NewEvery arXiv paper, its researchers & institutions — mapped.
papers

Publications (28)

cs.LG2017

Deep Primal-Dual Reinforcement Learning: Accelerating Actor-Critic using Bellman Duality

Woon Sang Cho, Mengdi Wang

cs.LG2018

Scalable Bilinear $π$ Learning Using State and Action Features

Yichen Chen, Lihong Li, Mengdi Wang

stat.ML2016

Stochastic Primal-Dual Methods and Sample Complexity of Reinforcement Learning

Yichen Chen, Mengdi Wang

cs.CC2017

Lower Bound On the Computational Complexity of Discounted Markov Decision Problems

Yichen Chen, Mengdi Wang

cs.LG2019

Learning to Control in Metric Space with Optimal Regret

Lin F. Yang, Chengzhuo Ni, Mengdi Wang

math.OC2019

Improved Oracle Complexity of Variance Reduced Methods for Nonsmooth Convex Stochastic Composition Optimization

Tianyi Lin, Chenyou Fan, Mengdi Wang

cs.CL2019

Towards Coherent and Cohesive Long-form Text Generation

Woon Sang Cho, Pengchuan Zhang, Yizhe Zhang +5

math.OC2018

Multi-Level Stochastic Gradient Methods for Nested Composition Optimization

Shuoguang Yang, Mengdi Wang, Ethan X. Fang

stat.ML2014

Stochastic Compositional Gradient Descent: Algorithms for Minimizing Compositions of Expected-Value Functions

Mengdi Wang, Ethan X. Fang, Han Liu

math.OC2017

Strong NP-Hardness for Sparse Optimization with Concave Penalty Functions

Yichen Chen, Dongdong Ge, Mengdi Wang +3

cs.LG2017

Primal-Dual $π$ Learning: Sample Complexity and Sublinear Run Time for Ergodic Markov Decision Problems

Mengdi Wang

cs.CV2018

Graph-Adaptive Pruning for Efficient Inference of Convolutional Neural Networks

Mengdi Wang, Qing Zhang, Jun Yang +2

math.OC2018

Approximation Methods for Bilevel Programming

Saeed Ghadimi, Mengdi Wang

math.OC2017

Finite-sum Composition Optimization via Variance Reduced Gradient Descent

Xiangru Lian, Mengdi Wang, Ji Liu

cs.LG2019

Sample-Optimal Parametric Q-Learning Using Linearly Additive Features

Lin F. Yang, Mengdi Wang

math.OC2017

Randomized Linear Programming Solves the Discounted Markov Decision Problem In Nearly-Linear (Sometimes Sublinear) Running Time

Mengdi Wang

math.OC2017

Near-Optimal Stochastic Approximation for Online Principal Component Estimation

Chris Junchi Li, Mengdi Wang, Han Liu +1

cs.LG2019

Reinforcement Learning in Feature Space: Matrix Bandit, Kernels, and Regret Bound

Lin F. Yang, Mengdi Wang

math.OC2018

Adaptive Low-Nonnegative-Rank Approximation for State Aggregation of Markov Chains

Yaqi Duan, Mengdi Wang, Zaiwen Wen +1

cs.LG2018

Dimensionality Reduction for Stationary Time Series via Stochastic Nonconvex Optimization

Minshuo Chen, Lin Yang, Mengdi Wang +1

stat.ML2015

Random Multi-Constraint Projection: Stochastic Gradient Methods for Convex Optimization with Many Constraints

Mengdi Wang, Yichen Chen, Jialin Liu +1

cs.LG2019

RL4health: Crowdsourcing Reinforcement Learning for Knee Replacement Pathway Optimization

Hao Lu, Mengdi Wang

math.OC2016

Accelerating Stochastic Composition Optimization

Mengdi Wang, Ji Liu, Ethan X. Fang

math.OC2019

Near-Optimal Time and Sample Complexities for Solving Discounted Markov Decision Process with a Generative Model

Aaron Sidford, Mengdi Wang, Xian Wu +2

stat.ML2018

Diffusion Approximations for Online Principal Component Estimation and Global Convergence

Chris Junchi Li, Mengdi Wang, Han Liu +1

cs.LG2017

Online Factorization and Partition of Complex Networks From Random Walks

Lin F. Yang, Vladimir Braverman, Tuo Zhao +1

stat.ML2018

Estimation of Markov Chain via Rank-Constrained Likelihood

Xudong Li, Mengdi Wang, Anru Zhang

cs.LG2019

Feature-Based Q-Learning for Two-Player Stochastic Games

Zeyu Jia, Lin F. Yang, Mengdi Wang