Sanjoy Dasgupta

According to our database1, Sanjoy Dasgupta authored at least 86 papers between 1997 and 2020.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of two.

Timeline

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Bibliography

2020
Reply to Semelidou and Skoulakis: "Short-term" habituation has multiple distinct mechanisms.
Proc. Natl. Acad. Sci. USA, 2020

Habituation as a neural algorithm for online odor discrimination.
Proc. Natl. Acad. Sci. USA, 2020

Theoretical Foundations of Hyperdimensional Computing.
CoRR, 2020

Expressivity of expand-and-sparsify representations.
CoRR, 2020

A Non-Parametric Test to Detect Data-Copying in Generative Models.
CoRR, 2020

Explainable k-Means and k-Medians Clustering.
Proceedings of the 37th International Conference on Machine Learning, 2020

What relations are reliably embeddable in Euclidean space?
Proceedings of the Algorithmic Learning Theory, 2020

A Three Sample Hypothesis Test for Evaluating Generative Models.
Proceedings of the 23rd International Conference on Artificial Intelligence and Statistics, 2020

Robust Learning from Discriminative Feature Feedback.
Proceedings of the 23rd International Conference on Artificial Intelligence and Statistics, 2020

Nearest Neighbor Classification and Search.
Proceedings of the Beyond the Worst-Case Analysis of Algorithms, 2020

2019
Interactive Topic Modeling with Anchor Words.
CoRR, 2019

An adaptive nearest neighbor rule for classification.
Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

Teaching a black-box learner.
Proceedings of the 36th International Conference on Machine Learning, 2019

A Geometric Data Structure from Neuroscience (Invited Talk).
Proceedings of the 35th International Symposium on Computational Geometry, 2019

The Relative Complexity of Maximum Likelihood Estimation, MAP Estimation, and Sampling.
Proceedings of the Conference on Learning Theory, 2019

2018
Early Classification of Time Series by Simultaneously Optimizing the Accuracy and Earliness.
IEEE Trans. Neural Networks Learn. Syst., 2018

A neural data structure for novelty detection.
Proc. Natl. Acad. Sci. USA, 2018

Structural query-by-committee.
CoRR, 2018

Interactive Structure Learning with Structural Query-by-Committee.
Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018

Learning from discriminative feature feedback.
Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018

Comparison Based Learning from Weak Oracles.
Proceedings of the International Conference on Artificial Intelligence and Statistics, 2018

2017
Active Learning Theory.
Proceedings of the Encyclopedia of Machine Learning and Data Mining, 2017

Maximum Likelihood Estimation for Mixtures of Spherical Gaussians is NP-hard.
J. Mach. Learn. Res., 2017

Learning from partial correction.
CoRR, 2017

Diameter-Based Active Learning.
Proceedings of the 34th International Conference on Machine Learning, 2017

Learning with Feature Feedback: from Theory to Practice.
Proceedings of the 20th International Conference on Artificial Intelligence and Statistics, 2017

2016
A cost function for similarity-based hierarchical clustering.
Proceedings of the 48th Annual ACM SIGACT Symposium on Theory of Computing, 2016

An algorithm for L1 nearest neighbor search via monotonic embedding.
Proceedings of the Advances in Neural Information Processing Systems 29: Annual Conference on Neural Information Processing Systems 2016, 2016

Interactive Bayesian Hierarchical Clustering.
Proceedings of the 33nd International Conference on Machine Learning, 2016

2015
Randomized Partition Trees for Nearest Neighbor Search.
Algorithmica, 2015

2014
Consistent Procedures for Cluster Tree Estimation and Pruning.
IEEE Trans. Inf. Theory, 2014

Optimal rates for k-NN density and mode estimation.
Proceedings of the Advances in Neural Information Processing Systems 27: Annual Conference on Neural Information Processing Systems 2014, 2014

Rates of Convergence for Nearest Neighbor Classification.
Proceedings of the Advances in Neural Information Processing Systems 27: Annual Conference on Neural Information Processing Systems 2014, 2014

Incremental Clustering: The Case for Extra Clusters.
Proceedings of the Advances in Neural Information Processing Systems 27: Annual Conference on Neural Information Processing Systems 2014, 2014

Lower Bounds for the Gibbs Sampler over Mixtures of Gaussians.
Proceedings of the 31th International Conference on Machine Learning, 2014

2013
Moment-based Uniform Deviation Bounds for $k$-means and Friends.
CoRR, 2013

Moment-based Uniform Deviation Bounds for <i>k</i>-means and Friends.
Proceedings of the Advances in Neural Information Processing Systems 26: 27th Annual Conference on Neural Information Processing Systems 2013. Proceedings of a meeting held December 5-8, 2013

The Fast Convergence of Incremental PCA.
Proceedings of the Advances in Neural Information Processing Systems 26: 27th Annual Conference on Neural Information Processing Systems 2013. Proceedings of a meeting held December 5-8, 2013

DELPHI: Data E-platform for personalized population health.
Proceedings of the IEEE 15th International Conference on e-Health Networking, 2013

Randomized partition trees for exact nearest neighbor search.
Proceedings of the COLT 2013, 2013

2012
Consistency of Nearest Neighbor Classification under Selective Sampling.
Proceedings of the COLT 2012, 2012

A tree-based regressor that adapts to intrinsic dimension.
J. Comput. Syst. Sci., 2012

CitiSense: improving geospatial environmental assessment of air quality using a wireless personal exposure monitoring system.
Proceedings of the Wireless Health 2012, 2012

