Bibtex entries for research papers

@inproceedings{karamanolakis2020cross,
  author = "Karamanolakis, Giannis and Hsu, Daniel and Gravano, Luis",
  booktitle = "Conference on Empirical Methods in Natural Language Processing: Findings",
  title = "Cross-lingual text classification with minimal resources by transferring a sparse teacher",
  year = "2020"
}
@article{hsu2020proliferation,
  author = "Hsu, Daniel and Muthukumar, Vidya and Xu, Ji",
  journal = "arXiv preprint arXiv:2009.10670",
  title = "On the proliferation of support vectors in high dimensions",
  year = "2020"
}
@article{tosh2020redundancy,
  author = "Tosh, Christopher and Krishnamurthy, Akshay and Hsu, Daniel",
  journal = "arXiv preprint arXiv:2008.10150",
  title = "Contrastive learning, multi-view redundancy, and linear models",
  year = "2020"
}
@article{dudeja2020statistical,
  author = "Dudeja, Rishabh and Hsu, Daniel",
  journal = "arXiv preprint arXiv:2008.04101",
  title = "Statistical query lower bounds for tensor PCA",
  year = "2020"
}
@article{zorrilla2020interpreting,
  author = "Zorrilla Matilla, José Manuel and Sharma, Manasi and Hsu, Daniel and Haiman, Zoltán",
  journal = "arXiv preprint arXiv:2007.06529",
  title = "Interpreting deep learning models for weak lensing",
  year = "2020"
}
@inproceedings{mandal2020ensuring,
  author = "Mandal, Debmalya and Deng, Samuel and Jana, Suman and Wing, Jeannette M. and Hsu, Daniel",
  booktitle = "Advances in Neural Information Processing Systems 33",
  title = "Ensuring fairness beyond the training data",
  year = "2020"
}
@article{muthukumar2020classification,
  author = "Muthukumar, Vidya and Narang, Adhyyan and Subramanian, Vignesh and Belkin, Mikhail and Hsu, Daniel and Sahai, Anant",
  journal = "arXiv preprint arXiv:2005.08054",
  title = "Classification vs regression in overparameterized regimes: Does the loss function matter?",
  year = "2020"
}
@article{tosh2020contrastive,
  author = "Tosh, Christopher and Krishnamurthy, Akshay and Hsu, Daniel",
  journal = "arXiv preprint arXiv:2003.02234",
  title = "Contrastive estimation reveals topic posterior information to linear models",
  year = "2020"
}
@inproceedings{tosh2020diameter,
  author = "Tosh, Christopher and Hsu, Daniel",
  booktitle = "Twenty-Third International Conference on Artificial Intelligence and Statistics",
  title = "Diameter-based interactive structure discovery",
  year = "2020"
}
@article{belkin2019two,
  author = "Belkin, Mikhail and Hsu, Daniel and Xu, Ji",
  journal = "arXiv preprint arXiv:1903.07571",
  title = "Two models of double descent for weak features",
  year = "2019"
}
@inproceedings{xu2019number,
  author = "Xu, Ji and Hsu, Daniel",
  booktitle = "Advances in Neural Information Processing Systems 32",
  title = "On the number of variables to use in principal component regression",
  year = "2019"
}
@inproceedings{karamanolakis2019leveraging,
  author = "Karamanolakis, Giannis and Hsu, Daniel and Gravano, Luis",
  booktitle = "Conference on Empirical Methods in Natural Language Processing",
  title = "Leveraging just a few keywords for fine-grained aspect detection through weakly supervised co-training",
  year = "2019"
}
@inproceedings{lecuyer2019privacy,
  author = "Lecuyer, Mathias and Spahn, Riley and Vodrahalli, Kiran and Geambasu, Roxana and Hsu, Daniel",
  booktitle = "Twenty-Seventh ACM Symposium on Operating Systems Principles",
  title = "Privacy accounting and quality control in the Sage differentially private ML platform",
