01/24/2021: Paper on distributed online LQR accepted in ACC 21. [link]
01/15/2021: Paper on distributed non-convex optimization accepted in TAC. [link]
12/02/2020: Paper on dynamic regret analysis of strongly convex, smooth online optimization accepted in AAAI 21. [link]
11/17/2020: Paper on asymptotic convergence of distributed mirror descent with integral feedback accepted in L-CSS. [link]
10/29/2020: Invited talk (virtual) in IE department at University of Pittsburgh.
10/28/2020: Invited talk (virtual) at Mitsubishi Electric Research Laboratories (MERL).
09/25/2020: Paper on statistical and topological properties of sliced probability divergences accepted in NeurIPS 20 (Spotlight). [link]
08/17/2020: Elevated to IEEE Senior Member.
08/11/2020: Two papers accepted in Asilomar 20.
08/06/2020: NSF Award on “Real-Time Learning and Control of Stochastic Nanostructure Growth Processes Through in situ Dynamic Imaging”! [link]
07/18/2020: I will be on the program committee of “International Workshop on Federated Learning for User Privacy and Data Confidentiality” in ICML 20. [link]
06/01/2020: Paper on generalization bounds for entropic optimal features accepted in ICML 20. [link]
02/07/2020: Invited talk at ITA 20 Workshop.
01/16/2020: Paper on distributed parameter estimation in randomized shallow networks accepted in ACC 20. [link]
12/18/2019: Congrats to my student, Yinsong Wang, for earning the 1st place in poster session for ISEN’s graduate students. He presented our work on general scoring rules for sampling random features. [link]
12/05/2019: Paper on online mechanism for resource allocation in networks accepted in TCNS. [link]
10/20/2019: Chair of the session “limits of large-scale statistical learning” at INFORMS 19.
10/19/2019: Paper on Byzantine-resilient distributed state estimation accepted in TAC. [link]
09/27/2019: “NSF Awards $1.5 Million TRIPODS Institute to Texas A&M to Bolster Data-Driven Discovery”. Excited to be part of this team! [link]
08/26/2019: NSF Award on “Collaborative Online Optimization for Efficient Model-Based Learning” ! [link]
07/10/2019: Pedro Tecchio presented our work on distributed network localization in ACC 19.
05/30/2019: Lili Su presented a poster about our work on Byzantine-resilient distributed state estimation in the inaugural L4DC workshop.
05/18/2019: Attended IISE 19 Annual Meeting.
05/01/2019: Award from Texas A&M Institute of Data Science! [link]
04/29/2019: Presented a talk on data-dependent kernel approximation in the Model Reduction Workshop at TAMU.
03/22/2019: Presented a talk on “generalization bounds for learning from batch and streaming data” in the STAT department at TAMU.
03/18/2019: Presented a talk on “generalization bounds for learning from batch and streaming data” in the CS department at TAMU.
03/01/2019: Presented a talk on “generalization bounds for learning from batch and streaming data” in the ECE department at TAMU.
02/13/2019: Invited talk at ITA 19 Workshop.
01/30/2019: Paper on distributed network localization accepted in ACC 19.
01/22/2019: Our work on kernel approximation featured in Texas A&M Today. [link]
12/17/2018: Attended CDC 18.
12/15/2018: Our project on “trade-offs between approximation and generalization in learning systems” is funded by Texas A&M Triads for Transformation!
12/03/2018: Attended NeurIPS 18.
11/03/2018: Invited talk at INFORMS 18 Annual Meeting.
10/19/2018: Attended the 10th Annual Winedale Workshop. [link]
10/03/2018: Attended Allerton 18.
09/15/2018: Paper on data-dependent random features accepted in CDC 18.
09/04/2018: Paper on learning bounds for greedy approximation accepted in NeurIPS 18. [link]
09/01/2018: First day at Texas A&M!