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White Paper Due: November 1, 2020
Publication Date: November 2021
CFP Document
White Paper Due: February 1, 2021
Publication Date: March 2022
CFP Document
Submission Deadline: February 19, 2021
Call for Proposals Document
Position description: The research project will focus on developing machine learning/deep learning methods for fundamental computer vision problems including object motion tracking, segmentation, 3D reconstruction, classification and image captioning in 2D/3D images including RGBD images, remote sensing data, 3D CT/MRI medical images and biomedical text.
October 26-27, 2020
Application submission deadline: October 14, 2020
Location: Virtual conference
Submission Deadline: October 12, 2020
Call for Proposals Document
Zeroth-order (ZO) optimization is a subset of gradient-free optimization that emerges in many signal processing and machine learning (ML) applications. It is used for solving optimization problems similarly to gradient-based methods. However, it does not require the gradient, using only function evaluations. Specifically, ZO optimization iteratively performs three major steps: gradient estimation, descent direction computation, and the solution update. In this article, we provide a comprehensive review of ZO optimization, with an emphasis on showing the underlying intuition, optimization principles, and recent advances in convergence analysis.