5 papers
Federated stochastic bilevel optimization with fully first-order gradients
Yihan Zhang, Rohit Dhaipule, Chiu C Tan +2
Federated stochastic bilevel optimization has been actively studied in recent years due to its widespread applications in machine learning. However, most existing federated stochas…
EMA: Efficient Model Adaptation for Learning-based Systems
Daiyang Yu, Xinyu Chen, Yihan Zhang +3
Machine learning (ML) is increasingly applied to optimize system performance in tasks such as resource management and network simulation. Unlike traditional ML tasks (e.g., image c…
Data-driven Symbolic Closure for Turbulence Modeling in the Lattice Boltzmann Framework
Yujie Fu, Yihan Zhang, Wanru Deng +1
Turbulence modeling within the Lattice Boltzmann Method (LBM) framework has long relied on traditional algebraic sub-grid scale (SGS) models, which often suffer from over-dissipati…
Evaluating LLMs in the Context of a Functional Programming Course: A Comprehensive Study
Yihan Zhang, Brigitte Pientka, Xujie Si
Large-Language Models (LLMs) are changing the way learners acquire knowledge outside the classroom setting. Previous studies have shown that LLMs seem effective in generating to sh…
Nonconvex Decentralized Stochastic Bilevel Optimization under Heavy-Tailed Noise
Xinwen Zhang, Yihan Zhang, Heng Liang +1
Existing decentralized stochastic optimization methods assume the lower-level loss function is strongly convex and the stochastic gradient noise has finite variance. These strong a…