Sanjoy Dasgupta

According to our database, Sanjoy Dasgupta authored at least 99 papers between 1997 and 2023.

Collaborative distances:

• Dijkstra number of three.
• Erdős number of two.

2023

Reducing Catastrophic Forgetting With Associative Learning: A Lesson From Fruit Flies.

Yang Shen, Sanjoy Dasgupta, Saket Navlakha

Neural Comput., November, 2023

Rethinking Logic Minimization for Tabular Machine Learning.

Litao Qiao, Weijia Wang, Sanjoy Dasgupta, Bill Lin

IEEE Trans. Artif. Intell., October, 2023

Online nearest neighbor classification.

Sanjoy Dasgupta, Geelon So

CoRR, 2023

Active learning using region-based sampling.

Sanjoy Dasgupta, Yoav Freund

CoRR, 2023

Data-Copying in Generative Models: A Formal Framework.

Robi Bhattacharjee, Sanjoy Dasgupta, Kamalika Chaudhuri

Proceedings of the International Conference on Machine Learning, 2023

Online k-means Clustering on Arbitrary Data Streams.

Robi Bhattacharjee, Jacob Imola, Michal Moshkovitz, Sanjoy Dasgupta

Proceedings of the International Conference on Algorithmic Learning Theory, 2023

2022

Streaming Encoding Algorithms for Scalable Hyperdimensional Computing.

Anthony Thomas, Behnam Khaleghi, Gopi Krishna Jha, Sanjoy Dasgupta, Nageen Himayat, Ravi Iyer, Nilesh Jain, Tajana Rosing

CoRR, 2022

A Theoretical Perspective on Hyperdimensional Computing (Extended Abstract).

Anthony Thomas, Sanjoy Dasgupta, Tajana Rosing

Proceedings of the Thirty-First International Joint Conference on Artificial Intelligence, 2022

Constants Matter: The Performance Gains of Active Learning.

Stephen O. Mussmann, Sanjoy Dasgupta

Proceedings of the International Conference on Machine Learning, 2022

Framework for Evaluating Faithfulness of Local Explanations.

Sanjoy Dasgupta, Nave Frost, Michal Moshkovitz

Proceedings of the International Conference on Machine Learning, 2022

Convergence of online k-means.

Geelon So, Gaurav Mahajan, Sanjoy Dasgupta

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2022

2021

A Theoretical Perspective on Hyperdimensional Computing.

Anthony Thomas, Sanjoy Dasgupta, Tajana Rosing

J. Artif. Intell. Res., 2021

Algorithmic insights on continual learning from fruit flies.

Yang Shen, Sanjoy Dasgupta, Saket Navlakha

CoRR, 2021

2020

Reply to Semelidou and Skoulakis: "Short-term" habituation has multiple distinct mechanisms.

Yang Shen, Sanjoy Dasgupta, Saket Navlakha

Proc. Natl. Acad. Sci. USA, 2020

Habituation as a neural algorithm for online odor discrimination.

Yang Shen, Sanjoy Dasgupta, Saket Navlakha

Proc. Natl. Acad. Sci. USA, 2020

Theoretical Foundations of Hyperdimensional Computing.

Anthony Thomas, Sanjoy Dasgupta, Tajana Rosing

CoRR, 2020

Expressivity of expand-and-sparsify representations.

Sanjoy Dasgupta, Christopher Tosh

CoRR, 2020

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

Casey Meehan, Kamalika Chaudhuri, Sanjoy Dasgupta

CoRR, 2020

Explainable k-Means and k-Medians Clustering.

Michal Moshkovitz, Sanjoy Dasgupta, Cyrus Rashtchian, Nave Frost

Proceedings of the 37th International Conference on Machine Learning, 2020

What relations are reliably embeddable in Euclidean space?

Robi Bhattacharjee, Sanjoy Dasgupta

Proceedings of the Algorithmic Learning Theory, 2020

A Three Sample Hypothesis Test for Evaluating Generative Models.

Casey Meehan, Kamalika Chaudhuri, Sanjoy Dasgupta

Proceedings of the 23rd International Conference on Artificial Intelligence and Statistics, 2020

Robust Learning from Discriminative Feature Feedback.

