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20232026
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cs.LG2026

Mean Velocity Matching: Rethinking Generative Dynamics in Diffusion Models

Yunhong Zhang, Changjie Cao, Zhihua Zhang +4

This work studies prediction parameterization for stochastic generative dynamics in diffusion models. Existing velocity-based generative models provide the simplicity of learning a…

cs.LG2026

Does 1/2-Tsallis-INF Also Work Well for Best-Arm Identification?

Jingxin Zhan, Yuze Han, Zhihua Zhang

Regret minimization (RM) and best-arm identification (BAI) are two fundamental objectives in multi-armed bandits. Among regret-minimizing algorithms, -Tsallis-INF is a canonic…

cs.LG2026

Active-Trace Complexity Bounds for Moreau--Yosida Unadjusted Langevin Sampling

Yuchen Xin, Zhihua Zhang

We study the Moreau--Yosida unadjusted Langevin algorithm (MYULA) for the nonsmooth composite target \[ π(dx)\propto \exp\{-f(x)-g(x)\}\,dx, \qquad x\in\mathbb R^d, \] where \(f\)…

cs.LG2025

Last-Iterate Analyses of FTRL with the 1/2-Tsallis Entropy in Stochastic Bandits

Jingxin Zhan, Yuze Han, Zhihua Zhang

The convergence analysis of online learning algorithms is central to machine learning theory, where the last-iterate convergence is particularly important, as it captures the learn…

cs.LG2025

Follow-the-Perturbed-Leader Approaches Best-of-Both-Worlds for the m-Set Semi-Bandit Problems

Jingxin Zhan, Yuchen Xin, Chenjie Sun +1

We consider a common case of the combinatorial semi-bandit problem, the -set semi-bandit, where the learner exactly selects arms from the total arms. In the adversarial…