  year = "2019"
}
@article{ribli2019weak,
  author = "Ribli, Dezső and Pataki, Bálint Ármin and Zorrilla Matilla, José Manuel and Hsu, Daniel and Haiman, Zoltán and Csabai, István",
  journal = {Monthly Notices of the Royal Astronomical Society},
  title = "Weak lensing cosmology with convolutional neural networks on noisy data",
  volume = {490},
  number = {2},
  pages = {1843-1860},
  year = {2019}
}
@article{belkin2019reconciling,
  author = "Belkin, Mikhail and Hsu, Daniel and Ma, Siyuan and Mandal, Soumik",
  title = "Reconciling modern machine learning practice and the bias-variance trade-off",
  journal = "Proceedings of the National Academy of Sciences",
  volume = "116",
  number = "32",
  pages = "15849--15854",
  year = "2019"
}
@article{hsu2019mixing,
  author = {Hsu, Daniel and Kontorovich, Aryeh and Levin, David A. and Peres, Yuval and Szepesv{\'a}ri, Csaba and Wolfer, Geoffrey},
  title = {Mixing time estimation in reversible Markov chains from a single sample path},
  journal = {The Annals of Applied Probability},
  volume = {29},
  number = {4},
  pages = {2439--2480},
  year = {2019},
}
@article{liu2019using,
  author = "Liu, Chia-Hao and Tao, Yunzhe and Hsu, Daniel and Du, Qiang and Billinge, Simon J.L.",
  journal = "Acta Crystallographica Section A",
  title = "Using a machine learning approach to determine the space group of a structure from the atomic pair distribution function",
  year = "2019",
  volume = "75",
  number = "4",
  pages = "633--643",
}
@inproceedings{dasgupta2019teaching,
  author = "Dasgupta, Sanjoy and Hsu, Daniel and Poulis, Stefanos and Zhu, Xiaojin",
  booktitle = "Thirty-Sixth International Conference on Machine Learning",
  title = "Teaching a black-box learner",
  year = "2019"
}
@inproceedings{chen2019gradual,
  author = "Chen, Yucheng and Telgarsky, Matus and Zhang, Chao and Bailey, Bolton and Hsu, Daniel and Peng, Jian",
  booktitle = "Thirty-Sixth International Conference on Machine Learning",
  title = "A gradual, semi-discrete approach to generative network training via explicit Wasserstein minimization",
  year = "2019"
}
@inproceedings{lecuyer2019certified,
  author = "Lecuyer, Mathias and Atlidakis, Vaggelis and Geambasu, Roxana and Hsu, Daniel and Jana, Suman",
  booktitle = "IEEE Symposium on Security and Privacy",
  title = "Certified robustness to adversarial examples with differential privacy",
  year = "2019"
}
@inproceedings{derezinski2019correcting,
  author = "Dereziński, Michał and Warmuth, Manfred K. and Hsu, Daniel",
  booktitle = "Twenty-Second International Conference on Artificial Intelligence and Statistics",
  title = "Correcting the bias in least squares regression with volume-rescaled sampling",
  year = "2019"
}
@inproceedings{andoni2019attribute,
  author = "Andoni, Alexandr and Dudeja, Rishabh and Hsu, Daniel and Vodrahalli, Kiran",
  booktitle = "Thirtieth International Conference on Algorithmic Learning Theory",
  title = "Attribute-efficient learning of monomials over highly-correlated variables",
  year = "2019"
}
@inproceedings{belkin2018overfitting,
  author = "Belkin, Mikhail and Hsu, Daniel and Mitra, Partha",
  booktitle = "Advances in Neural Information Processing Systems 31",
  title = "Overfitting or perfect fitting? Risk bounds for classification and regression rules that interpolate",
  year = "2018"
}
@inproceedings{derezinski2018leveraged,
  author = "Dereziński, Michał and Warmuth, Manfred K. and Hsu, Daniel",
