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ORCIDSanjoy Dasgupta
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- affiliation: University of California, San Diego, Department of Computer Science and Engineering
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2020 – today
- 2024
[c69]Sanjoy Dasgupta, Eduardo Sany Laber:
New Bounds on the Cohesion of Complete-link and Other Linkage Methods for Agglomerative Clustering. ICML 2024- [e2]Sanjoy Dasgupta, Stephan Mandt, Yingzhen Li:
International Conference on Artificial Intelligence and Statistics, 2-4 May 2024, Palau de Congressos, Valencia, Spain. Proceedings of Machine Learning Research 238, PMLR 2024 [contents] - [i35]Sanjoy Dasgupta, Eduardo Sany Laber:
New bounds on the cohesion of complete-link and other linkage methods for agglomeration clustering. CoRR abs/2405.00937 (2024) - [i34]Steven An, Sanjoy Dasgupta:
Convergence Behavior of an Adversarial Weak Supervision Method. CoRR abs/2405.16013 (2024) - 2023
- [j22]Yang Shen, Sanjoy Dasgupta, Saket Navlakha:
Reducing Catastrophic Forgetting With Associative Learning: A Lesson From Fruit Flies. Neural Comput. 35(11): 1797-1819 (2023) - [j21]Litao Qiao
, Weijia Wang, Sanjoy Dasgupta, Bill Lin:
Rethinking Logic Minimization for Tabular Machine Learning. IEEE Trans. Artif. Intell. 4(5): 1129-1140 (2023) - [c68]Robi Bhattacharjee, Jacob Imola, Michal Moshkovitz, Sanjoy Dasgupta:
Online k-means Clustering on Arbitrary Data Streams. ALT 2023: 204-236 - [c67]Robi Bhattacharjee, Sanjoy Dasgupta, Kamalika Chaudhuri:
Data-Copying in Generative Models: A Formal Framework. ICML 2023: 2364-2396 - [i33]Robi Bhattacharjee, Sanjoy Dasgupta, Kamalika Chaudhuri:
Data-Copying in Generative Models: A Formal Framework. CoRR abs/2302.13181 (2023) - [i32]Sanjoy Dasgupta, Yoav Freund:
Active learning using region-based sampling. CoRR abs/2303.02721 (2023) - [i31]Sanjoy Dasgupta, Geelon So:
Online nearest neighbor classification. CoRR abs/2307.01170 (2023) - 2022
- [c66]Geelon So, Gaurav Mahajan, Sanjoy Dasgupta:
Convergence of online k-means. AISTATS 2022: 8534-8569 - [c65]Sanjoy Dasgupta, Nave Frost, Michal Moshkovitz:
Framework for Evaluating Faithfulness of Local Explanations. ICML 2022: 4794-4815 - [c64]Stephen O. Mussmann, Sanjoy Dasgupta:
Constants Matter: The Performance Gains of Active Learning. ICML 2022: 16123-16173 - [c63]Anthony Thomas, Sanjoy Dasgupta, Tajana Rosing:
A Theoretical Perspective on Hyperdimensional Computing (Extended Abstract). IJCAI 2022: 5772-5776 - [e1]Sanjoy Dasgupta, Nika Haghtalab:
International Conference on Algorithmic Learning Theory, 29 March - 1 April 2022, Paris, France. Proceedings of Machine Learning Research 167, PMLR 2022 [contents] - [i30]Sanjoy Dasgupta, Nave Frost, Michal Moshkovitz:
Framework for Evaluating Faithfulness of Local Explanations. CoRR abs/2202.00734 (2022) - [i29]Sanjoy Dasgupta, Gaurav Mahajan, Geelon So:
