3 papers
math.OC2026
Near-Optimal Lower Bounds for Randomized Algorithms in Exact Value Zeroth-Order Convex Optimization
Haihan Zhang, Chenheng Zhang, Zhiquan Qi +1
Whether exact scalar feedback intrinsically incurs the additional dimension paid by known zeroth-order methods remains open even for Lipschitz convex optimization. For a univer…
cs.LG2026
SpecGradFilter: A Spectral Gradient Filtering Framework for Taming Federated Heterogeneity
Liyang Yuan, Yibo Yang, Dandan Guo +2
Federated Learning (FL) is fundamentally challenged by statistical heterogeneity, where non-identically distributed (non-IID) data induces client drift that severely hampers global…
cs.LG2025
On Leveraging Unlabeled Data for Concurrent Positive-Unlabeled Classification and Robust Generation
Bing Yu, Ke Sun, He Wang +2
The scarcity of class-labeled data is a ubiquitous bottleneck in many machine learning problems. While abundant unlabeled data typically exist and provide a potential solution, it…