Keshu Zhang

Kari Torkkola, Mike Gardner, Christopher Schreiner, Keshu Zhang, Bob Leivian, Harry Zhang, John Summers: Understanding Driving Activity Using Ensemble Methods. Computational Intelligence in Automotive Applications 2008: 39-58

Keshu Zhang, Haifeng Li, Kari Torkkola, Mike Gardner: Adaptive learning of semantic locations and routes. Autonomics 2007: 3

Keshu Zhang, Kari Torkkola, Haifeng Li, Christopher Schreiner, Harry Zhang, Robert Mike Gardner, Zheng Zhao: A Context Aware Automatic Traffic Notification System for Cell Phones. ICDCS Workshops 2007: 48

Keshu Zhang, Haifeng Li, Kari Torkkola, Mike Gardner: Adaptive Learning of Semantic Locations and Routes. LoCA 2007: 193-210

Harry Zhang, Christopher Schreiner, Keshu Zhang, Kari Torkkola: Naturalistic use of cell phones in driving and context-based user assistance. Mobile HCI 2007: 273-276

Haifeng Li, Xin Chen, Keshu Zhang, Tao Jiang: A General Framework for Biclustering Gene Expression Data. J. Bioinformatics and Computational Biology 4(4): 911-993 (2006)

Haifeng Li, Tao Jiang, Keshu Zhang: Efficient and robust feature extraction by maximum margin criterion. IEEE Transactions on Neural Networks 17(1): 157-165 (2006)

Kari Torkkola, Mike Gardner, Christopher Schreiner, Keshu Zhang, Bob Leivian, John Summers: Sensor Selection for Driving State Recognition. IJCNN 2006: 4734-4739

Keshu Zhang, X. Rong Li, Yunmin Zhu: Optimal update with out-of-sequence measurements. IEEE Transactions on Signal Processing 53(6): 1992-2004 (2005)

Haifeng Li, Keshu Zhang, Tao Jiang: The Regularized EM Algorithm. AAAI 2005: 807-812

Haifeng Li, Keshu Zhang, Tao Jiang: Robust and Accurate Cancer Classification with Gene Expression Profiling. CSB 2005: 310-321

Haifeng Li, Keshu Zhang, Tao Jiang: Minimum Entropy Clustering and Applications to Gene Expression Analysis. CSB 2004: 142-151

Haifeng Li, Tao Jiang, Keshu Zhang: Efficient and Robust Feature Extraction by Maximum Margin Criterion. NIPS 2003

Yunmin Zhu, Zhisheng You, Juan Zhao, Keshu Zhang, X. Rong Li: The optimality for the distributed Kalman filtering fusion with feedback. Automatica 37(9): 1489-1493 (2001)