DAP-BERT: Differentiable Architecture Pruning of BERT. - Chung-Yiu Yau; Haoli Bai; Irwin King; Michael R. Lyu (ICONIP (1), 2021)

Multi-agent Performative Prediction with Greedy Deployment and Consensus Seeking Agents. - Qiang Li 017; Chung-Yiu Yau; Hoi-To Wai (NeurIPS, 2022)

Distributed Optimization for Overparameterized Problems: Achieving Optimal Dimension Independent Communication Complexity. - Bingqing Song; Ioannis C. Tsaknakis; Chung-Yiu Yau; Hoi-To Wai; Mingyi Hong 001 (NeurIPS, 2022)

DoCoM-SGT: Doubly Compressed Momentum-assisted Stochastic Gradient Tracking Algorithm for Communication Efficient Decentralized Learning. - Chung-Yiu Yau; Hoi-To Wai (CoRR, 2022)

Fully Stochastic Distributed Convex Optimization on Time-Varying Graph with Compression. - Chung-Yiu Yau; Hoi-To Wai (CDC, 2023)

Network Effects in Performative Prediction Games. - Xiaolu Wang; Chung-Yiu Yau; Hoi-To Wai (ICML, 2023)

DoCoM: Compressed Decentralized Optimization with Near-Optimal Sample Complexity. - Chung-Yiu Yau; Hoi-To Wai (Trans. Mach. Learn. Res., 2023)

EMC2: Efficient MCMC Negative Sampling for Contrastive Learning with Global Convergence. - Chung-Yiu Yau; Hoi-To Wai; Parameswaran Raman; Soumajyoti Sarkar; Mingyi Hong 001 (ICML, 2024)

EMC2: Efficient MCMC Negative Sampling for Contrastive Learning with Global Convergence. - Chung-Yiu Yau; Hoi-To Wai; Parameswaran Raman; Soumajyoti Sarkar; Mingyi Hong 001 (CoRR, 2024)

Fully Stochastic Primal-dual Gradient Algorithm for Non-convex Optimization on Random Graphs. - Chung-Yiu Yau; Haoming Liu; Hoi-To Wai (CoRR, 2024)

A Two-timescale Primal-dual Algorithm for Decentralized Optimization with Compression. - Haoming Liu; Chung-Yiu Yau; Hoi-To Wai (ICASSP, 2025)

RoSTE: An Efficient Quantization-Aware Supervised Fine-Tuning Approach for Large Language Models. - Quan Wei 001; Chung-Yiu Yau; Hoi-To Wai; Yang Zhao; Dongyeop Kang; Youngsuk Park; Mingyi Hong 001 (CoRR, 2025)