Fei Sha

Zhixiang Eddie Xu, Minmin Chen, Kilian Q. Weinberger, Fei Sha: An alternative text representation to TF-IDF and Bag-of-Words. CoRR abs/1301.6770 (2013)

Tomer Levinboim, Fei Sha: Learning the Kernel Matrix with Low-Rank Multiplicative Shaping. AAAI 2012

Zhixiang Eddie Xu, Minmin Chen, Kilian Q. Weinberger, Fei Sha: From sBoW to dCoT marginalized encoders for text representation. CIKM 2012: 1879-1884

Boqing Gong, Yuan Shi, Fei Sha, Kristen Grauman: Geodesic flow kernel for unsupervised domain adaptation. CVPR 2012: 2066-2073

Minmin Chen, Zhixiang Eddie Xu, Kilian Q. Weinberger, Fei Sha: Marginalized Denoising Autoencoders for Domain Adaptation. ICML 2012

Yuan Shi, Fei Sha: Information-Theoretical Learning of Discriminative Clusters for Unsupervised Domain Adaptation. ICML 2012

Dingchao Lu, Fei Sha: Predicting Likability of Speakers with Gaussian Processes. INTERSPEECH 2012

Sung Ju Hwang, Kristen Grauman, Fei Sha: Semantic Kernel Forests from Multiple Taxonomies. NIPS 2012: 1727-1735

Dor Kedem, Stephen Tyree, Kilian Q. Weinberger, Fei Sha, Gert R. G. Lanckriet: Non-linear Metric Learning. NIPS 2012: 2582-2590

Bin Liu, Yurong Jiang, Fei Sha, Ramesh Govindan: Cloud-enabled privacy-preserving collaborative learning for mobile sensing. SenSys 2012: 57-70

Minmin Chen, Zhixiang Eddie Xu, Kilian Q. Weinberger, Fei Sha: Marginalized Denoising Autoencoders for Domain Adaptation. CoRR abs/1206.4683 (2012)

Meihong Wang, Fei Sha: Information Theoretical Clustering via Semidefinite Programming. Journal of Machine Learning Research - Proceedings Track 15: 761-769 (2011)

Junping Zhang, Ben Tan, Fei Sha, Li He: Predicting Pedestrian Counts in Crowded Scenes With Rich and High-Dimensional Features. IEEE Transactions on Intelligent Transportation Systems 12(4): 1037-1046 (2011)

Matthew E. Taylor, Brian Kulis, Fei Sha: Metric learning for reinforcement learning agents. AAMAS 2011: 777-784

Sung Ju Hwang, Fei Sha, Kristen Grauman: Sharing features between objects and their attributes. CVPR 2011: 1761-1768

Xu Li, Fei Sha: Application of moment invariants in checking the overall dimension of the head cover. EMEIT 2011: 932-935

Geoffrey Zweig, Patrick Nguyen, Dirk Van Compernolle, Kris Demuynck, Les E. Atlas, Pascal Clark, Gregory Sell, Meihong Wang, Fei Sha, Hynek Hermansky, Damianos Karakos, Aren Jansen, Samuel Thomas, Sivaram G. S. V. S., Sam Bowman, Justine T. Kao: Speech recognitionwith segmental conditional random fields: A summary of the JHU CLSP 2010 Summer Workshop. ICASSP 2011: 5044-5047

Zhuoliang Kang, Kristen Grauman, Fei Sha: Learning with Whom to Share in Multi-task Feature Learning. ICML 2011: 521-528

Leslie Cheung, Leana Golubchik, Fei Sha: A Study of Web Services Performance Prediction: A Client's Perspective. MASCOTS 2011: 75-84

Sung Ju Hwang, Kristen Grauman, Fei Sha: Learning a Tree of Metrics with Disjoint Visual Features. NIPS 2011: 621-629

Zhixiang Eddie Xu, Kilian Q. Weinberger, Fei Sha: Rapid Feature Learning with Stacked Linear Denoisers. CoRR abs/1105.0972 (2011)

Yuan Shi, Yung-Kyun Noh, Fei Sha, Daniel D. Lee: Learning Discriminative Metrics via Generative Models and Kernel Learning. CoRR abs/1109.3940 (2011)

Sriram Sankararaman, Fei Sha, Jack F. Kirsch, Michael I. Jordan, Kimmen Sjölander: Active site prediction using evolutionary and structural information. Bioinformatics 26(5): 617-624 (2010)

Dian Gong, Fei Sha, Gérard G. Medioni: Locally Linear Denoising on Image Manifolds. Journal of Machine Learning Research - Proceedings Track 9: 265-272 (2010)

Chih-Chieh Cheng, Fei Sha, Lawrence K. Saul: Online Learning and Acoustic Feature Adaptation in Large-Margin Hidden Markov Models. J. Sel. Topics Signal Processing 4(6): 926-942 (2010)