Convergence of online k-means. CoRR abs/2202.10640 (2022) - [i28]Anthony Thomas, Behnam Khaleghi, Gopi Krishna Jha, Sanjoy Dasgupta, Nageen Himayat, Ravi Iyer, Nilesh Jain, Tajana Rosing:
Streaming Encoding Algorithms for Scalable Hyperdimensional Computing. CoRR abs/2209.09868 (2022) - 2021
- [j20]Anthony Thomas, Sanjoy Dasgupta, Tajana Rosing:
A Theoretical Perspective on Hyperdimensional Computing. J. Artif. Intell. Res. 72: 215-249 (2021) - [i27]Yang Shen, Sanjoy Dasgupta, Saket Navlakha:
Algorithmic insights on continual learning from fruit flies. CoRR abs/2107.07617 (2021) - 2020
- [j19]Yang Shen, Sanjoy Dasgupta, Saket Navlakha:
Habituation as a neural algorithm for online odor discrimination. Proc. Natl. Acad. Sci. USA 117(22): 12402-12410 (2020) - [j18]Yang Shen, Sanjoy Dasgupta, Saket Navlakha:
Reply to Semelidou and Skoulakis: "Short-term" habituation has multiple distinct mechanisms. Proc. Natl. Acad. Sci. USA 117(34): 20373-20374 (2020) - [c62]Sanjoy Dasgupta, Sivan Sabato:
Robust Learning from Discriminative Feature Feedback. AISTATS 2020: 973-982 - [c61]Casey Meehan, Kamalika Chaudhuri, Sanjoy Dasgupta:
A Three Sample Hypothesis Test for Evaluating Generative Models. AISTATS 2020: 3546-3556 - [c60]Robi Bhattacharjee, Sanjoy Dasgupta:
What relations are reliably embeddable in Euclidean space? ALT 2020: 174-195 - [c59]Michal Moshkovitz, Sanjoy Dasgupta, Cyrus Rashtchian, Nave Frost:
Explainable k-Means and k-Medians Clustering. ICML 2020: 7055-7065 - [p1]Sanjoy Dasgupta, Samory Kpotufe:
Nearest Neighbor Classification and Search. Beyond the Worst-Case Analysis of Algorithms 2020: 403-423 - [i26]Sanjoy Dasgupta, Nave Frost, Michal Moshkovitz, Cyrus Rashtchian:
Explainable k-Means and k-Medians Clustering. CoRR abs/2002.12538 (2020) - [i25]Sanjoy Dasgupta, Sivan Sabato:
Robust Learning from Discriminative Feature Feedback. CoRR abs/2003.03946 (2020) - [i24]Casey Meehan, Kamalika Chaudhuri, Sanjoy Dasgupta:
A Non-Parametric Test to Detect Data-Copying in Generative Models. CoRR abs/2004.05675 (2020) - [i23]Sanjoy Dasgupta, Christopher Tosh:
Expressivity of expand-and-sparsify representations. CoRR abs/2006.03741 (2020) - [i22]Anthony Thomas, Sanjoy Dasgupta, Tajana Rosing:
Theoretical Foundations of Hyperdimensional Computing. CoRR abs/2010.07426 (2020)
2010 – 2019
- 2019
- [c58]Christopher Tosh, Sanjoy Dasgupta:
The Relative Complexity of Maximum Likelihood Estimation, MAP Estimation, and Sampling. COLT 2019: 2993-3035 - [c57]Sanjoy Dasgupta:
A Geometric Data Structure from Neuroscience (Invited Talk). SoCG 2019: 1:1-1:1 - [c56]Sanjoy Dasgupta, Daniel Hsu, Stefanos Poulis, Xiaojin Zhu:
Teaching a black-box learner. ICML 2019: 1547-1555 - [c55]Akshay Balsubramani, Sanjoy Dasgupta, Yoav Freund, Shay Moran:
An adaptive nearest neighbor rule for classification. NeurIPS 2019: 7577-7586 - [i21]Robi Bhattacharjee, Sanjoy Dasgupta:
