Journal Publications

  • Xi Chen, Qihang Lin, Seyoung Kim, Jamie Carbonell and Eric P. Xing. Smoothing Proximal Gradient Method for General Structured Sparse Learning. Annals of Applied Statistics (AOAS), 6(2): 719--752, 2012 [pdf] [Code] (An earlier version appeared in UAI 2011)
  • Xi Chen and Han Liu. An Efficient Optimization Algorithm for Structured Sparse CCA, with Applications to eQTL Mapping. Statistics in Biosciences , 4(1):3--26, 2012 [pdf] [Code] (An earlier version appeared in AISTATS 2012)

Peer Reviewed Conference Papers

  • Xi Chen, Qihang Lin and Dengyong Zhou. Optimistic Knowledge Gradient for Optimal Budget Allocation in Crowdsourcing. International Conference on Machine Learning (ICML), 2013. [pdf][Appendix][Tech Report]
  • Xi Chen, Paul N. Bennett, Kevyn Collins-Thompson and Eric Horvitz. Pairwise Ranking Aggregation in a Crowdsourced Setting. ACM International Conference on Web Search and Data Mining (WSDM), 2013 [pdf]
  • Xi Chen, Qihang Lin and Javier Peña. Optimal Regularized Dual Averaging Methods for Stochastic Optimization. Advances in Neural Information Processing Systems (NIPS), 2012. [pdf][appendix]
  • Xi Chen, Han Liu and Jaime Carbonell. Structured Sparse Canonical Correlation Analysis. International Conference on Artificial Intelligence and Statistics (AISTATS), 2012. Oral (26/400 ≈ 6%) [pdf][Code]
  • Junming Yin, Xi Chen and Eric P. Xing. Group Sparse Additive Models. International Conference on Machine Learning (ICML) , 2012. [pdf] [Arxiv long version]
  • Xi Chen, Jingrui He, Rick Lawrence and Jaime Carbonell, Adaptive Multi-task Sparse Learning with an Application to fMRI Study. SIAM International Conference on Data Mining (SDM), 2012. Oral (53/363≈ 14%) [pdf]
  • Xi Chen, Qihang Lin, Seyoung Kim, Jaime Carbonell and Eric P. Xing. Smoothing Proximal Gradient Method for General Structured Sparse Learning. Uncertainty in Artificial Intelligence (UAI), 2011 [pdf]
  • Xi Chen, Yanjun Qi, Bing Bai, Qihang Lin and Jaime Carbonell. Sparse Latent Semantic Analysis. SIAM International Conference on Data Mining (SDM), 2011. [pdf] [Code]
  • Xiong Liang, Xi Chen and Jeff Schneider. Direct Robust Matrix Factorization for Anomaly Detection. International Conference on Data Mining (ICDM), 2011. [pdf] [Code]
  • Han Liu, Xi Chen, John Lafferty and Larry Wasserman. Graph-valued Regression. Advances in Neural Information Processing Systems (NIPS), 2010. Spotlight (73/1219 ≈6\%) [pdf] [Arxiv long version]
  • Han Liu and Xi Chen. Multivariate Dyadic Regression Trees for Sparse Learning Problems. Advances in Neural Information Processing Systems (NIPS), , 2010. [pdf]
  • Xi Chen, Bing Bai, Yanjun Qi, Qihang Lin and Jaime Carbonell. Learning Preferences using Millions of Parameters by Enforcing Sparsity. International Conference on Data Mining (ICDM) , 2010. [pdf]
  • Xi Chen, Yan Liu, Han Liu and Jaime Carbonell. Learning Spatial-Temporal Varying Graphs with Applications to Climate Data Analysis. AAAI Conference on Artificial Intelligence, 2010. [pdf]
  • Xiong Liang, Xi Chen, T.K. Huang, Jeff Schneider and Jaime Carbonell. Time-evolving collaborative filtering. SIAM International Conference on Data Mining (SDM) , 2010. [pdf] [Code]
  • Han Liu and Xi Chen. Nonparametric Greedy Algorithms for the Sparse Learning Problem. Advances in Neural Information Processing Systems (NIPS), 2009. [pdf]
  • Xi Chen, Weike Pan, James Kwok and Jaime Carbonell. Accelerated Gradient Method for Multi-Task Sparse Learning Problem. International Conference on Data Mining (ICDM) , 2009 [pdf]

Working Papers

  • Qihang Lin, Xi Chen and Javier Peña. A Sparsity Preserving Stochastic Gradient Method for Composite Optimization. [pdf]


(c) 2012 Xi Chen. Design by FCT