5 citations · 14 across the 8 of their papers we have counts for
8 papers
MaxProof: Scaling Mathematical Proof with Generative-Verifier RL and Population-Level Test-Time Scaling
Jiacheng Chen, Xinyu Zhang, Shunkai Zhang +20
We present MaxProof, a population-level test-time scaling framework for competition-level mathematical proof in the MiniMax-M3 series. M3 first trains three proof-oriented capabili…
Scalable and Independent Learning of Nash Equilibrium Policies in -Player Stochastic Games with Unknown Independent Chains
Tiancheng Qin, S. Rasoul Etesami
We study a subclass of -player stochastic games, namely, stochastic games with independent chains and unknown transition matrices. In this class of games, players control their…
Local Environment Poisoning Attacks on Federated Reinforcement Learning
Evelyn Ma, Praneet Rathi, S. Rasoul Etesami
Federated learning (FL) has become a popular tool for solving traditional Reinforcement Learning (RL) tasks. The multi-agent structure addresses the major concern of data-hungry in…
Theta-Resonance: A Single-Step Reinforcement Learning Method for Design Space Exploration
Masood S. Mortazavi, Tiancheng Qin, Ning Yan
Given an environment (e.g., a simulator) for evaluating samples in a specified design space and a set of weighted evaluation metrics -- one can use Theta-Resonance, a single-step M…
The Role of Local Steps in Local SGD
Tiancheng Qin, S. Rasoul Etesami, César A. Uribe
We consider the distributed stochastic optimization problem where agents want to minimize a global function given by the sum of agents' local functions, and focus on the hetero…
Faster Convergence of Local SGD for Over-Parameterized Models
Tiancheng Qin, S. Rasoul Etesami, César A. Uribe
Modern machine learning architectures are often highly expressive. They are usually over-parameterized and can interpolate the data by driving the empirical loss close to zero. We…
Communication-efficient Decentralized Local SGD over Undirected Networks
Tiancheng Qin, S. Rasoul Etesami, César A. Uribe
We consider the distributed learning problem where a network of agents seeks to minimize a global function . Agents have access to through noisy gradients, and they can…
Optimal Online Algorithms for File-Bundle Caching and Generalization to Distributed Caching
Tiancheng Qin, S. Rasoul Etesami
We consider a generalization of the standard cache problem called file-bundle caching, where different queries (tasks), each containing files, sequentially arrive. An onli…