Publications By Type

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Journal Papers

  • Fast Similarity Search for Learned Metrics
    Brian Kulis, Prateek Jain, & Kristen Grauman
    IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 31, no. 12, pp. 2143--2157, 2009.
    [pdf]

  • Low-Rank Kernel Learning with Bregman Matrix Divergences
    Brian Kulis, Matyas Sustik, & Inderjit Dhillon
    Journal of Machine Learning Research, 10 (Feb): 341--376, 2009.
    [pdf]

  • Semi-Supervised Graph Clustering: A Kernel Approach
    Brian Kulis, Sugato Basu, Inderjit Dhillon, & Raymond Mooney
    Machine Learning, vol. 74, no. 1, pp. 1--22, 2009.
    [pdf]

  • Weighted Graph Cuts without Eigenvectors: A Multilevel Approach
    Inderjit Dhillon, Yuqiang Guan, & Brian Kulis
    IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 29, no. 11, pp. 1944--1957, 2007.
    [pdf] [code]

  • Tracking Evolving Communities in Large Linked Networks
    John Hopcroft, Omar Khan, Brian Kulis, & Bart Selman
    Proc. of the National Academy of Sciences, vol. 101, pp. 5249--5253, April 2004.
    [pdf]

Conference Papers

  • Learning to Hash with Binary Reconstructive Embeddings
    Brian Kulis & Trevor Darrell
    In Neural Information Processing Systems (NIPS), 2009.
    [pdf]

  • Kernelized Locality-Sensitive Hashing for Scalable Image Search
    Brian Kulis & Kristen Grauman
    In Proc. 12th International Conference on Computer Vision (ICCV), 2009.
    [pdf] [webpage and code]

  • Convex Perturbations for Scalable Semidefinite Programming
    Brian Kulis, Suvrit Sra, & Inderjit Dhillon
    In Proc. 12th Intl. AISTATS Conference, 2009.
    [pdf]

  • Online Metric Learning and Fast Similarity Search
    Prateek Jain, Brian Kulis, Inderjit Dhillon, & Kristen Grauman
    In Neural Information Processing Systems (NIPS), 2008.
    Oral Presentation: 2.7% Acceptance Rate
    [pdf], Longer version: [pdf]

  • Fast Image Search for Learned Metrics
    Prateek Jain, Brian Kulis, & Kristen Grauman
    In. Proc. IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2008.
    CVPR 2008 Best Student Paper Award
    [pdf]

  • Information-Theoretic Metric Learning
    Jason Davis, Brian Kulis, Prateek Jain, Suvrit Sra, & Inderjit Dhillon
    In Proc. 24th International Conference on Machine Learning (ICML), 2007.
    ICML 2007 Best Student Paper Award
    [pdf] [code]

  • Fast Low-Rank Semidefinite Programming for Embedding and Clustering
    Brian Kulis, Arun Surendran, & John Platt
    In Proc. 11th Intl. AISTATS Conference, 2007.
    [pdf]

  • Learning Low-Rank Kernel Matrices
    Brian Kulis, Matyas Sustik, & Inderjit Dhillon
    In Proc. 23rd International Conference on Machine Learning (ICML), 2006.
    [pdf]

  • A Fast Kernel-Based Multilevel Algorithm for Graph Clustering
    Inderjit Dhillon, Yuqiang Guan, & Brian Kulis
    In Proc. 11th ACM SIGKDD Intl. Conference on Knowledge Discovery and Data Mining, 2005.
    [pdf] [code]

  • Semi-Supervised Graph Clustering: A Kernel Approach
    Brian Kulis, Sugato Basu, Inderjit Dhillon, & Raymond Mooney
    In Proc. 22nd International Conference on Machine Learning (ICML), 2005.
    ICML 2005 Best Student Paper Award
    [pdf]

  • Kernel k-means, Spectral Clustering, and Normalized Cuts
    Inderjit Dhillon, Yuqiang Guan, & Brian Kulis
    In Proc. 10th ACM SIGKDD Intl. Conf. on Knowledge Discovery and Data Mining, 2004.
    [pdf]

  • Natural Communities in Large Linked Networks
    John Hopcroft, Omar Khan, Brian Kulis, & Bart Selman
    In Proc. 9th ACM SIGKDD Intl. Conf. on Knowledge Discovery and Data Mining, 2003.
    [pdf]

Workshop Papers and Technical Reports

  • Learning to Hash with Binary Reconstructive Embeddings
    Brian Kulis & Trevor Darrell
    UC Berkeley EECS Techical Report #UCB/EECS-2009-101, July, 2009.
    [pdf]

  • Fast Similarity Search for Learned Metrics
    Prateek Jain, Brian Kulis, & Kristen Grauman
    UTCS Techical Report #TR-07-48, September 2007.
    [pdf]

  • Scalable Semidefinite Programming using Convex Perturbations
    Brian Kulis, Suvrit Sra, Stefanie Jegelka, & Inderjit Dhillon
    UTCS Technical Report #TR-07-47, September 2007.
    [pdf]

  • Online Linear Regression using Burg Entropy
    Prateek Jain, Brian Kulis, & Inderjit Dhillon
    UTCS Technical Report #TR-07-08, February 2007.
    [pdf]

  • Information-Theoretic Metric Learning
    Jason Davis, Brian Kulis, Suvrit Sra, & Inderjit Dhillon
    In NIPS 2006 Workshop on Learning to Compare Examples, 2006.
    [pdf]

  • A Unified View of Kernel k-means, Spectral Clustering and Graph Cuts
    Inderjit Dhillon, Yuqiang Guan, & Brian Kulis
    UTCS Technical Report #TR-04-25, July 2004.
    [pdf]