1 citations · 1 across the 10 of their papers we have counts for
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Rollplex: Cross-Phase GPU Spatial Sharing for Vision Language Model Post-Training
Hanfeng Lu, Tianyu Feng, Suyi Li +8
Vision-language models (VLMs) enable embodied agents to reason and act from visual observations and language instructions. Reinforcement learning (RL) post-training enhances these…
Towards Fully Parameter-Free Stochastic Optimization: Grid Search with Self-Bounding Analysis
Yuheng Zhao, Yu-Hu Yan, Amit Attia +3
Parameter-free stochastic optimization aims to design algorithms that are agnostic to the underlying problem parameters while still achieving convergence rates competitive with opt…
Gradient-Variation Regret Bounds for Unconstrained Online Learning
Yuheng Zhao, Andrew Jacobsen, Nicolò Cesa-Bianchi +1
We develop parameter-free algorithms for unconstrained online learning with regret guarantees that scale with the gradient variation $V_T(u) = \sum_{t=2}^T \|\nabla f_t(u)-\nabla f…
Gradient-Variation Online Adaptivity for Accelerated Optimization with Hölder Smoothness
Yuheng Zhao, Yu-Hu Yan, Kfir Yehuda Levy +1
Smoothness is known to be crucial for acceleration in offline optimization, and for gradient-variation regret minimization in online learning. Interestingly, these two problems are…
Reinforcement Learning Optimization for Large-Scale Learning: An Efficient and User-Friendly Scaling Library
Weixun Wang, Shaopan Xiong, Gengru Chen +38
We introduce ROLL, an efficient, scalable, and user-friendly library designed for Reinforcement Learning Optimization for Large-scale Learning. ROLL caters to three primary user gr…