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Christopher Tosh
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Books and Theses
- 2018
- [b1]Christopher Tosh:
Algorithms for Statistical and Interactive Learning Tasks. University of California, San Diego, USA, 2018
Journal Articles
- 2021
- [j2]Christopher Tosh, Akshay Krishnamurthy, Daniel Hsu:
Contrastive Estimation Reveals Topic Posterior Information to Linear Models. J. Mach. Learn. Res. 22: 281:1-281:31 (2021) - 2017
- [j1]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)
Conference and Workshop Papers
- 2022
- [c9]Christopher J. Tosh, Daniel Hsu:
Simple and near-optimal algorithms for hidden stratification and multi-group learning. ICML 2022: 21633-21657 - 2021
- [c8]Christopher Tosh, Akshay Krishnamurthy, Daniel Hsu:
Contrastive learning, multi-view redundancy, and linear models. ALT 2021: 1179-1206 - [c7]Max Simchowitz, Christopher Tosh, Akshay Krishnamurthy, Daniel J. Hsu, Thodoris Lykouris, Miroslav Dudík, Robert E. Schapire:
Bayesian decision-making under misspecified priors with applications to meta-learning. NeurIPS 2021: 26382-26394 - 2020
- [c6]Christopher Tosh, Daniel Hsu:
Diameter-based Interactive Structure Discovery. AISTATS 2020: 580-590 - 2019
- [c5]Christopher Tosh, Sanjoy Dasgupta:
The Relative Complexity of Maximum Likelihood Estimation, MAP Estimation, and Sampling. COLT 2019: 2993-3035 - 2018
- [c4]Christopher Tosh, Sanjoy Dasgupta:
Interactive Structure Learning with Structural Query-by-Committee. NeurIPS 2018: 1129-1139 - 2017
- [c3]Christopher Tosh, Sanjoy Dasgupta:
Diameter-Based Active Learning. ICML 2017: 3444-3452 - 2016
- [c2]Christopher Tosh:
Mixing Rates for the Alternating Gibbs Sampler over Restricted Boltzmann Machines and Friends. ICML 2016: 840-849 - 2014
- [c1]Christopher Tosh, Sanjoy Dasgupta:
Lower Bounds for the Gibbs Sampler over Mixtures of Gaussians. ICML 2014: 1467-1475
Informal and Other Publications
- 2022
- [i11]Christopher Tosh, Mauricio Tec, Wesley Tansey:
Targeted active learning for probabilistic models. CoRR abs/2210.12122 (2022) - 2021
- [i10]Max Simchowitz, Christopher Tosh, Akshay Krishnamurthy, Daniel Hsu, Thodoris Lykouris, Miroslav Dudík, Robert E. Schapire:
Bayesian decision-making under misspecified priors with applications to meta-learning. CoRR abs/2107.01509 (2021) - [i9]Christopher Tosh, Daniel Hsu:
Simple and near-optimal algorithms for hidden stratification and multi-group learning. CoRR abs/2112.12181 (2021) - 2020
- [i8]Christopher Tosh, Akshay Krishnamurthy, Daniel Hsu:
Contrastive estimation reveals topic posterior information to linear models. CoRR abs/2003.02234 (2020) - [i7]Sanjoy Dasgupta, Christopher Tosh:
Expressivity of expand-and-sparsify representations. CoRR abs/2006.03741 (2020) - [i6]Christopher Tosh, Akshay Krishnamurthy, Daniel Hsu:
Contrastive learning, multi-view redundancy, and linear models. CoRR abs/2008.10150 (2020) - 2019
- [i5]Christopher Tosh, Daniel Hsu:
Diameter-based Interactive Structure Search. CoRR abs/1906.02101 (2019) - [i4]Wesley Tansey, Christopher Tosh, David M. Blei:
Bayesian Tensor Filtering: Smooth, Locally-Adaptive Factorization of Functional Matrices. CoRR abs/1906.04072 (2019) - [i3]Sanjoy Dasgupta, Stefanos Poulis, Christopher Tosh:
Interactive Topic Modeling with Anchor Words. CoRR abs/1907.04919 (2019) - 2018
- [i2]Christopher Tosh, Sanjoy Dasgupta:
Structural query-by-committee. CoRR abs/1803.06586 (2018) - 2017
- [i1]Christopher Tosh, Sanjoy Dasgupta:
Diameter-Based Active Learning. CoRR abs/1702.08553 (2017)
Coauthor Index
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