Sanjoy Dasgupta, Sivan Sabato

Proceedings of the 23rd International Conference on Artificial Intelligence and Statistics, 2020

Nearest Neighbor Classification and Search.

Sanjoy Dasgupta, Samory Kpotufe

Proceedings of the Beyond the Worst-Case Analysis of Algorithms, 2020

2019

Interactive Topic Modeling with Anchor Words.

Sanjoy Dasgupta, Stefanos Poulis, Christopher Tosh

CoRR, 2019

An adaptive nearest neighbor rule for classification.

Akshay Balsubramani, Sanjoy Dasgupta, Yoav Freund, Shay Moran

Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

Teaching a black-box learner.

Sanjoy Dasgupta, Daniel Hsu, Stefanos Poulis, Xiaojin Zhu

Proceedings of the 36th International Conference on Machine Learning, 2019

A Geometric Data Structure from Neuroscience (Invited Talk).

Sanjoy Dasgupta

Proceedings of the 35th International Symposium on Computational Geometry, 2019

The Relative Complexity of Maximum Likelihood Estimation, MAP Estimation, and Sampling.

Christopher Tosh, Sanjoy Dasgupta

Proceedings of the Conference on Learning Theory, 2019

2018

Early Classification of Time Series by Simultaneously Optimizing the Accuracy and Earliness.

Usue Mori, Alexander Mendiburu, Sanjoy Dasgupta, José Antonio Lozano

IEEE Trans. Neural Networks Learn. Syst., 2018

A neural data structure for novelty detection.

Sanjoy Dasgupta, Timothy Sheehan, Charles F. Stevens, Saket Navlakha

Proc. Natl. Acad. Sci. USA, 2018

Structural query-by-committee.

Christopher Tosh, Sanjoy Dasgupta

CoRR, 2018

Interactive Structure Learning with Structural Query-by-Committee.

Christopher Tosh, Sanjoy Dasgupta

Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018

Learning from discriminative feature feedback.

Sanjoy Dasgupta, Akansha Dey, Nicholas Roberts, Sivan Sabato

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.

Ehsan Kazemi, Lin Chen, Sanjoy Dasgupta, Amin Karbasi

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2018

2017

Active Learning Theory.

Sanjoy Dasgupta

Proceedings of the Encyclopedia of Machine Learning and Data Mining, 2017

Maximum Likelihood Estimation for Mixtures of Spherical Gaussians is NP-hard.

Christopher Tosh, Sanjoy Dasgupta

J. Mach. Learn. Res., 2017

Learning from partial correction.

Sanjoy Dasgupta, Michael Luby

CoRR, 2017

Diameter-Based Active Learning.

Christopher Tosh, Sanjoy Dasgupta

Proceedings of the 34th International Conference on Machine Learning, 2017

Learning with Feature Feedback: from Theory to Practice.

Stefanos Poulis, Sanjoy Dasgupta

Proceedings of the 20th International Conference on Artificial Intelligence and Statistics, 2017

2016

A cost function for similarity-based hierarchical clustering.

Sanjoy Dasgupta

Proceedings of the 48th Annual ACM SIGACT Symposium on Theory of Computing, 2016

An algorithm for L1 nearest neighbor search via monotonic embedding.

Xinan Wang, Sanjoy Dasgupta

Proceedings of the Advances in Neural Information Processing Systems 29: Annual Conference on Neural Information Processing Systems 2016, 2016

Interactive Bayesian Hierarchical Clustering.

Sharad Vikram, Sanjoy Dasgupta

Proceedings of the 33nd International Conference on Machine Learning, 2016

2015

Randomized Partition Trees for Nearest Neighbor Search.

Sanjoy Dasgupta, Kaushik Sinha

Algorithmica, 2015

2014

Consistent Procedures for Cluster Tree Estimation and Pruning.

Kamalika Chaudhuri, Sanjoy Dasgupta, Samory Kpotufe, Ulrike von Luxburg

IEEE Trans. Inf. Theory, 2014

Optimal rates for k-NN density and mode estimation.