Agglomerative Bregman Clustering.
Proceedings of the 29th International Conference on Machine Learning, 2012

2011
Two faces of active learning.
Theor. Comput. Sci., 2011

Recent advances in active learning.
Proceedings of the 2011 Symposium on Machine Learning in Speech and Language Processing, 2011

2010
Active Learning Theory.
Proceedings of the Encyclopedia of Machine Learning, 2010

Strange effects in high dimension.
Commun. ACM, 2010

Rates of convergence for the cluster tree.
Proceedings of the Advances in Neural Information Processing Systems 23: 24th Annual Conference on Neural Information Processing Systems 2010. Proceedings of a meeting held 6-9 December 2010, 2010

2009
Random projection trees for vector quantization.
IEEE Trans. Inf. Theory, 2009

Analysis of Perceptron-Based Active Learning.
J. Mach. Learn. Res., 2009

Learning Mixtures of Gaussians using the k-means Algorithm
CoRR, 2009

Which Spatial Partition Trees are Adaptive to Intrinsic Dimension?
Proceedings of the UAI 2009, 2009

Tutorial summary: Active learning.
Proceedings of the 26th Annual International Conference on Machine Learning, 2009

Importance weighted active learning.
Proceedings of the 26th Annual International Conference on Machine Learning, 2009

2008
Special issue on learning theory.
J. Comput. Syst. Sci., 2008

Random projection trees and low dimensional manifolds.
Proceedings of the 40th Annual ACM Symposium on Theory of Computing, 2008

Hierarchical sampling for active learning.
Proceedings of the Machine Learning, 2008

Algorithms.
McGraw-Hill, ISBN: 978-0-07-352340-8, 2008

2007
A Probabilistic Analysis of EM for Mixtures of Separated, Spherical Gaussians.
J. Mach. Learn. Res., 2007

Learning the structure of manifolds using random projections.
Proceedings of the Advances in Neural Information Processing Systems 20, 2007

A general agnostic active learning algorithm.
Proceedings of the Advances in Neural Information Processing Systems 20, 2007

A learning framework for nearest neighbor search.
Proceedings of the Advances in Neural Information Processing Systems 20, 2007

On-Line Estimation with the Multivariate Gaussian Distribution.
Proceedings of the Learning Theory, 20th Annual Conference on Learning Theory, 2007

2006
A Concentration Theorem for Projections.
Proceedings of the UAI '06, 2006

Robust Euclidean embedding.
Proceedings of the Machine Learning, 2006

2005
The Complexity of Approximating the Entropy.
SIAM J. Comput., 2005

Performance guarantees for hierarchical clustering.
J. Comput. Syst. Sci., 2005

Coarse sample complexity bounds for active learning.
Proceedings of the Advances in Neural Information Processing Systems 18 [Neural Information Processing Systems, 2005

2004
Analysis of a greedy active learning strategy.
Proceedings of the Advances in Neural Information Processing Systems 17 [Neural Information Processing Systems, 2004

2003
An elementary proof of a theorem of Johnson and Lindenstrauss.
Random Struct. Algorithms, 2003

A Theoretical Analysis of Query Selection for Collaborative Filtering.
Mach. Learn., 2003

An Iterative Improvement Procedure for Hierarchical Clustering.
Proceedings of the Advances in Neural Information Processing Systems 16 [Neural Information Processing Systems, 2003

Boosting with Diverse Base Classifiers.
Proceedings of the Computational Learning Theory and Kernel Machines, 2003

How Fast Is <i>k</i>-Means?
Proceedings of the Computational Learning Theory and Kernel Machines, 2003

Subspace Detection: A Robust Statistics Formulation.
Proceedings of the Computational Learning Theory and Kernel Machines, 2003

2002
Performance Guarantees for Hierarchical Clustering.
Proceedings of the Computational Learning Theory, 2002

An Efficient PAC Algorithm for Reconstructing a Mixture of Lines.
Proceedings of the Algorithmic Learning Theory, 13th International Conference, 2002

2001
PAC Generalization Bounds for Co-training.
Proceedings of the Advances in Neural Information Processing Systems 14 [Neural Information Processing Systems: Natural and Synthetic, 2001

A Generalization of Principal Components Analysis to the Exponential Family.
Proceedings of the Advances in Neural Information Processing Systems 14 [Neural Information Processing Systems: Natural and Synthetic, 2001

Off-Policy Temporal Difference Learning with Function Approximation.
Proceedings of the Eighteenth International Conference on Machine Learning (ICML 2001), Williams College, Williamstown, MA, USA, June 28, 2001

2000
A Two-Round Variant of EM for Gaussian Mixtures.
Proceedings of the UAI '00: Proceedings of the 16th Conference in Uncertainty in Artificial Intelligence, Stanford University, Stanford, California, USA, June 30, 2000

Experiments with Random Projection.
Proceedings of the UAI '00: Proceedings of the 16th Conference in Uncertainty in Artificial Intelligence, Stanford University, Stanford, California, USA, June 30, 2000

1999
Learning Polytrees.
Proceedings of the UAI '99: Proceedings of the Fifteenth Conference on Uncertainty in Artificial Intelligence, Stockholm, Sweden, July 30, 1999

Learning Mixtures of Gaussians.
Proceedings of the 40th Annual Symposium on Foundations of Computer Science, 1999

1997
The Sample Complexity of Learning Fixed-Structure Bayesian Networks.
Mach. Learn., 1997


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