News

• [New Member] 11/2023 New Ph.D. student Hao Ban (BS and MS from Southeast University, China) will join our group in Spring 2024. Welcome, Hao!

• [Publication] 09/2023 Five papers accepted in NeurIPS 2023 with one spotlight presentation! The topics span over Hessian-free bilevel optimization, federated learning, continual learning and multi-objective learning. Big congratulations to my students Yifan, Peiyao and Hao, and many thanks to my collaborators!

• • Simple federated bilevel learning

  • Direction-oriented multi-objective/task learning with simple algorithms and enhanced analysis

  • Achieve O(\epsilon^{-1.5}) sample complexity in stochastic Hessian-free bilevel optimization

  • Corset selection for continual learning

  • Non-convex bilevel optimization with time-varying objective functions

• [Grant] 07/2023 I received a grant as site PI @ UB in collaboration with Dr. Shiqian Ma (Rice University) on Distributed Optimization in Multi-Agent Systems. Many thanks to NSF!

• [Grant] 07/2023 I received a grant as Lead PI @ UB in collaboration with Dr. Shiqian Ma (Rice University) on Large-Scale Bilevel Optimization. Many thanks to NSF!

• [Publication] 07/2023 Our work on fair resource allocation over communication network has been accepted by ACM MobiHoc 2023! (acceptance rate: 21.9%)

• [Talk] 06/2023 Gave an invited talk on bilevel optimization and continual learning at SIAM Conference on Optimization.

• [Manuscript] 06/2023 Two new manuscripts on Simple federated bilevel learning and Direction-oriented multi-objective/task learning are available online. Codes can be found in GitHub.

• [Publication] 04/2023 Our two submissions on federated bilevel optimization: Achieving Linear Speedup and Aggregated Iterative Differentiation have been accepted at ICML 2023 (acceptance rate: 27.9%). Congrats to my students Peiyao and Dewei! This is also Peiyao's first work. Keep going!

• [Award] 02/2023 Selected as Top Reviewer in AISTATS 2023.

• [Manuscript] 01/2023 A manuscript on fair resource allocation over communication network is available online: Network Utility Maximization with Bilevel Learning. We propose a new distributed data-driven bilevel optimization approach for network utility maximization with unknown user utilities!

• [Award] 11/2022 Our NeurIPS 2022 paper on Unified Analysis for Bilevel Optimization received Spotlight (5% acceptance rate).

• [Service] 10/2022 Will serve as TPC member of ACM MobiHoc 2023. Please consider submitting your best work to the conference!

• [Talk] 10/2022 Gave an invited talk in the session “Bilevel Stochastic Methods for Optimization and Learning” at the 2022 INFORMS Annual Meeting, Indianapolis, IN.

• [Publication] 09/2022 Two papers on Hessian-Free Bilevel Optimization and Unified Analysis for Bilevel Optimization have been accepted by NeurIPS 2022.

• [Publication] 09/2022 Our paper, “Lower Bounds and Accelerated Algorithms for Bilevel Optimization”, has been accepted by JMLR 2022 with minor revision.