News Archive

  • January, 2021: With Prof. Usman Khan (Tufts), we are organizing a special track on Signal Processing for Self-Aware and Social Autonomous Systems at the inaugural IEEE-ICAS in Montreal this August! The deadline of submission is March 3, 2021.

  • December, 2020: New paper Federated Block Coordinate Descent Scheme for Learning Global and Personalized Models (with Ryan, Anna, Nurullah, Kari and Ken) accepted at AAAI 2021 preprint

AAAI 
  • September, 2020: Two papers accepted at NeurIPS 2020:

    • Provably Efficient Neural GTD for Off-Policy Learning (with Zhuoran, Zhaoran, Mingyi) pre-proceeding.

    • A Stochastic Path Integral Differential EstimatoR Expectation Maximization Algorithm (with Gersende, Eric) pre-proceeding.

NeurIPS 
  • September, 2020: New paper Resilient Primal-Dual Optimization Algorithms for Distributed Resource Allocation accepted by IEEE Transactions on Control of Networked Systems (with Burkay, Cesar, Mahnoosh). This paper studies how to robustify distributed primal-dual optimization using a median filtering for robust mean estimation. Checkout the preprint here

TCNS 
  • August, 2020: New paper A User Guide to Low-Pass Graph Signal Processing and its Applications (with Raksha and Anna) accepted by IEEE SP Magazine for a special issue on Graph Signal Processing. Checkout the preprint here. In this paper, we overview a number of network dynamics models which lead to low-pass graph signals, and demonstrate how to leverage the low-pass properties for making inference and data analytics.

SPM 
  • August, 2020: New paper Exact Blind Community Detection from Signals on Multiple Graphs (with Mitch, Michael and Santiago) accepted by IEEE TSP. Checkout the preprint here. In this paper, we show that communities can be detected exactly from graph signals generated from multiple SBM-PPM graphs, regardless of the spectral resolution limit.

TSP 
  • May, 2020: Our paper, Finite Time Analysis of Linear Two-timescale Stochastic Approximation with Markovian Noise (with Maxim, Eric, Alex and Vladislav), has been accepted by COLT 2020. Checkout the preprint here.

  • Mar., 2020: Our paper, Block-randomized stochastic proximal gradient for low-rank tensor factorization (with Xiao, Shahana, Cheng and Kejun), has been accepted by IEEE TSP. Checkout the paper here.

  • Feb., 2020: Our paper, Accelerating Incremental Gradient Optimization with Curvature Information (with Wilbur, Cesar, Angelia and Anna), has been accepted by Computational Optimization and Applications. The preprint here will be updated soon.

  • Feb., 2020: With Prof. Usman Khan (Tufts), we are organizing a special track on *Signal Processing for Self-Aware and Social Autonomous Systems* at the inaugural [https://2020.ieee-icas.org/ *IEEE-ICAS*] in Montreal this August! Please consider sending your work there The IEEE-ICAS conference has been postponed to 2021 due to the coronavirus outbreak.

  • Feb., 2020: Our paper, Hybrid Inexact BCD for Coupled Structured Matrix Factorization in Hyperspectral Super-Resolution (with Ryan and Ken), has been accepted by IEEE TSP. See the preprint here.

  • Jan., 2020: Our paper, Estimating Centrality Blindly from Low-pass Filtered Graph Signals (with Yiran), has been accepted by IEEE ICASSP 2020. This is Yiran's first paper. Congrats! See the preprint here.

  • Jan., 2020: Our paper, Distributed Learning in the Non-Convex World: From Batch to Streaming Data, and Beyond (with Tsung-hui, Mingyi, Xinwei, Songtao), has been accepted by IEEE SP Magazine as a special issue paper on Distributed, Streaming Machine Learning. This paper provides a selective review on non-convex distributed learning, accompanied with extensive numerical experiments to illustrates some practical concerns in applying distributed algorithms on machine learning. See the preprint here.

  • Dec., 2019: Our paper, Blind community detection from low-rank excitations of a graph filter (with Santiago, Asu, Anna, Ali), has been accepted by IEEE TSP. This paper studies how to bypass graph topology inference to detect the underlying community/clusters of the graph. IEEE Explore.

  • Nov., 2019: I have given a talk at ESD, SUTD on Non-asymptotic Analysis of Biased Stochastic Approximation Scheme.

  • Nov., 2019: I have given a talk on Malicious Agent Detection in Social Network at the CUHK Conference on FinTech link.

  • Oct., 2019: I have given a talk at EECS, OSU on Non-asymptotic Analysis of Biased Stochastic Approximation Scheme.

  • Sept., 2019: Two papers accepted at NeurIPS 2019. This year the acceptance rate was 21.1%, and our papers are titled On the Global Convergence of (Fast) Incremental Expectation Maximization Methods (with Belhal, Eric and Marc), and Variance Reduced Policy Evaluation with Smooth Function Approximation (with Zhuoran, Zhaoran, Mingyi and Kexin). Preprints will be available soon.

  • July, 2019: One paper accepted at IEEE CDC 2019: Resilient Distributed Optimization Algorithms for Resource Allocation (with Cesar and Mahnoosh). See the preprint Here.

  • June, 2019: Our paper, Joint Network Topology and Dynamics Recovery from Perturbed Stationary Points (with Anna, Baruch, Amir), has been accepted by IEEE TSP. This paper studies the identifiability of network structure from stationary points of certain non-linear dynamics. Preprint will be available soon.

  • June, 2019: I have given a talk at LIDS, MIT on Non-asymptotic Analysis of Biased Stochastic Approximation Scheme.

  • Mar, 2019: Our paper, Non-asymptotic Analysis on Biased Stochastic Approximation Scheme (with Belhal, Blazej, Eric), has been accepted by COLT 2019. See the preprint Here.