Sanjoy Dasgupta, Samory Kpotufe

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.

Kamalika Chaudhuri, Sanjoy Dasgupta

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.

Margareta Ackerman, Sanjoy Dasgupta

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.

Christopher Tosh, Sanjoy Dasgupta

Proceedings of the 31th International Conference on Machine Learning, 2014

2013

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

Matus Telgarsky, Sanjoy Dasgupta

CoRR, 2013

Moment-based Uniform Deviation Bounds for <i>k</i>-means and Friends.

Matus Telgarsky, Sanjoy Dasgupta

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.

Akshay Balsubramani, Sanjoy Dasgupta, Yoav Freund

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.

Yannis Katsis, Chaitanya K. Baru, Ted Chan, Sanjoy Dasgupta, Claudiu Farcas, William G. Griswold, Jeannie Huang, Lucila Ohno-Machado, Yannis Papakonstantinou, Fredric Raab, Kevin Patrick

Proceedings of the IEEE 15th International Conference on e-Health Networking, 2013

Randomized partition trees for exact nearest neighbor search.

Sanjoy Dasgupta, Kaushik Sinha

Proceedings of the COLT 2013, 2013

2012

Consistency of Nearest Neighbor Classification under Selective Sampling.

Sanjoy Dasgupta

Proceedings of the COLT 2012, 2012

A tree-based regressor that adapts to intrinsic dimension.

Samory Kpotufe, Sanjoy Dasgupta

J. Comput. Syst. Sci., 2012

CitiSense: improving geospatial environmental assessment of air quality using a wireless personal exposure monitoring system.

Nima Nikzad, Nakul Verma, Celal Ziftci, Elizabeth S. Bales, Nichole Quick, Piero Zappi, Kevin Patrick, Sanjoy Dasgupta, Ingolf Krueger, Tajana Simunic Rosing, William G. Griswold

Proceedings of the Wireless Health 2012, 2012

Agglomerative Bregman Clustering.

Matus Telgarsky, Sanjoy Dasgupta

Proceedings of the 29th International Conference on Machine Learning, 2012

2011

Two faces of active learning.

Sanjoy Dasgupta

Theor. Comput. Sci., 2011

Recent advances in active learning.

Sanjoy Dasgupta

Proceedings of the 2011 Symposium on Machine Learning in Speech and Language Processing, 2011

2010

Active Learning Theory.

Sanjoy Dasgupta

Proceedings of the Encyclopedia of Machine Learning, 2010

Strange effects in high dimension.

Sanjoy Dasgupta

Commun. ACM, 2010

Rates of convergence for the cluster tree.

Kamalika Chaudhuri, Sanjoy Dasgupta

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.

Sanjoy Dasgupta, Yoav Freund

IEEE Trans. Inf. Theory, 2009

Analysis of Perceptron-Based Active Learning.

Sanjoy Dasgupta, Adam Tauman Kalai, Claire Monteleoni

J. Mach. Learn. Res., 2009

Learning Mixtures of Gaussians using the k-means Algorithm

Kamalika Chaudhuri, Sanjoy Dasgupta, Andrea Vattani

CoRR, 2009

Which Spatial Partition Trees are Adaptive to Intrinsic Dimension?

Nakul Verma, Samory Kpotufe, Sanjoy Dasgupta

Proceedings of the UAI 2009, 2009

Tutorial summary: Active learning.

Sanjoy Dasgupta, John Langford

Proceedings of the 26th Annual International Conference on Machine Learning, 2009

Importance weighted active learning.

Alina Beygelzimer, Sanjoy Dasgupta, John Langford

Proceedings of the 26th Annual International Conference on Machine Learning, 2009

2008

Special issue on learning theory.

Sanjoy Dasgupta

J. Comput. Syst. Sci., 2008

Random projection trees and low dimensional manifolds.

Sanjoy Dasgupta, Yoav Freund

Proceedings of the 40th Annual ACM Symposium on Theory of Computing, 2008

Hierarchical sampling for active learning.

Sanjoy Dasgupta, Daniel J. Hsu

Proceedings of the Machine Learning, 2008

Algorithms.

