More from the Same Authors

• 2021 Poster: An online passive-aggressive algorithm for difference-of-squares classification »
  Lawrence Saul
• 2020 Session: Orals & Spotlights Track 01: Representation/Relational »
  Laurens van der Maaten · Fei Sha
• 2018 Poster: Synthesize Policies for Transfer and Adaptation across Tasks and Environments »
  Hexiang Hu · Liyu Chen · Boqing Gong · Fei Sha
• 2018 Spotlight: Synthesize Policies for Transfer and Adaptation across Tasks and Environments »
  Hexiang Hu · Liyu Chen · Boqing Gong · Fei Sha
• 2017 Workshop: Optimal Transport and Machine Learning »
  Olivier Bousquet · Marco Cuturi · Gabriel Peyré · Fei Sha · Justin Solomon
• 2017 Poster: An Empirical Study on The Properties of Random Bases for Kernel Methods »
  Maximilian Alber · Pieter-Jan Kindermans · Kristof Schütt · Klaus-Robert Müller · Fei Sha
• 2015 : Do Shallow Kernel Methods Match Deep Neural Networks »
  Fei Sha
• 2015 : Do Shallow Kernel Methods Match Deep Neural Networks? »
  Fei Sha
• 2014 Poster: Diverse Sequential Subset Selection for Supervised Video Summarization »
  Boqing Gong · Wei-Lun Chao · Kristen Grauman · Fei Sha
• 2013 Workshop: New Directions in Transfer and Multi-Task: Learning Across Domains and Tasks »
  Urun Dogan · Marius Kloft · Tatiana Tommasi · Francesco Orabona · Massimiliano Pontil · Sinno Jialin Pan · Shai Ben-David · Arthur Gretton · Fei Sha · Marco Signoretto · Rajhans Samdani · Yun-Qian Miao · Mohammad Gheshlaghi azar · Ruth Urner · Christoph Lampert · Jonathan How
• 2013 Poster: Reshaping Visual Datasets for Domain Adaptation »
  Boqing Gong · Kristen Grauman · Fei Sha
• 2013 Poster: Similarity Component Analysis »
  Soravit Changpinyo · Kuan Liu · Fei Sha
• 2012 Poster: Non-linear Metric Learning »
  Dor Kedem · Stephen Tyree · Kilian Q Weinberger · Fei Sha · Gert Lanckriet
• 2012 Poster: Latent Coincidence Analysis: A Hidden Variable Model for Distance Metric Learning »
  Matthew F Der · Lawrence Saul
• 2012 Session: Oral Session 5 »
  Fei Sha
• 2012 Poster: Semantic Kernel Forests from Multiple Taxonomies »
  Sung Ju Hwang · Kristen Grauman · Fei Sha
• 2011 Poster: Learning a Tree of Metrics with Disjoint Visual Features »
  Sung Ju Hwang · Kristen Grauman · Fei Sha
• 2011 Poster: Maximum Covariance Unfolding : Manifold Learning for Bimodal Data »
  Vijay Mahadevan · Chi Wah Wong · Jose Costa Pereira · Tom Liu · Nuno Vasconcelos · Lawrence Saul
• 2010 Workshop: Challenges of Data Visualization »
  Barbara Hammer · Laurens van der Maaten · Fei Sha · Alexander Smola
• 2010 Talk: Manifold Learning »
  Lawrence Saul
• 2010 Poster: Unsupervised Kernel Dimension Reduction »
  Meihong Wang · Fei Sha · Michael Jordan
• 2010 Poster: Latent Variable Models for Predicting File Dependencies in Large-Scale Software Development »
  Diane Hu · Laurens van der Maaten · Youngmin Cho · Lawrence Saul · Sorin Lerner
• 2009 Workshop: Statistical Machine Learning for Visual Analytics »
  Guy Lebanon · Fei Sha
• 2009 Poster: Kernel Methods for Deep Learning »
  Youngmin Cho · Lawrence Saul
• 2008 Poster: DiscLDA: Discriminative Learning for Dimensionality Reduction and Classification »
  Simon Lacoste-Julien · Fei Sha · Michael Jordan
• 2008 Session: Oral session 1: Clustering »
  Fei Sha
• 2007 Workshop: Machine Learning for Systems Problems (Part 2) »
  Archana Ganapathi · Sumit Basu · Fei Sha · Emre Kiciman
• 2007 Workshop: Machine Learning for Systems Problems (Part 1) »
  Archana Ganapathi · Sumit Basu · Fei Sha · Emre Kiciman
• 2007 Session: Session 7: Systems and Applications »
  Fei Sha
• 2006 Talk: Large Margin Gaussian Mixture Models for Automatic Speech Recognition »
  Fei Sha · Lawrence Saul
• 2006 Poster: Graph Regularization for Maximum Variance Unfolding with an Application to Sensor Localization »
  Kilian Q Weinberger · Fei Sha · Qihui Zhu · Lawrence Saul