The Sample Complexity of Learning Fixed-Structure Bayesian Networks. - Sanjoy Dasgupta (Mach. Learn., 1997)

Learning Mixtures of Gaussians. - Sanjoy Dasgupta (FOCS, 1999)

Learning Polytrees. - Sanjoy Dasgupta (UAI, 1999)

Experiments with Random Projection. - Sanjoy Dasgupta (UAI, 2000)

A Two-Round Variant of EM for Gaussian Mixtures. - Sanjoy Dasgupta; Leonard J. Schulman (UAI, 2000)

Off-Policy Temporal Difference Learning with Function Approximation. - Doina Precup; Richard S. Sutton; Sanjoy Dasgupta (ICML, 2001)

A Generalization of Principal Components Analysis to the Exponential Family. - Michael Collins 001; Sanjoy Dasgupta; Robert E. Schapire (NIPS, 2001)

PAC Generalization Bounds for Co-training. - Sanjoy Dasgupta; Michael L. Littman; David A. McAllester (NIPS, 2001)

An Efficient PAC Algorithm for Reconstructing a Mixture of Lines. - Sanjoy Dasgupta; Elan Pavlov; Yoram Singer (ALT, 2002)

Performance Guarantees for Hierarchical Clustering. - Sanjoy Dasgupta (COLT, 2002)

Subspace Detection: A Robust Statistics Formulation. - Sanjoy Dasgupta (COLT, 2003)

How Fast Is k-Means? - Sanjoy Dasgupta (COLT, 2003)

Boosting with Diverse Base Classifiers. - Sanjoy Dasgupta; Philip M. Long (COLT, 2003)

An Iterative Improvement Procedure for Hierarchical Clustering. - David Kauchak; Sanjoy Dasgupta (NIPS, 2003)

A Theoretical Analysis of Query Selection for Collaborative Filtering. - Sanjoy Dasgupta; Wee Sun Lee; Philip M. Long (Mach. Learn., 2003)

An elementary proof of a theorem of Johnson and Lindenstrauss. - Sanjoy Dasgupta; Anupam Gupta 001 (Random Struct. Algorithms, 2003)

Analysis of a greedy active learning strategy. - Sanjoy Dasgupta (NIPS, 2004)

Coarse sample complexity bounds for active learning. - Sanjoy Dasgupta (NIPS, 2005)

Performance guarantees for hierarchical clustering. - Sanjoy Dasgupta; Philip M. Long (J. Comput. Syst. Sci., 2005)

The Complexity of Approximating the Entropy. - Tugkan Batu; Sanjoy Dasgupta; Ravi Kumar 001; Ronitt Rubinfeld (SIAM J. Comput., 2005)

Robust Euclidean embedding. - Lawrence Cayton; Sanjoy Dasgupta (ICML, 2006)

A Concentration Theorem for Projections. - Sanjoy Dasgupta; Daniel J. Hsu; Nakul Verma (UAI, 2006)

On-Line Estimation with the Multivariate Gaussian Distribution. - Sanjoy Dasgupta; Daniel J. Hsu (COLT, 2007)

A learning framework for nearest neighbor search. - Lawrence Cayton; Sanjoy Dasgupta (NIPS, 2007)

A general agnostic active learning algorithm. - Sanjoy Dasgupta; Daniel J. Hsu; Claire Monteleoni (NIPS, 2007)

Learning the structure of manifolds using random projections. - Yoav Freund; Sanjoy Dasgupta; Mayank Kabra; Nakul Verma (NIPS, 2007)

A Probabilistic Analysis of EM for Mixtures of Separated, Spherical Gaussians. - Sanjoy Dasgupta; Leonard J. Schulman (J. Mach. Learn. Res., 2007)

Algorithms. - Sanjoy Dasgupta; Christos H. Papadimitriou; Umesh V. Vazirani (McGraw-Hill, 2008)

Hierarchical sampling for active learning. - Sanjoy Dasgupta; Daniel J. Hsu (ICML, 2008)

Random projection trees and low dimensional manifolds. - Sanjoy Dasgupta; Yoav Freund (STOC, 2008)

Special issue on learning theory. - Sanjoy Dasgupta (J. Comput. Syst. Sci., 2008)

Importance weighted active learning. - Alina Beygelzimer; Sanjoy Dasgupta; John Langford 001 (ICML, 2009)

Tutorial summary: Active learning. - Sanjoy Dasgupta; John Langford 001 (ICML, 2009)

Which Spatial Partition Trees are Adaptive to Intrinsic Dimension? - Nakul Verma; Samory Kpotufe; Sanjoy Dasgupta (UAI, 2009)

Learning Mixtures of Gaussians using the k-means Algorithm - Kamalika Chaudhuri; Sanjoy Dasgupta; Andrea Vattani (CoRR, 2009)

Analysis of Perceptron-Based Active Learning. - Sanjoy Dasgupta; Adam Tauman Kalai; Claire Monteleoni (J. Mach. Learn. Res., 2009)

Random projection trees for vector quantization. - Sanjoy Dasgupta; Yoav Freund (IEEE Trans. Inf. Theory, 2009)

