2 citations · 3 across the 5 of their papers we have counts for
6 papers
Revisiting Decentralized Online Convex Optimization with Compressed Communication
Hao Zhou, Xiaoyu Wang, Chang Yao +2
Decentralized online convex optimization (D-OCO) is a popular framework for distributed applications with streaming data. To tackle the communication bottleneck, previous studies h…
Improved Approximate Regret for Decentralized Online Continuous Submodular Maximization via Reductions
Yuanyu Wan, Yu Shen, Dingzhi Yu +2
To expand the applicability of decentralized online learning, previous studies have proposed several algorithms for decentralized online continuous submodular maximization (D-OCSM)…
Dataset Ownership Verification for Pre-trained Masked Models
Yuechen Xie, Jie Song, Yicheng Shan +5
High-quality open-source datasets have emerged as a pivotal catalyst driving the swift advancement of deep learning, while facing the looming threat of potential exploitation. Prot…
Sampling-Aware Quantization for Diffusion Models
Qian Zeng, Jie Song, Yuanyu Wan +2
Diffusion models have recently emerged as the dominant approach in visual generation tasks. However, the lengthy denoising chains and the computationally intensive noise estimation…
Optimal and Efficient Algorithms for Decentralized Online Convex Optimization
Yuanyu Wan, Tong Wei, Bo Xue +2
We investigate decentralized online convex optimization (D-OCO), in which a set of local learners are required to minimize a sequence of global loss functions using only local comp…
Improved Regret for Bandit Convex Optimization with Delayed Feedback
Yuanyu Wan, Chang Yao, Mingli Song +1
We investigate bandit convex optimization (BCO) with delayed feedback, where only the loss value of the action is revealed under an arbitrary delay. Let denote the di…