  booktitle = "Advances in Neural Information Processing Systems 31",
  title = "Leveraged volume sampling for linear regression",
  year = "2018"
}
@inproceedings{xu2018benefits,
  author = "Xu, Ji and Hsu, Daniel and Maleki, Arian",
  booktitle = "Advances in Neural Information Processing Systems 31",
  title = "Benefits of over-parameterization with EM",
  year = "2018"
}
@inproceedings{dudeja2018learning,
  author = "Dudeja, Rishabh and Hsu, Daniel",
  booktitle = "Thirty-First Annual Conference on Learning Theory",
  title = "Learning single-index models in Gaussian space",
  year = "2018"
}
@article{gupta2018nongaussian,
  title = {Non-Gaussian information from weak lensing data via deep learning},
  author = {Gupta, Arushi and Zorrilla Matilla, Jos\'e Manuel and Hsu, Daniel and Haiman, Zolt\'an},
  journal = {Phys. Rev. D},
  volume = {97},
  issue = {10},
  pages = {103515},
  numpages = {15},
  year = {2018},
  month = {May},
  publisher = {American Physical Society},
  doi = {10.1103/PhysRevD.97.103515},
  url = {https://link.aps.org/doi/10.1103/PhysRevD.97.103515}
}
@article{effland2018discovering,
  author = "Effland, Thomas and Lawson, Anna and Balter, Sharon and Devinney, Katelynn and Reddy, Vasudha and Waechter, {HaeNa} and Gravano, Luis and Hsu, Daniel",
  journal = "Journal of the American Medical Informatics Association",
  title = "Discovering foodborne illness in online restaurant reviews",
  volume = "25",
  number = "12",
  pages = "1586--1592",
  year = "2018"
}
@article{andoni2017coding,
  author = "Andoni, Alexandr and Ghaderi, Javad and Hsu, Daniel and Rubenstein, Dan and Weinstein, Omri",
  journal = "arXiv preprint arXiv:1707.04875",
  title = "Coding sets with asymmetric information",
  year = "2017"
}
@inproceedings{hsu2017linear,
  author = "Hsu, Daniel and Shi, Kevin and Sun, Xiaorui",
  booktitle = "Advances in Neural Information Processing Systems 30",
  title = "Linear regression without correspondence",
  year = "2017"
}
@article{kandula2017subregional,
  author = "Kandula, Sasikiran and Hsu, Daniel and Shaman, Jeffrey",
  journal = "Journal of Medical Internet Research",
  title = "Subregional nowcasts of seasonal influenza using search trends",
  volume = "19",
  number = "11",
  pages = "e370",
  year = "2017"
}
@article{mu2017greedy,
  author = "Mu, Cun and Hsu, Daniel and Goldfarb, Donald",
  journal = "SIAM Journal on Matrix Analysis and Applications",
  number = "4",
  pages = "1210--1226",
  title = "Greedy approaches to symmetric orthogonal tensor decomposition",
  volume = "38",
  year = "2017"
}
@inproceedings{gupta2017parameter,
  author = "Gupta, Arushi and Hsu, Daniel",
  booktitle = "Twenty-Eighth International Conference on Algorithmic Learning Theory",
  title = "Parameter identification in Markov chain choice models",
  year = "2017"
}
@inproceedings{andoni2017correspondence,
  author = "Andoni, Alexandr and Hsu, Daniel and Shi, Kevin and Sun, Xiaorui",
  booktitle = "Thirtieth Annual Conference on Learning Theory",
  title = "Correspondence retrieval",
  year = "2017"
}
@inproceedings{tramer2017fairtest,
  author = "Tramer, Florian and Atlidakis, Vaggelis and Geambasu, Roxana and Hsu, Daniel and Hubaux, Jean-Pierre and Humbert, Mathias and Juels, Ari and Lin, Huang",
  booktitle = "Second IEEE European Symposium on Security and Privacy",
  title = "FairTest: discovering unwarranted associations in data-driven applications",
  year = "2017"
}
@article{dicker2017kernel,
  author = "Dicker, Lee H. and Foster, Dean P. and Hsu, Daniel",
