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Sanjoy Dasgupta: [Publications] [Author Rank by year] [Co-authors] [Prefers] [Cites] [Cited by]

Publications of Author

  1. Sanjoy Dasgupta, Elan Pavlov, Yoram Singer
    An Efficient PAC Algorithm for Reconstructing a Mixture of Lines. [Citation Graph (0, 0)][DBLP]
    ALT, 2002, pp:351-364 [Conf]
  2. Tugkan Batu, Sanjoy Dasgupta, Ravi Kumar, Ronitt Rubinfeld
    The Complexity of Approximating the Entropy. [Citation Graph (0, 0)][DBLP]
    IEEE Conference on Computational Complexity, 2002, pp:17- [Conf]
  3. Sanjoy Dasgupta
    Performance Guarantees for Hierarchical Clustering. [Citation Graph (0, 0)][DBLP]
    COLT, 2002, pp:351-363 [Conf]
  4. Sanjoy Dasgupta
    Subspace Detection: A Robust Statistics Formulation. [Citation Graph (0, 0)][DBLP]
    COLT, 2003, pp:734- [Conf]
  5. Sanjoy Dasgupta
    How Fast Is k-Means? [Citation Graph (0, 0)][DBLP]
    COLT, 2003, pp:735- [Conf]
  6. Sanjoy Dasgupta, Adam Tauman Kalai, Claire Monteleoni
    Analysis of Perceptron-Based Active Learning. [Citation Graph (0, 0)][DBLP]
    COLT, 2005, pp:249-263 [Conf]
  7. Sanjoy Dasgupta, Philip M. Long
    Boosting with Diverse Base Classifiers. [Citation Graph (0, 0)][DBLP]
    COLT, 2003, pp:273-287 [Conf]
  8. Sanjoy Dasgupta
    Learning Mixtures of Gaussians. [Citation Graph (0, 0)][DBLP]
    FOCS, 1999, pp:634-644 [Conf]
  9. Lawrence Cayton, Sanjoy Dasgupta
    Robust Euclidean embedding. [Citation Graph (0, 0)][DBLP]
    ICML, 2006, pp:169-176 [Conf]
  10. Doina Precup, Richard S. Sutton, Sanjoy Dasgupta
    Off-Policy Temporal Difference Learning with Function Approximation. [Citation Graph (0, 0)][DBLP]
    ICML, 2001, pp:417-424 [Conf]
  11. Sanjoy Dasgupta
    Analysis of a greedy active learning strategy. [Citation Graph (0, 0)][DBLP]
    NIPS, 2004, pp:- [Conf]
  12. Sanjoy Dasgupta
    Coarse sample complexity bounds for active learning. [Citation Graph (0, 0)][DBLP]
    NIPS, 2005, pp:- [Conf]
  13. Sanjoy Dasgupta, Michael L. Littman, David A. McAllester
    PAC Generalization Bounds for Co-training. [Citation Graph (0, 0)][DBLP]
    NIPS, 2001, pp:375-382 [Conf]
  14. David Kauchak, Sanjoy Dasgupta
    An Iterative Improvement Procedure for Hierarchical Clustering. [Citation Graph (0, 0)][DBLP]
    NIPS, 2003, pp:- [Conf]
  15. Tugkan Batu, Sanjoy Dasgupta, Ravi Kumar, Ronitt Rubinfeld
    The complexity of approximating entropy. [Citation Graph (0, 0)][DBLP]
    STOC, 2002, pp:678-687 [Conf]
  16. Sanjoy Dasgupta
    Experiments with Random Projection. [Citation Graph (0, 0)][DBLP]
    UAI, 2000, pp:143-151 [Conf]
  17. Sanjoy Dasgupta
    Learning Polytrees. [Citation Graph (0, 0)][DBLP]
    UAI, 1999, pp:134-141 [Conf]
  18. Sanjoy Dasgupta, Leonard J. Schulman
    A Two-Round Variant of EM for Gaussian Mixtures. [Citation Graph (0, 0)][DBLP]
    UAI, 2000, pp:152-159 [Conf]
  19. Sanjoy Dasgupta, Philip M. Long
    Performance guarantees for hierarchical clustering. [Citation Graph (0, 0)][DBLP]
    J. Comput. Syst. Sci., 2005, v:70, n:4, pp:555-569 [Journal]
  20. Sanjoy Dasgupta, Leonard J. Schulman
    A Probabilistic Analysis of EM for Mixtures of Separated, Spherical Gaussians. [Citation Graph (0, 0)][DBLP]
    Journal of Machine Learning Research, 2007, v:8, n:, pp:203-226 [Journal]
  21. Sanjoy Dasgupta
    The Sample Complexity of Learning Fixed-Structure Bayesian Networks. [Citation Graph (0, 0)][DBLP]
    Machine Learning, 1997, v:29, n:2-3, pp:165-180 [Journal]
  22. Sanjoy Dasgupta, Wee Sun Lee, Philip M. Long
    A Theoretical Analysis of Query Selection for Collaborative Filtering. [Citation Graph (0, 0)][DBLP]
    Machine Learning, 2003, v:51, n:3, pp:283-298 [Journal]
  23. Sanjoy Dasgupta, Anupam Gupta
    An elementary proof of a theorem of Johnson and Lindenstrauss. [Citation Graph (0, 0)][DBLP]
    Random Struct. Algorithms, 2003, v:22, n:1, pp:60-65 [Journal]
  24. Tugkan Batu, Sanjoy Dasgupta, Ravi Kumar, Ronitt Rubinfeld
    The Complexity of Approximating the Entropy. [Citation Graph (0, 0)][DBLP]
    SIAM J. Comput., 2005, v:35, n:1, pp:132-150 [Journal]
  25. Sanjoy Dasgupta, Daniel Hsu
    On-Line Estimation with the Multivariate Gaussian Distribution. [Citation Graph (0, 0)][DBLP]
    COLT, 2007, pp:278-292 [Conf]
  26. Sanjoy Dasgupta, Daniel Hsu, Nakul Verma
    A Concentration Theorem for Projections. [Citation Graph (0, 0)][DBLP]
    UAI, 2006, pp:- [Conf]

  27. The Two Faces of Active Learning. [Citation Graph (, )][DBLP]


  28. The Two Faces of Active Learning. [Citation Graph (, )][DBLP]


  29. Hierarchical sampling for active learning. [Citation Graph (, )][DBLP]


  30. Tutorial summary: Active learning. [Citation Graph (, )][DBLP]


  31. Importance weighted active learning. [Citation Graph (, )][DBLP]


  32. A general agnostic active learning algorithm. [Citation Graph (, )][DBLP]


  33. A learning framework for nearest neighbor search. [Citation Graph (, )][DBLP]


  34. Learning the structure of manifolds using random projections. [Citation Graph (, )][DBLP]


  35. Random projection trees and low dimensional manifolds. [Citation Graph (, )][DBLP]


  36. Strange effects in high dimension. [Citation Graph (, )][DBLP]


  37. Importance Weighted Active Learning [Citation Graph (, )][DBLP]


  38. Learning Mixtures of Gaussians using the k-means Algorithm [Citation Graph (, )][DBLP]


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