2008 |
33 | EE | Sanjoy Dasgupta,
Daniel Hsu:
Hierarchical sampling for active learning.
ICML 2008: 208-215 |
32 | EE | Sanjoy Dasgupta,
Yoav Freund:
Random projection trees and low dimensional manifolds.
STOC 2008: 537-546 |
31 | EE | Alina Beygelzimer,
Sanjoy Dasgupta,
John Langford:
Importance Weighted Active Learning
CoRR abs/0812.4952: (2008) |
30 | EE | Sanjoy Dasgupta:
Special issue on learning theory.
J. Comput. Syst. Sci. 74(1): 1 (2008) |
2007 |
29 | EE | Sanjoy Dasgupta,
Daniel Hsu:
On-Line Estimation with the Multivariate Gaussian Distribution.
COLT 2007: 278-292 |
28 | EE | Sanjoy Dasgupta,
Daniel Hsu,
Claire Monteleoni:
A general agnostic active learning algorithm.
NIPS 2007 |
27 | EE | Lawrence Cayton,
Sanjoy Dasgupta:
A learning framework for nearest neighbor search.
NIPS 2007 |
26 | EE | Yoav Freund,
Sanjoy Dasgupta,
Mayank Kabra,
Nakul Verma:
Learning the structure of manifolds using random projections.
NIPS 2007 |
25 | EE | Sanjoy Dasgupta,
Leonard J. Schulman:
A Probabilistic Analysis of EM for Mixtures of Separated, Spherical Gaussians.
Journal of Machine Learning Research 8: 203-226 (2007) |
2006 |
24 | EE | Lawrence Cayton,
Sanjoy Dasgupta:
Robust Euclidean embedding.
ICML 2006: 169-176 |
23 | EE | Sanjoy Dasgupta,
Daniel Hsu,
Nakul Verma:
A Concentration Theorem for Projections.
UAI 2006 |
2005 |
22 | EE | Sanjoy Dasgupta,
Adam Tauman Kalai,
Claire Monteleoni:
Analysis of Perceptron-Based Active Learning.
COLT 2005: 249-263 |
21 | EE | Sanjoy Dasgupta:
Coarse sample complexity bounds for active learning.
NIPS 2005 |
20 | EE | Sanjoy Dasgupta,
Philip M. Long:
Performance guarantees for hierarchical clustering.
J. Comput. Syst. Sci. 70(4): 555-569 (2005) |
19 | EE | Tugkan Batu,
Sanjoy Dasgupta,
Ravi Kumar,
Ronitt Rubinfeld:
The Complexity of Approximating the Entropy.
SIAM J. Comput. 35(1): 132-150 (2005) |
2004 |
18 | EE | Sanjoy Dasgupta:
Analysis of a greedy active learning strategy.
NIPS 2004 |
2003 |
17 | EE | Sanjoy Dasgupta,
Philip M. Long:
Boosting with Diverse Base Classifiers.
COLT 2003: 273-287 |
16 | EE | Sanjoy Dasgupta:
Subspace Detection: A Robust Statistics Formulation.
COLT 2003: 734 |
15 | EE | Sanjoy Dasgupta:
How Fast Is k-Means?
COLT 2003: 735 |
14 | EE | David Kauchak,
Sanjoy Dasgupta:
An Iterative Improvement Procedure for Hierarchical Clustering.
NIPS 2003 |
13 | EE | Sanjoy Dasgupta,
Wee Sun Lee,
Philip M. Long:
A Theoretical Analysis of Query Selection for Collaborative Filtering.
Machine Learning 51(3): 283-298 (2003) |
12 | EE | Sanjoy Dasgupta,
Anupam Gupta:
An elementary proof of a theorem of Johnson and Lindenstrauss.
Random Struct. Algorithms 22(1): 60-65 (2003) |
2002 |
11 | EE | Sanjoy Dasgupta,
Elan Pavlov,
Yoram Singer:
An Efficient PAC Algorithm for Reconstructing a Mixture of Lines.
ALT 2002: 351-364 |
10 | EE | Sanjoy Dasgupta:
Performance Guarantees for Hierarchical Clustering.
COLT 2002: 351-363 |
9 | EE | Tugkan Batu,
Sanjoy Dasgupta,
Ravi Kumar,
Ronitt Rubinfeld:
The Complexity of Approximating the Entropy.
IEEE Conference on Computational Complexity 2002: 17 |
8 | EE | Tugkan Batu,
Sanjoy Dasgupta,
Ravi Kumar,
Ronitt Rubinfeld:
The complexity of approximating entropy.
STOC 2002: 678-687 |
2001 |
7 | | Doina Precup,
Richard S. Sutton,
Sanjoy Dasgupta:
Off-Policy Temporal Difference Learning with Function Approximation.
ICML 2001: 417-424 |
6 | EE | Sanjoy Dasgupta,
Michael L. Littman,
David A. McAllester:
PAC Generalization Bounds for Co-training.
NIPS 2001: 375-382 |
2000 |
5 | EE | Sanjoy Dasgupta:
Experiments with Random Projection.
UAI 2000: 143-151 |
4 | EE | Sanjoy Dasgupta,
Leonard J. Schulman:
A Two-Round Variant of EM for Gaussian Mixtures.
UAI 2000: 152-159 |
1999 |
3 | EE | Sanjoy Dasgupta:
Learning Mixtures of Gaussians.
FOCS 1999: 634-644 |
2 | EE | Sanjoy Dasgupta:
Learning Polytrees.
UAI 1999: 134-141 |
1997 |
1 | | Sanjoy Dasgupta:
The Sample Complexity of Learning Fixed-Structure Bayesian Networks.
Machine Learning 29(2-3): 165-180 (1997) |