  journal = "Electronic Journal of Statistics",
  number = "1",
  pages = "1022--1047",
  title = "Kernel ridge vs. principal component regression: minimax bounds and the qualification of regularization operators",
  volume = "1",
  year = "2017"
}
@article{hsu2016greedy,
  author = "Hsu, Daniel and Telgarsky, Matus",
  journal = "arXiv preprint arXiv:1607.06203",
  title = "Greedy bi-criteria approximations for k-medians and k-means",
  year = "2016"
}
@inproceedings{beygelzimer2016search,
  author = "Beygelzimer, Alina and Hsu, Daniel and Langford, John and Zhang, Chicheng",
  booktitle = "Advances in Neural Information Processing Systems 29",
  title = "Search improves label for active learning",
  year = "2016"
}
@inproceedings{xu2016global,
  author = "Xu, Ji and Hsu, Daniel and Maleki, Arian",
  booktitle = "Advances in Neural Information Processing Systems 29",
  title = "Global analysis of Expectation Maximization for mixtures of two Gaussians",
  year = "2016"
}
@article{zorrilla2016dark,
  author = "Zorrilla Matilla, Jose Manuel and Haiman, Zoltan and Hsu, Daniel and Gupta, Arushi and Petri, Andrea",
  issue = "8",
  journal = "Phys. Rev. D",
  month = "Oct",
  pages = "083506",
  title = "Do dark matter halos explain lensing peaks?",
  volume = "94",
  year = "2016"
}
@article{stratos2016unsupervised,
  author = "Stratos, Karl and Collins, Michael and Hsu, Daniel",
  journal = "Transactions of the Association for Computational Linguistics",
  pages = "245--257",
  title = "Unsupervised part-of-speech tagging with anchor hidden Markov models",
  volume = "4",
  year = "2016"
}
@inproceedings{may2016compact,
  author = "May, Avner and Collins, Michael and Hsu, Daniel and Kingsbury, Brian",
  booktitle = "Forty-First IEEE International Conference on Acoustics, Speech and Signal Processing",
  title = "Compact kernel models for acoustic modeling via random feature selection",
  year = "2016"
}
@article{hsu2016loss,
  author = "Hsu, Daniel and Sabato, Sivan",
  journal = "Journal of Machine Learning Research",
  number = "18",
  pages = "1--40",
  title = "Loss minimization and parameter estimation with heavy tails",
  volume = "17",
  year = "2016"
}
@inproceedings{hsu2015mixing,
  author = "Hsu, Daniel and Kontorovich, Aryeh and Szepesvari, Csaba",
  booktitle = "Advances in Neural Information Processing Systems 28",
  title = "Mixing time estimation in reversible Markov chains from a single sample path",
  year = "2015"
}
@inproceedings{huang2015efficient,
  author = "Huang, Tzu-Kuo and Agarwal, Alekh and Hsu, Daniel and Langford, John and E. Schapire, Robert",
  booktitle = "Advances in Neural Information Processing Systems 28",
  title = "Efficient and parsimonious agnostic active learning",
  year = "2015"
}
@inproceedings{lecuyer2015sunlight,
  author = "Lecuyer, Mathias and Spahn, Riley and Spiliopoulos, Yannis and Chaintreau, Augustin and Geambasu, Roxana and Hsu, Daniel",
  booktitle = "Twenty-Second ACM Conference on Computer and Communications Security",
  title = "Sunlight: fine-grained targeting detection at scale with statistical confidence",
  year = "2015"
}
@inproceedings{stratos2015modelbased,
  author = "Stratos, Karl and Collins, Michael and Hsu, Daniel",
  booktitle = "Fifty-Third Annual Meeting of the Association for Computational Linguistics",
  title = "Model-based word embeddings from decompositions of count matrices",
  year = "2015"
}
@article{anandkumar2015when,