Meihong Wang, Fei Sha, Michael I. Jordan: Unsupervised Kernel Dimension Reduction. NIPS 2010: 2379-2387

Chih-Chieh Cheng, Fei Sha, Lawrence K. Saul: Large-margin feature adaptation for automatic speech recognition. ASRU 2009: 87-92

Chih-Chieh Cheng, Fei Sha, Lawrence K. Saul: Matrix updates for perceptron training of continuous density hidden Markov models. ICML 2009: 20

Chih-Chieh Cheng, Fei Sha, Lawrence K. Saul: A fast online algorithm for large margin training of continuous density hidden Markov models. INTERSPEECH 2009: 668-671

Nilesh N. Dalvi, Philip Bohannon, Fei Sha: Robust web extraction: an approach based on a probabilistic tree-edit model. SIGMOD Conference 2009: 335-348

Simon Lacoste-Julien, Fei Sha, Michael I. Jordan: DiscLDA: Discriminative Learning for Dimensionality Reduction and Classification. NIPS 2008: 897-904

Fei Sha, Yuanqing Lin, Lawrence K. Saul, Daniel D. Lee: Multiplicative Updates for Nonnegative Quadratic Programming. Neural Computation 19(8): 2004-2031 (2007)

Andrea Frome, Yoram Singer, Fei Sha, Jitendra Malik: Learning Globally-Consistent Local Distance Functions for Shape-Based Image Retrieval and Classification. ICCV 2007: 1-8

Jens Nilsson, Fei Sha, Michael I. Jordan: Regression on manifolds using kernel dimension reduction. ICML 2007: 697-704

Fei Sha, Y. Albert Park, Lawrence K. Saul: Multiplicative Updates for L₁-Regularized Linear and Logistic Regression. IDA 2007: 13-24

Fei Sha, Lawrence K. Saul: Large Margin Hidden Markov Models for Automatic Speech Recognition. NIPS 2006: 1249-1256

Kilian Q. Weinberger, Fei Sha, Qihui Zhu, Lawrence K. Saul: Graph Laplacian Regularization for Large-Scale Semidefinite Programming. NIPS 2006: 1489-1496

Fei Sha, Lawrence K. Saul: Analysis and extension of spectral methods for nonlinear dimensionality reduction. ICML 2005: 784-791

Kilian Q. Weinberger, Fei Sha, Lawrence K. Saul: Learning a kernel matrix for nonlinear dimensionality reduction. ICML 2004

Fei Sha, Lawrence K. Saul: Real-Time Pitch Determination of One or More Voices by Nonnegative Matrix Factorization. NIPS 2004

Fei Sha, Lawrence K. Saul, Daniel D. Lee: Multiplicative Updates for Large Margin Classifiers. COLT 2003: 188-202

Lawrence K. Saul, Fei Sha, Daniel D. Lee: Statistical signal processing with nonnegativity constraints. INTERSPEECH 2003

Fei Sha, Fernando C. N. Pereira: Shallow Parsing with Conditional Random Fields. HLT-NAACL 2003

Fei Sha, Lawrence K. Saul, Daniel D. Lee: Multiplicative Updates for Nonnegative Quadratic Programming in Support Vector Machines. NIPS 2002: 1041-1048

Fei Sha, Georges Gardarin, Laurent Némirovski: A Semi-Structured Data Cartridge for Relational Databases. ICDE 2000: 192

Fei Sha, Georges Gardarin, Laurent Némirovski: Managing Semistructured Data in Object-Relational DBMS. Proc. 15èmes Journées Bases de Données Avancées, BDA 1999: 101-115

Georges Gardarin, Fei Sha, Tuyet-Tram Dang-Ngoc: XML-based Components for Federating Multiple Heterogeneous Data Sources. ER 1999: 506-519

Luc Bouganim, Tatiana Chan-Sine-Ying, Tuyet-Tram Dang-Ngoc, Jean-Luc Darroux, Georges Gardarin, Fei Sha: Miro Web: Integrating Multiple Data Sources through Semistructured Data Types. VLDB 1999: 750-753

Georges Gardarin, Fei Sha: Using Conceptual Modeling and Intelligent Agents to Integrate Semi-structured Documents in Federated Databases. Conceptual Modeling 1997: 87-99

Georges Gardarin, Fei Sha, Zhao-Hui Tang: Calibrating the Query Optimizer Cost Model of IRO-DB, an Object-Oriented Federated Database System. BDA 1996: 37-56

Georges Gardarin, Fei Sha, Zhao-Hui Tang: Calibrating the Query Optimizer Cost Model of IRO-DB, an Object-Oriented Federated Database System. VLDB 1996: 378-389

Tülin Atmaca, Guy Pujolle, Fei Sha: Performance Analysis of an Access Control Strategy in Integrated Networks. Computer Networks and ISDN Systems 24(5): 421-434 (1992)