Rennes1 & Inserm, France); Siouar Bensaid (LTSI, Inserm & Université de Rennes 1 & INSERM, France); Ahmad Karfoul (Université de Rennes1 & INSERM U1099, France); Christelle Boichon-Grivot and Michel Rochette (Ansys Inc., France); Alfredo Hernández (INSERM, France)

Wednesday, December 13, 18:00 - 19:40

WA1: Signal Processing for Smart Gridsgo to top

Special Session
Room: Arawak A
Chairs: Vassilis Kekatos (Virginia Tech, USA), Hao Zhu (University of Illinois at Urbana-Champaign, USA)
6:00 Distributed Optimal Power Flow Using Feasible Point Pursuit
Ahmed S Zamzam and Xiao Fu (University of Minnesota, USA); Emiliano Dall'Anese (National Renewable Energy Laboratory, USA); Nikolaos D Sidiropoulos (University of Virginia, USA)
6:20 Going Beyond Linear Dependencies to Unveil Connectivity of Meshed Grids
Liang Zhang, Gang Wang and Georgios B. Giannakis (University of Minnesota, USA)
6:40 Multi-Channel Missing Data Recovery by Exploiting the Low-rank Hankel Structures
Shuai Zhang, Yingshuai Hao, Meng Wang and Joe H. Chow (Rensselaer Polytechnic Institute, USA)
7:00 Predicting Voltage Stability Margin via Learning Stability Region Boundary
Young-hwan Lee (University of Maryland, Baltimore County, USA); Yue Zhao (Stony Brook University, USA); Seung-Jun Kim (University of Maryland, Baltimore County, USA); Jiaming Li (Stony Brook University, USA)
7:20 Power Grid Probing for Load Learning: Identifiability over Multiple Time Instances
Siddharth Bhela and Vassilis Kekatos (Virginia Tech, USA); Sriharsha Veeramachaneni (Windlogics Inc., USA)

WA2: Advances in Monte Carlo Methods for Optimization and Inference in High-dimensional Systemsgo to top

Special Session
Room: Arawak E
Chairs: Víctor Elvira (IMT Lille Douai, France), David Luengo (Universidad Politecnica de Madrid (UPM), Spain)
6:00 Multiple Sigma-point Kalman Smoothers for High-dimensional State-Space Models
Jordi Vilà-Valls (Centre Tecnològic de Telecomunicacions de Catalunya (CTTC/CERCA), Spain); Pau Closas (Northeastern University, USA); Angel Garcia-Fernandez (Aalto University, Finland); Carles Fernández-Prades (Centre Tecnològic de Telecomunicacions de Catalunya (CTTC), Spain)
6:20 Population Monte Carlo Schemes with Reduced Path Degeneracy
Víctor Elvira (IMT Lille Douai, France); Luca Martino (Universidad de Valencia, France); David Luengo (Universidad Politecnica de Madrid (UPM), Spain); Monica F. Bugallo (Stony Brook University, USA)
6:40 Simulated Convergence Rates with Application to an Intractable $\alpha$-Stable Inference Problem
Marina Riabiz (University of Cambridge & Alan Turing Institute, United Kingdom (Great Britain)); Tohid Ardeshiri (University of Cambridge & Linköping University, United Kingdom (Great Britain)); Ioannis Kontoyiannis (Athens UniversityEcon & Business, Greece); Simon Godsill (University of Cambridge, United Kingdom (Great Britain))
7:00 Gaussian Sum Particle Flow Filter
Soumyasundar Pal and Mark Coates (McGill University, Canada)
7:20 Adaptive Noisy Importance Sampling for Stochastic Optimization
Deniz Akyildiz (Universidad Carlos III de Madrid, Spain); Inés Mariño (Universidad Rey Juan Carlos, Spain); Joaquin Míguez (Universidad Carlos III de Madrid, Spain)

WA3: Target Trackinggo to top

Special Session
Room: Arawak C
6:00 Adaptive Target Tracking Using Multistatic Sensor with Unknown Moving Transmitter Positions
Rong Yang (Asian Society of Information Exploitaion, Singapore); Yaakov Bar-Shalom (University of Connecticut, USA)
6:20 Performance of Range-Only TMA
Annie-Claude Perez and Claude Jauffret (Université de Toulon, France); Denis Pillon (Retired, France)
6:40 Algorithms for the Multi-Sensor Assignment Problem in the Delta-Generalized Labeled multi-Bernoulli Filter
Jun Ye Yu, Augustin-Alexandru Saucan, Mark Coates and Michael Rabbat (McGill University, Canada)
7:00 A Classify-While-Track Approach Using Dynamical Tensors
Felix Govaers (Fraunhofer FKIE / University of Bonn, Germany)
7:20 Simultaneous Target State and Sensor Bias Estimation: Is More Better
Michael Kowalski and Peter Willett (University of Connecticut, USA)
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