NIPS Proceedingsβ

Yu-Xiang Wang

8 Papers

  • Enhancing the Locality and Breaking the Memory Bottleneck of Transformer on Time Series Forecasting (2019)
  • Online Forecasting of Total-Variation-bounded Sequences (2019)
  • Provably Efficient Q-Learning with Low Switching Cost (2019)
  • Towards Optimal Off-Policy Evaluation for Reinforcement Learning with Marginalized Importance Sampling (2019)
  • Higher-Order Total Variation Classes on Grids: Minimax Theory and Trend Filtering Methods (2017)
  • Total Variation Classes Beyond 1d: Minimax Rates, and the Limitations of Linear Smoothers (2016)
  • Differentially private subspace clustering (2015)
  • Provable Subspace Clustering: When LRR meets SSC (2013)