NIPS Proceedingsβ

Mengdi Wang

6 Papers

  • Learning low-dimensional state embeddings and metastable clusters from time series data (2019)
  • State Aggregation Learning from Markov Transition Data (2019)
  • Dimensionality Reduction for Stationary Time Series via Stochastic Nonconvex Optimization (2018)
  • Near-Optimal Time and Sample Complexities for Solving Markov Decision Processes with a Generative Model (2018)
  • Diffusion Approximations for Online Principal Component Estimation and Global Convergence (2017)
  • Accelerating Stochastic Composition Optimization (2016)