What relations are reliably embeddable in Euclidean space? CoRR abs/1903.05347 (2019) - [i20]Akshay Balsubramani, Sanjoy Dasgupta, Yoav Freund, Shay Moran:
An adaptive nearest neighbor rule for classification. CoRR abs/1905.12717 (2019) - [i19]Sanjoy Dasgupta, Stefanos Poulis, Christopher Tosh:
Interactive Topic Modeling with Anchor Words. CoRR abs/1907.04919 (2019) - 2018
- [j17]Sanjoy Dasgupta, Timothy Sheehan, Charles F. Stevens, Saket Navlakha:
A neural data structure for novelty detection. Proc. Natl. Acad. Sci. USA 115(51): 13093-13098 (2018) - [j16]Usue Mori, Alexander Mendiburu, Sanjoy Dasgupta, José Antonio Lozano:
Early Classification of Time Series by Simultaneously Optimizing the Accuracy and Earliness. IEEE Trans. Neural Networks Learn. Syst. 29(10): 4569-4578 (2018) - [c54]Ehsan Kazemi, Lin Chen, Sanjoy Dasgupta, Amin Karbasi:
Comparison Based Learning from Weak Oracles. AISTATS 2018: 1849-1858 - [c53]Christopher Tosh, Sanjoy Dasgupta:
Interactive Structure Learning with Structural Query-by-Committee. NeurIPS 2018: 1129-1139 - [c52]Sanjoy Dasgupta, Akansha Dey, Nicholas Roberts, Sivan Sabato:
Learning from discriminative feature feedback. NeurIPS 2018: 3959-3967 - [i18]Ehsan Kazemi, Lin Chen, Sanjoy Dasgupta, Amin Karbasi:
Comparison Based Learning from Weak Oracles. CoRR abs/1802.06942 (2018) - [i17]Christopher Tosh, Sanjoy Dasgupta:
Structural query-by-committee. CoRR abs/1803.06586 (2018) - 2017
- [j15]Christopher Tosh, Sanjoy Dasgupta:
Maximum Likelihood Estimation for Mixtures of Spherical Gaussians is NP-hard. J. Mach. Learn. Res. 18: 175:1-175:11 (2017) - [c51]Stefanos Poulis, Sanjoy Dasgupta:
Learning with Feature Feedback: from Theory to Practice. AISTATS 2017: 1104-1113 - [c50]Christopher Tosh, Sanjoy Dasgupta:
Diameter-Based Active Learning. ICML 2017: 3444-3452 - [r2]Sanjoy Dasgupta:
Active Learning Theory. Encyclopedia of Machine Learning and Data Mining 2017: 14-19 - [i16]Christopher Tosh, Sanjoy Dasgupta:
Diameter-Based Active Learning. CoRR abs/1702.08553 (2017) - [i15]Sanjoy Dasgupta, Michael Luby:
Learning from partial correction. CoRR abs/1705.08076 (2017) - 2016
- [c49]Sharad Vikram, Sanjoy Dasgupta:
Interactive Bayesian Hierarchical Clustering. ICML 2016: 2081-2090 - [c48]Xinan Wang, Sanjoy Dasgupta:
An algorithm for L1 nearest neighbor search via monotonic embedding. NIPS 2016: 983-991 - [c47]Sanjoy Dasgupta:
A cost function for similarity-based hierarchical clustering. STOC 2016: 118-127 - [i14]Sharad Vikram, Sanjoy Dasgupta:
Interactive Bayesian Hierarchical Clustering. CoRR abs/1602.03258 (2016) - 2015
- [j14]Sanjoy Dasgupta, Kaushik Sinha:
Randomized Partition Trees for Nearest Neighbor Search. Algorithmica 72(1): 237-263 (2015) - [i13]Akshay Balsubramani, Sanjoy Dasgupta, Yoav Freund:
The Fast Convergence of Incremental PCA. CoRR abs/1501.03796 (2015) - [i12]Sanjoy Dasgupta:
A cost function for similarity-based hierarchical clustering. CoRR abs/1510.05043 (2015) - 2014
- [j13]Kamalika Chaudhuri, Sanjoy Dasgupta, Samory Kpotufe, Ulrike von Luxburg:
Consistent Procedures for Cluster Tree Estimation and Pruning. IEEE Trans. Inf. Theory 60(12): 7900-7912 (2014) - [c46]Christopher Tosh, Sanjoy Dasgupta:
Lower Bounds for the Gibbs Sampler over Mixtures of Gaussians. ICML 2014: 1467-1475 - [c45]Margareta Ackerman, Sanjoy Dasgupta:
Incremental Clustering: The Case for Extra Clusters. NIPS 2014: 307-315 - [c44]Sanjoy Dasgupta, Samory Kpotufe:
Optimal rates for k-NN density and mode estimation. NIPS 2014: 2555-2563 - [c43]Kamalika Chaudhuri, Sanjoy Dasgupta:
Rates of Convergence for Nearest Neighbor Classification. NIPS 2014: 3437-3445 - [i11]Margareta Ackerman, Sanjoy Dasgupta:
Incremental Clustering: The Case for Extra Clusters. CoRR abs/1406.6398 (2014) - [i10]Kamalika Chaudhuri, Sanjoy Dasgupta:
Rates of Convergence for Nearest Neighbor Classification. CoRR abs/1407.0067 (2014) - 2013
- [c42]Sanjoy Dasgupta, Kaushik Sinha:
Randomized partition trees for exact nearest neighbor search. COLT 2013: 317-337 - [c41]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:
DELPHI: Data E-platform for personalized population health. Healthcom 2013: 115-119 - [c40]Matus Telgarsky, Sanjoy Dasgupta:
Moment-based Uniform Deviation Bounds for k-means and Friends. NIPS 2013: 2940-2948 - [c39]Akshay Balsubramani, Sanjoy Dasgupta, Yoav Freund:
The Fast Convergence of Incremental PCA. NIPS 2013: 3174-3182 - [i9]Sanjoy Dasgupta:
Experiments with Random Projection. CoRR abs/1301.3849 (2013) - [i8]Sanjoy Dasgupta, Leonard J. Schulman:
A Two-round Variant of EM for Gaussian Mixtures. CoRR abs/1301.3850 (2013) - [i7]Sanjoy Dasgupta:
Learning Polytrees. CoRR abs/1301.6688 (2013) - [i6]Sanjoy Dasgupta, Kaushik Sinha:
Randomized partition trees for exact nearest neighbor search. CoRR abs/1302.1948 (2013) - [i5]Matus Telgarsky, Sanjoy Dasgupta:
Moment-based Uniform Deviation Bounds for $k$-means and Friends. CoRR abs/1311.1903 (2013) - 2012
- [j12]Samory Kpotufe, Sanjoy Dasgupta:
A tree-based regressor that adapts to intrinsic dimension. J. Comput. Syst. Sci. 78(5): 1496-1515 (2012) - [c38]Matus Telgarsky, Sanjoy Dasgupta:
Agglomerative Bregman Clustering. ICML 2012 - [c37]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:
CitiSense: improving geospatial environmental assessment of air quality using a wireless personal exposure monitoring system. Wireless Health 2012: 11:1-11:8 - [c36]Sanjoy Dasgupta:
Consistency of Nearest Neighbor Classification under Selective Sampling. COLT 2012: 18.1-18.15 - [i4]Nakul Verma, Samory Kpotufe, Sanjoy Dasgupta:
Which Spatial Partition Trees are Adaptive to Intrinsic Dimension? CoRR abs/1205.2609 (2012) - [i3]Sanjoy Dasgupta, Daniel J. Hsu, Nakul Verma:
A concentration theorem for projections. CoRR abs/1206.6813 (2012) - 2011
- [j11]Sanjoy Dasgupta:
