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Adaptive Stochastic Optimization: A Framework for Analyzing Stochastic Optimization Algorithms

Optimization lies at the heart of machine learning (ML) and signal processing (SP). Contemporary approaches based on the stochastic gradient (SG) method are nonadaptive in the sense that their implementation employs prescribed parameter values that need to be tuned for each application. This article summarizes recent research and motivates future work on adaptive stochastic optimization methods, which have the potential to offer significant computational savings when training largescale systems.

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Understanding Notions of Stationarity in Nonsmooth Optimization: A Guided Tour of Various Constructions of Subdifferential for Nonsmooth Functions

Many contemporary applications in signal processing and machine learning give rise to structured nonconvex nonsmooth optimization problems that can often be tackled by simple iterative methods quite effectively. One of the keys to understanding such a phenomenon-and, in fact, a very difficult conundrum even for experts-lies in the study of "stationary points" of the problem in question. Unlike smooth optimization, for which the definition of a stationary point is rather standard, there are myriad definitions of stationarity in nonsmooth optimization.

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Advances in Single-Photon Lidar for Autonomous Vehicles: Working Principles, Challenges, and Recent Advances

The safety and success of autonomous vehicles (AVs) depend on their ability to accurately map and respond to their surroundings in real time. One of the most promising recent technologies for depth mapping is single-photon lidar (SPL), which measures the time of flight of individual photons. The long-range capabilities (kilometers), excellent depth resolution (centimeters), and use of low-power (eye-safe) laser sources renders this modality a strong candidate for use in AVs. 

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Spiking Reservoir Networks: Brain-inspired recurrent algorithms that use random, fixed synaptic strengths

The success of artificial neural networks (ANNs) in carrying out various specialized cognitive tasks has brought renewed efforts to apply machine learning (ML) tools for economic, commercial, and societal aims, while also raising expectations regarding the advent of an artificial “general intelligence” [1][2][3]. Recent highly publicized examples of ML breakthroughs include the ANN-based algorithm AlphaGo...

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Intelligent Signal Processing and Coordination for the Adaptive Smart Grid: An Overview of Data-Driven Grid Management

In today's era of the Internet of Things (IoT), the amalgamation of information and communication technologies with actuating devices has reached all corners of the modern world. In the context of critical infrastructures, such as the power grid, this cyberphysical transformation has permeated all system levels as evident in devices ranging from crucial operational components (e.g., generators) and advanced sensors...

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Model Selection Techniques: An Overview

In the era of big data, analysts usually explore various statistical models or machine-learning methods for observed data to facilitate scientific discoveries or gain predictive power. Whatever data and fitting procedures are employed, a crucial step is to select the most appropriate model or method from a set of candidates. 

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Crowd-Based Learning of Spatial Fields for the Internet of Things: From Harvesting of Data to Inference

The knowledge of spatial distributions of physical quantities, such as radio-frequency (RF) interference, pollution, geomagnetic field magnitude, temperature, humidity, audio, and light intensity, will foster the development of new context-aware applications. For example, knowing the distribution of RF interference might significantly improve cognitive radio systems [1], [2].

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Practical Backscatter Communication Systems for Battery-Free Internet of Things: A Tutorial and Survey of Recent Research

Backscatter presents an emerging ultralow-power wireless communication paradigm. The ability to offer submilliwatt power consumption makes it a competitive core technology for Internet of Things (IoT) applications. In this article, we provide a tutorial of backscatter communication from the signal processing perspective as well as a survey of the recent research activities in this domain, primarily focusing on bistatic backscatter systems.

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A Survey on Smart Homes for Aging in Place: Toward Solutions to the Specific Needs of the Elderly

Advances in engineering and health science have brought a significant improvement in health care and increased life expectancy. As a result, there has been a substantial growth in the number of older adults around the globe, and that number is rising. According to a United Nations report, between 2015 and 2030, the number of adults over the age of 60 is projected to grow by 56%, with the total reaching nearly 2.1 billion by the year 2050 [1].

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