Rates of convergence for the cluster tree. - Kamalika Chaudhuri; Sanjoy Dasgupta (NIPS, 2010)

Strange effects in high dimension. - Sanjoy Dasgupta (Commun. ACM, 2010)

Active Learning Theory. - Sanjoy Dasgupta (Encyclopedia of Machine Learning, 2010)

Recent advances in active learning. - Sanjoy Dasgupta (MLSLP, 2011)

Two faces of active learning. - Sanjoy Dasgupta (Theor. Comput. Sci., 2011)

Agglomerative Bregman Clustering. - Matus Telgarsky; Sanjoy Dasgupta (ICML, 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 (Wireless Health, 2012)

A tree-based regressor that adapts to intrinsic dimension. - Samory Kpotufe; Sanjoy Dasgupta (J. Comput. Syst. Sci., 2012)

Consistency of Nearest Neighbor Classification under Selective Sampling. - Sanjoy Dasgupta (COLT, 2012)

Randomized partition trees for exact nearest neighbor search. - Sanjoy Dasgupta; Kaushik Sinha (COLT, 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 (Healthcom, 2013)

The Fast Convergence of Incremental PCA. - Akshay Balsubramani; Sanjoy Dasgupta; Yoav Freund (NIPS, 2013)

Moment-based Uniform Deviation Bounds for k-means and Friends. - Matus Telgarsky; Sanjoy Dasgupta (NIPS, 2013)

Moment-based Uniform Deviation Bounds for $k$-means and Friends. - Matus Telgarsky; Sanjoy Dasgupta (CoRR, 2013)

Lower Bounds for the Gibbs Sampler over Mixtures of Gaussians. - Christopher Tosh; Sanjoy Dasgupta (ICML, 2014)

Incremental Clustering: The Case for Extra Clusters. - Margareta Ackerman; Sanjoy Dasgupta (NIPS, 2014)

Rates of Convergence for Nearest Neighbor Classification. - Kamalika Chaudhuri; Sanjoy Dasgupta (NIPS, 2014)

Optimal rates for k-NN density and mode estimation. - Sanjoy Dasgupta; Samory Kpotufe (NIPS, 2014)

Consistent Procedures for Cluster Tree Estimation and Pruning. - Kamalika Chaudhuri; Sanjoy Dasgupta; Samory Kpotufe; Ulrike von Luxburg (IEEE Trans. Inf. Theory, 2014)

Randomized Partition Trees for Nearest Neighbor Search. - Sanjoy Dasgupta; Kaushik Sinha (Algorithmica, 2015)

Interactive Bayesian Hierarchical Clustering. - Sharad Vikram; Sanjoy Dasgupta (ICML, 2016)

An algorithm for L1 nearest neighbor search via monotonic embedding. - Xinan Wang; Sanjoy Dasgupta (NIPS, 2016)

A cost function for similarity-based hierarchical clustering. - Sanjoy Dasgupta (STOC, 2016)

Learning with Feature Feedback: from Theory to Practice. - Stefanos Poulis; Sanjoy Dasgupta (AISTATS, 2017)

Diameter-Based Active Learning. - Christopher Tosh; Sanjoy Dasgupta (ICML, 2017)

Learning from partial correction. - Sanjoy Dasgupta; Michael Luby (CoRR, 2017)

Maximum Likelihood Estimation for Mixtures of Spherical Gaussians is NP-hard. - Christopher Tosh; Sanjoy Dasgupta (J. Mach. Learn. Res., 2017)

Active Learning Theory. - Sanjoy Dasgupta (Encyclopedia of Machine Learning and Data Mining, 2017)

Comparison Based Learning from Weak Oracles. - Ehsan Kazemi 001; Lin Chen 003; Sanjoy Dasgupta; Amin Karbasi (AISTATS, 2018)

Learning from discriminative feature feedback. - Sanjoy Dasgupta; Akansha Dey; Nicholas Roberts; Sivan Sabato (NeurIPS, 2018)

Interactive Structure Learning with Structural Query-by-Committee. - Christopher Tosh; Sanjoy Dasgupta (NeurIPS, 2018)

Structural query-by-committee. - Christopher Tosh; Sanjoy Dasgupta (CoRR, 2018)

A neural data structure for novelty detection. - Sanjoy Dasgupta; Timothy Sheehan; Charles F. Stevens; Saket Navlakha (Proc. Natl. Acad. Sci. USA, 2018)

Early Classification of Time Series by Simultaneously Optimizing the Accuracy and Earliness. - Usue Mori; Alexander Mendiburu; Sanjoy Dasgupta; José Antonio Lozano 001 (IEEE Trans. Neural Networks Learn. Syst., 2018)

The Relative Complexity of Maximum Likelihood Estimation, MAP Estimation, and Sampling. - Christopher Tosh; Sanjoy Dasgupta (COLT, 2019)

A Geometric Data Structure from Neuroscience (Invited Talk). - Sanjoy Dasgupta (SoCG, 2019)

Teaching a black-box learner. - Sanjoy Dasgupta; Daniel Hsu 001; Stefanos Poulis; Xiaojin Zhu 001 (ICML, 2019)

