70 citations · 880 across the 62 of their papers we have counts for
7 papers · 1 filter
Waring-Goldbach problem in short intervals
Mengdi Wang
Let and be positive integers. Let be a real number. In this paper, we establish that if and , then every sufficiently large natural numb…
Learning Markov models via low-rank optimization
Ziwei Zhu, Xudong Li, Mengdi Wang +1
Modeling unknown systems from data is a precursor of system optimization and sequential decision making. In this paper, we focus on learning a Markov model from a single trajectory…
Reinforcement Learning in Feature Space: Matrix Bandit, Kernels, and Regret Bound
Lin F. Yang, Mengdi Wang
Exploration in reinforcement learning (RL) suffers from the curse of dimensionality when the state-action space is large. A common practice is to parameterize the high-dimensional…
Feature-Based Q-Learning for Two-Player Stochastic Games
Zeyu Jia, Lin F. Yang, Mengdi Wang
Consider a two-player zero-sum stochastic game where the transition function can be embedded in a given feature space. We propose a two-player Q-learning algorithm for approximatin…
Learning low-dimensional state embeddings and metastable clusters from time series data
Yifan Sun, Yaqi Duan, Hao Gong +1
This paper studies how to find compact state embeddings from high-dimensional Markov state trajectories, where the transition kernel has a small intrinsic rank. In the spirit of di…
Learning to Control in Metric Space with Optimal Regret
Lin F. Yang, Chengzhuo Ni, Mengdi Wang
We study online reinforcement learning for finite-horizon deterministic control systems with {\it arbitrary} state and action spaces. Suppose that the transition dynamics and rewar…