Daniel Hsu

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Sham M KakadeHarvard UniversityVerified email at seas.harvard.edu
Tong ZhangUIUCVerified email at tongzhang-ml.org
Anima AnandkumarCalifornia Institute of Technology and NVIDIAVerified email at caltech.edu
Matus TelgarskyCourant Institute of Mathematical Sciences, New York UniversityVerified email at nyu.edu
John LangfordMicrosoft Research New YorkVerified email at hunch.net
Mikhail (Misha) BelkinProfessor of Data Science, Halıcıoğlu Data Science Institute, CSE, UCSD, Amazon ScholarVerified email at ucsd.edu
Roxana GeambasuAssistant Professor of Computer Science, Columbia UniversityVerified email at columbia.edu
Ji XuColumbia UniversityVerified email at columbia.edu
Rong GeDuke UniversityVerified email at cs.duke.edu
Kamalika ChaudhuriUCSD, MetaVerified email at ucsd.edu
Mathias LécuyerUniversity of British ColumbiaVerified email at ubc.ca
Dean FosterAmazon, NYCVerified email at amazon.com
Luis GravanoProfessor of Computer Science, Columbia UniversityVerified email at cs.columbia.edu
Christopher ToshMemorial Sloan Kettering Cancer CenterVerified email at mskcc.org
Vaggelis AtlidakisLaceworkVerified email at brown.edu
Alekh AgarwalGoogleVerified email at google.com
Siyuan MaThe Ohio State UniversityVerified email at cse.ohio-state.edu
soumik mandalPhD student, Ohio State UniversityVerified email at buckeyemail.osu.edu
Suman JanaAssociate Professor of Computer Science, Columbia UniversityVerified email at cs.columbia.edu
Zoltan HaimanColumbia UniversityVerified email at astro.columbia.edu

Daniel Hsu

Columbia University

Verified email at cs.columbia.edu - Homepage

Algorithmic statistics machine learning


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Reconciling modern machine-learning practice and the classical bias–variance trade-off M Belkin, D Hsu, S Ma, S Mandal Proceedings of the National Academy of Sciences 116 (32), 15849-15854, 2019	2181	2019
Tensor decompositions for learning latent variable models. A Anandkumar, R Ge, DJ Hsu, SM Kakade, M Telgarsky J. Mach. Learn. Res. 15 (1), 2773-2832, 2014	1384	2014
Certified robustness to adversarial examples with differential privacy M Lecuyer, V Atlidakis, R Geambasu, D Hsu, S Jana arXiv preprint arXiv:1802.03471, 2018	1123	2018
Hierarchical sampling for active learning S Dasgupta, D Hsu Proceedings of the 25th international conference on Machine learning, 208-215, 2008	634	2008
A spectral algorithm for learning hidden markov models D Hsu, SM Kakade, T Zhang Arxiv preprint arXiv:0811.4413, 2008	624*	2008
Taming the monster: A fast and simple algorithm for contextual bandits A Agarwal, D Hsu, S Kale, J Langford, L Li, RE Schapire Thirty-First International Conference on Machine Learning, 2014	592	2014
Multi-label prediction via compressed sensing DJ Hsu, SM Kakade, J Langford, T Zhang Advances in neural information processing systems 22, 2009	530	2009
A tail inequality for quadratic forms of subgaussian random vectors D Hsu, SM Kakade, T Zhang Arxiv preprint arXiv:1110.2842, 2011	484	2011
Two models of double descent for weak features M Belkin, D Hsu, J Xu SIAM Journal on Mathematics of Data Science 2 (4), 1167-1180, 2020	464	2020
A spectral algorithm for latent dirichlet allocation A Anandkumar, Y Liu, D Hsu, DP Foster, SM Kakade Advances in Neural Information Processing Systems, 917-925, 2012	407	2012
A general agnostic active learning algorithm S Dasgupta, D Hsu, C Monteleoni Advances in neural information processing systems 20, 353-360, 2007	393	2007
Learning mixtures of spherical gaussians: moment methods and spectral decompositions D Hsu, SM Kakade Proceedings of the 4th conference on Innovations in Theoretical Computer …, 2013	391	2013
A method of moments for mixture models and hidden Markov models A Anandkumar, D Hsu, SM Kakade Conference on learning theory, 33.1-33.34, 2012	388	2012
Efficient optimal learning for contextual bandits M Dudik, D Hsu, S Kale, N Karampatziakis, J Langford, L Reyzin, T Zhang arXiv preprint arXiv:1106.2369, 2011	374	2011
a CAPpella: programming by demonstration of context-aware applications AK Dey, R Hamid, C Beckmann, I Li, D Hsu Proceedings of the SIGCHI conference on Human factors in computing systems …, 2004	345	2004
Overfitting or perfect fitting? risk bounds for classification and regression rules that interpolate M Belkin, DJ Hsu, P Mitra Advances in neural information processing systems 31, 2018	331	2018
Robust Matrix Decomposition with Sparse Corruptions D Hsu, SM Kakade, T Zhang Information Theory, IEEE Transactions on, 1-1, 2011	293	2011
Discovering unwarranted associations in data-driven applications with the fairtest testing toolkit F Tramèr, V Atlidakis, R Geambasu, DJ Hsu, JP Hubaux, M Humbert, ... CoRR, abs/1510.02377, 2015	255*	2015
Stochastic convex optimization with bandit feedback A Agarwal, DP Foster, D Hsu, SM Kakade, A Rakhlin Advances in Neural Information Processing Systems, 1035-1043, 2011	232	2011
Loss minimization and parameter estimation with heavy tails D Hsu, S Sabato Journal of Machine Learning Research 17 (18), 1-40, 2016	211	2016

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