An adaptive nearest neighbor rule for classification. - Akshay Balsubramani; Sanjoy Dasgupta; Yoav Freund; Shay Moran (NeurIPS, 2019)

Interactive Topic Modeling with Anchor Words. - Sanjoy Dasgupta; Stefanos Poulis; Christopher Tosh (CoRR, 2019)

Nearest Neighbor Classification and Search. - Sanjoy Dasgupta; Samory Kpotufe (Beyond the Worst-Case Analysis of Algorithms, 2020)

Robust Learning from Discriminative Feature Feedback. - Sanjoy Dasgupta; Sivan Sabato (AISTATS, 2020)

A Three Sample Hypothesis Test for Evaluating Generative Models. - Casey Meehan; Kamalika Chaudhuri; Sanjoy Dasgupta (AISTATS, 2020)

What relations are reliably embeddable in Euclidean space? - Robi Bhattacharjee; Sanjoy Dasgupta (ALT, 2020)

Explainable k-Means and k-Medians Clustering. - Michal Moshkovitz; Sanjoy Dasgupta; Cyrus Rashtchian; Nave Frost (ICML, 2020)

A Non-Parametric Test to Detect Data-Copying in Generative Models. - Casey Meehan; Kamalika Chaudhuri; Sanjoy Dasgupta (CoRR, 2020)

Expressivity of expand-and-sparsify representations. - Sanjoy Dasgupta; Christopher Tosh (CoRR, 2020)

Theoretical Foundations of Hyperdimensional Computing. - Anthony Thomas; Sanjoy Dasgupta; Tajana Rosing (CoRR, 2020)

Habituation as a neural algorithm for online odor discrimination. - Yang Shen; Sanjoy Dasgupta; Saket Navlakha (Proc. Natl. Acad. Sci. USA, 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)

Algorithmic insights on continual learning from fruit flies. - Yang Shen; Sanjoy Dasgupta; Saket Navlakha (CoRR, 2021)

A Theoretical Perspective on Hyperdimensional Computing. - Anthony Thomas; Sanjoy Dasgupta; Tajana Rosing (J. Artif. Intell. Res., 2021)

Convergence of online k-means. - Geelon So; Gaurav Mahajan; Sanjoy Dasgupta (AISTATS, 2022)

Framework for Evaluating Faithfulness of Local Explanations. - Sanjoy Dasgupta; Nave Frost; Michal Moshkovitz (ICML, 2022)

Constants Matter: The Performance Gains of Active Learning. - Stephen O. Mussmann; Sanjoy Dasgupta (ICML, 2022)

A Theoretical Perspective on Hyperdimensional Computing (Extended Abstract). - Anthony Thomas; Sanjoy Dasgupta; Tajana Rosing (IJCAI, 2022)

Streaming Encoding Algorithms for Scalable Hyperdimensional Computing. - Anthony Thomas; Behnam Khaleghi; Gopi Krishna Jha; Sanjoy Dasgupta; Nageen Himayat; Ravi Iyer 001; Nilesh Jain; Tajana Rosing (CoRR, 2022)

Online k-means Clustering on Arbitrary Data Streams. - Robi Bhattacharjee; Jacob Imola; Michal Moshkovitz; Sanjoy Dasgupta (ALT, 2023)

Data-Copying in Generative Models: A Formal Framework. - Robi Bhattacharjee; Sanjoy Dasgupta; Kamalika Chaudhuri (ICML, 2023)

Active learning using region-based sampling. - Sanjoy Dasgupta; Yoav Freund (CoRR, 2023)

Online nearest neighbor classification. - Sanjoy Dasgupta; Geelon So (CoRR, 2023)

Rethinking Logic Minimization for Tabular Machine Learning. - Litao Qiao; Weijia Wang 002; Sanjoy Dasgupta; Bill Lin 001 (IEEE Trans. Artif. Intell., 2023)

Reducing Catastrophic Forgetting With Associative Learning: A Lesson From Fruit Flies. - Yang Shen; Sanjoy Dasgupta; Saket Navlakha (Neural Comput., 2023)

New Bounds on the Cohesion of Complete-link and Other Linkage Methods for Agglomerative Clustering. - Sanjoy Dasgupta; Eduardo Sany Laber (ICML, 2024)

Online Consistency of the Nearest Neighbor Rule. - Geelon So; Sanjoy Dasgupta (NeurIPS, 2024)

Convergence Behavior of an Adversarial Weak Supervision Method. - Steven An 002; Sanjoy Dasgupta (UAI, 2024)

New bounds on the cohesion of complete-link and other linkage methods for agglomeration clustering. - Sanjoy Dasgupta; Eduardo Sany Laber (CoRR, 2024)

Learning Smooth Distance Functions via Queries. - Akash Kumar 010; Sanjoy Dasgupta (CoRR, 2024)

Graph neural networks extrapolate out-of-distribution for shortest paths. - Robert R. Nerem; Samantha Chen 001; Sanjoy Dasgupta; Yusu Wang 001 (CoRR, 2025)