Two faces of active learning. Theor. Comput. Sci. 412(19): 1767-1781 (2011) - [c35]Sanjoy Dasgupta:
Recent advances in active learning. MLSLP 2011 - 2010
- [j10]Sanjoy Dasgupta:
Strange effects in high dimension. Commun. ACM 53(2): 96 (2010) - [c34]Kamalika Chaudhuri, Sanjoy Dasgupta:
Rates of convergence for the cluster tree. NIPS 2010: 343-351 - [r1]Sanjoy Dasgupta:
Active Learning Theory. Encyclopedia of Machine Learning 2010: 14-19
2000 – 2009
- 2009
- [j9]Sanjoy Dasgupta, Adam Tauman Kalai, Claire Monteleoni:
Analysis of Perceptron-Based Active Learning. J. Mach. Learn. Res. 10: 281-299 (2009) - [j8]Sanjoy Dasgupta, Yoav Freund:
Random projection trees for vector quantization. IEEE Trans. Inf. Theory 55(7): 3229-3242 (2009) - [c33]Sanjoy Dasgupta:
The Two Faces of Active Learning. ALT 2009: 1 - [c32]Sanjoy Dasgupta:
The Two Faces of Active Learning. Discovery Science 2009: 35 - [c31]Sanjoy Dasgupta, John Langford:
Tutorial summary: Active learning. ICML 2009: 18 - [c30]Alina Beygelzimer, Sanjoy Dasgupta, John Langford:
Importance weighted active learning. ICML 2009: 49-56 - [c29]Nakul Verma, Samory Kpotufe, Sanjoy Dasgupta:
Which Spatial Partition Trees are Adaptive to Intrinsic Dimension? UAI 2009: 565-574 - [i2]Kamalika Chaudhuri, Sanjoy Dasgupta, Andrea Vattani:
Learning Mixtures of Gaussians using the k-means Algorithm. CoRR abs/0912.0086 (2009) - 2008
- [b1]Sanjoy Dasgupta, Christos H. Papadimitriou, Umesh V. Vazirani:
Algorithms. McGraw-Hill 2008, ISBN 978-0-07-352340-8, pp. I-X, 1-320 - [j7]Sanjoy Dasgupta:
Special issue on learning theory. J. Comput. Syst. Sci. 74(1): 1 (2008) - [c28]Sanjoy Dasgupta, Yoav Freund:
Random projection trees for vector quantization. Allerton 2008: 192-197 - [c27]Sanjoy Dasgupta, Daniel J. Hsu:
Hierarchical sampling for active learning. ICML 2008: 208-215 - [c26]Sanjoy Dasgupta, Daniel J. Hsu, Claire Monteleoni:
A General Agnostic Active Learning Algorithm. ISAIM 2008 - [c25]Sanjoy Dasgupta, Yoav Freund:
Random projection trees and low dimensional manifolds. STOC 2008: 537-546 - [i1]Alina Beygelzimer, Sanjoy Dasgupta, John Langford:
Importance Weighted Active Learning. CoRR abs/0812.4952 (2008) - 2007
- [j6]Sanjoy Dasgupta, Leonard J. Schulman:
A Probabilistic Analysis of EM for Mixtures of Separated, Spherical Gaussians. J. Mach. Learn. Res. 8: 203-226 (2007) - [c24]Sanjoy Dasgupta, Daniel J. Hsu:
On-Line Estimation with the Multivariate Gaussian Distribution. COLT 2007: 278-292 - [c23]Lawrence Cayton, Sanjoy Dasgupta:
A learning framework for nearest neighbor search. NIPS 2007: 233-240 - [c22]Sanjoy Dasgupta, Daniel J. Hsu, Claire Monteleoni:
A general agnostic active learning algorithm. NIPS 2007: 353-360 - [c21]Yoav Freund, Sanjoy Dasgupta, Mayank Kabra, Nakul Verma:
Learning the structure of manifolds using random projections. NIPS 2007: 473-480 - 2006
- [c20]Lawrence Cayton, Sanjoy Dasgupta:
Robust Euclidean embedding. ICML 2006: 169-176 - [c19]Sanjoy Dasgupta, Daniel J. Hsu, Nakul Verma:
A Concentration Theorem for Projections. UAI 2006 - 2005
- [j5]Sanjoy Dasgupta, Philip M. Long:
Performance guarantees for hierarchical clustering. J. Comput. Syst. Sci. 70(4): 555-569 (2005) - [j4]Tugkan Batu, Sanjoy Dasgupta, Ravi Kumar, Ronitt Rubinfeld:
The Complexity of Approximating the Entropy. SIAM J. Comput. 35(1): 132-150 (2005) - [c18]Sanjoy Dasgupta, Adam Tauman Kalai, Claire Monteleoni:
Analysis of Perceptron-Based Active Learning. COLT 2005: 249-263 - [c17]Sanjoy Dasgupta:
Coarse sample complexity bounds for active learning. NIPS 2005: 235-242 - 2004
- [c16]Sanjoy Dasgupta:
Analysis of a greedy active learning strategy. NIPS 2004: 337-344 - 2003
- [j3]Sanjoy Dasgupta, Wee Sun Lee, Philip M. Long:
A Theoretical Analysis of Query Selection for Collaborative Filtering. Mach. Learn. 51(3): 283-298 (2003) - [j2]Sanjoy Dasgupta, Anupam Gupta:
An elementary proof of a theorem of Johnson and Lindenstrauss. Random Struct. Algorithms 22(1): 60-65 (2003) - [c15]Sanjoy Dasgupta, Philip M. Long:
Boosting with Diverse Base Classifiers. COLT 2003: 273-287 - [c14]Sanjoy Dasgupta:
Subspace Detection: A Robust Statistics Formulation. COLT 2003: 734 - [c13]Sanjoy Dasgupta:
How Fast Is k-Means? COLT 2003: 735 - [c12]David Kauchak, Sanjoy Dasgupta:
An Iterative Improvement Procedure for Hierarchical Clustering. NIPS 2003: 481-488 - 2002
- [c11]Sanjoy Dasgupta, Elan Pavlov, Yoram Singer:
An Efficient PAC Algorithm for Reconstructing a Mixture of Lines. ALT 2002: 351-364 - [c10]Tugkan Batu, Sanjoy Dasgupta, Ravi Kumar, Ronitt Rubinfeld:
The Complexity of Approximating the Entropy. CCC 2002: 17 - [c9]Sanjoy Dasgupta:
Performance Guarantees for Hierarchical Clustering. COLT 2002: 351-363 - [c8]Tugkan Batu, Sanjoy Dasgupta, Ravi Kumar, Ronitt Rubinfeld:
The complexity of approximating entropy. STOC 2002: 678-687 - 2001
- [c7]Doina Precup, Richard S. Sutton, Sanjoy Dasgupta:
Off-Policy Temporal Difference Learning with Function Approximation. ICML 2001: 417-424 - [c6]Sanjoy Dasgupta, Michael L. Littman, David A. McAllester:
PAC Generalization Bounds for Co-training. NIPS 2001: 375-382 - [c5]Michael Collins, Sanjoy Dasgupta, Robert E. Schapire:
A Generalization of Principal Components Analysis to the Exponential Family. NIPS 2001: 617-624 - 2000
- [c4]Sanjoy Dasgupta:
Experiments with Random Projection. UAI 2000: 143-151 - [c3]Sanjoy Dasgupta, Leonard J. Schulman:
A Two-Round Variant of EM for Gaussian Mixtures. UAI 2000: 152-159
1990 – 1999
- 1999
- [c2]Sanjoy Dasgupta:
Learning Mixtures of Gaussians. FOCS 1999: 634-644 - [c1]Sanjoy Dasgupta:
Learning Polytrees. UAI 1999: 134-141 - 1997
- [j1]Sanjoy Dasgupta:
The Sample Complexity of Learning Fixed-Structure Bayesian Networks. Mach. Learn. 29(2-3): 165-180 (1997)
Coauthor Index
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