Sanjoy Dasgupta, Christos H. Papadimitriou, Umesh V. Vazirani

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

2007

A Probabilistic Analysis of EM for Mixtures of Separated, Spherical Gaussians.

Sanjoy Dasgupta, Leonard J. Schulman

J. Mach. Learn. Res., 2007

Learning the structure of manifolds using random projections.

Yoav Freund, Sanjoy Dasgupta, Mayank Kabra, Nakul Verma

Proceedings of the Advances in Neural Information Processing Systems 20, 2007

A general agnostic active learning algorithm.

Sanjoy Dasgupta, Daniel J. Hsu, Claire Monteleoni

Proceedings of the Advances in Neural Information Processing Systems 20, 2007

A learning framework for nearest neighbor search.

Lawrence Cayton, Sanjoy Dasgupta

Proceedings of the Advances in Neural Information Processing Systems 20, 2007

On-Line Estimation with the Multivariate Gaussian Distribution.

Sanjoy Dasgupta, Daniel J. Hsu

Proceedings of the Learning Theory, 20th Annual Conference on Learning Theory, 2007

2006

A Concentration Theorem for Projections.

Sanjoy Dasgupta, Daniel J. Hsu, Nakul Verma

Proceedings of the UAI '06, 2006

Robust Euclidean embedding.

Lawrence Cayton, Sanjoy Dasgupta

Proceedings of the Machine Learning, 2006

2005

The Complexity of Approximating the Entropy.

Tugkan Batu, Sanjoy Dasgupta, Ravi Kumar, Ronitt Rubinfeld

SIAM J. Comput., 2005

Performance guarantees for hierarchical clustering.

Sanjoy Dasgupta, Philip M. Long

J. Comput. Syst. Sci., 2005

Coarse sample complexity bounds for active learning.

Sanjoy Dasgupta

Proceedings of the Advances in Neural Information Processing Systems 18 [Neural Information Processing Systems, 2005

2004

Analysis of a greedy active learning strategy.

Sanjoy Dasgupta

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.

Sanjoy Dasgupta, Anupam Gupta

Random Struct. Algorithms, 2003

A Theoretical Analysis of Query Selection for Collaborative Filtering.

Sanjoy Dasgupta, Wee Sun Lee, Philip M. Long

Mach. Learn., 2003

An Iterative Improvement Procedure for Hierarchical Clustering.

David Kauchak, Sanjoy Dasgupta

Proceedings of the Advances in Neural Information Processing Systems 16 [Neural Information Processing Systems, 2003

Boosting with Diverse Base Classifiers.

Sanjoy Dasgupta, Philip M. Long

Proceedings of the Computational Learning Theory and Kernel Machines, 2003

How Fast Is <i>k</i>-Means?

Sanjoy Dasgupta

Proceedings of the Computational Learning Theory and Kernel Machines, 2003

Subspace Detection: A Robust Statistics Formulation.

Sanjoy Dasgupta

Proceedings of the Computational Learning Theory and Kernel Machines, 2003

2002

Performance Guarantees for Hierarchical Clustering.

Sanjoy Dasgupta

Proceedings of the Computational Learning Theory, 2002

An Efficient PAC Algorithm for Reconstructing a Mixture of Lines.

Sanjoy Dasgupta, Elan Pavlov, Yoram Singer

Proceedings of the Algorithmic Learning Theory, 13th International Conference, 2002

2001

PAC Generalization Bounds for Co-training.

Sanjoy Dasgupta, Michael L. Littman, David A. McAllester

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.

Michael Collins, Sanjoy Dasgupta, Robert E. Schapire

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.

Doina Precup, Richard S. Sutton, Sanjoy Dasgupta

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.

Sanjoy Dasgupta, Leonard J. Schulman

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.

Sanjoy Dasgupta

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.

Sanjoy Dasgupta

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

Learning Mixtures of Gaussians.

Sanjoy Dasgupta

Proceedings of the 40th Annual Symposium on Foundations of Computer Science, 1999

1997

The Sample Complexity of Learning Fixed-Structure Bayesian Networks.

Sanjoy Dasgupta

Mach. Learn., 1997