  author = "Anandkumar, Anima and Hsu, Daniel and Janzamin, Majid and Kakade, Sham M.",
  journal = "Journal of Machine Learning Research",
  number = "Dec",
  pages = "2643--2694",
  title = "When are overcomplete topic models identifiable? Uniqueness of tensor Tucker decompositions with structured sparsity",
  volume = "16",
  year = "2015"
}
@article{mu2015successive,
  author = "Mu, Cun and Hsu, Daniel and Goldfarb, Donald",
  journal = "SIAM Journal on Matrix Analysis and Applications",
  number = "4",
  pages = "1638--1659",
  title = "Successive rank-one approximations for nearly orthogonally decomposable symmetric tensors",
  volume = "36",
  year = "2015"
}
@article{anandkumar2015spectral,
  author = "Anandkumar, Anima and Foster, Dean P. and Hsu, Daniel and Kakade, Sham M. and Liu, Yi-Kai",
  journal = "Algorithmica",
  number = "1",
  pages = "193--214",
  title = "A spectral algorithm for latent Dirichlet allocation",
  volume = "72",
  year = "2015"
}
@inproceedings{subakan2015method,
  author = "Subakan, Yusuf Cem and Traa, Johannes and Smaragdis, Paris and Hsu, Daniel",
  booktitle = "IEEE Workshop on Applications of Signal Processing to Audio and Acoustics",
  title = "Method of moments learning for left-to-right hidden Markov models",
  year = "2015"
}
@article{sabato2015learning,
  author = "Sabato, Sivan and Shalev-Shwartz, Shai and Srebro, Nathan and Hsu, Daniel and Zhang, Tong",
  journal = "Journal of Machine Learning Research",
  number = "Jul",
  pages = "1275--1304",
  title = "Learning sparse low-threshold linear classifiers",
  volume = "16",
  year = "2015"
}
@inproceedings{agarwal2014scalable,
  author = "Agarwal, Alekh and Beygelzimer, Alina and Hsu, Daniel and Langford, John and Telgarsky, Matus",
  booktitle = "Advances in Neural Information Processing Systems 27",
  title = "Scalable nonlinear learning with adaptive polynomial expansions",
  year = "2014"
}
@inproceedings{chaudhuri2014large,
  author = "Chaudhuri, Kamalika and Hsu, Daniel and Song, Shuang",
  booktitle = "Advances in Neural Information Processing Systems 27",
  title = "The large margin mechanism for differentially private maximization",
  year = "2014"
}
@inproceedings{stratos2014spectral,
  author = "Stratos, Karl and Kim, Do-kyum and Collins, Michael and Hsu, Daniel",
  booktitle = "Thirtieth Conference on Uncertainty in Artificial Intelligence",
  title = "A spectral algorithm for learning class-based $n$-gram models of natural language",
  year = "2014"
}
@inproceedings{agarwal2014taming,
  author = "Agarwal, Alekh and Hsu, Daniel and Kale, Satyen and Langford, John and Li, Lihong and Schapire, Robert E.",
  booktitle = "Thirty-First International Conference on Machine Learning",
  title = "Taming the monster: a fast and simple algorithm for contextual bandits",
  year = "2014"
}
@inproceedings{hsu2014heavytailed,
  author = "Hsu, Daniel and Sabato, Sivan",
  booktitle = "Thirty-First International Conference on Machine Learning",
  title = "Heavy-tailed regression with a generalized median-of-means",
  year = "2014"
}
@article{anandkumar2014tensor,
  author = "Anandkumar, Anima and Ge, Rong and Hsu, Daniel and Kakade, Sham M. and Telgarsky, Matus",
  journal = "Journal of Machine Learning Research",
  number = "Aug",
  pages = "2773--2831",
  title = "Tensor decompositions for learning latent variable models",
  volume = "15",
  year = "2014"
}
@article{hsu2014random,
  author = "Hsu, Daniel and Kakade, Sham M. and Zhang, Tong",
  journal = "Foundations of Computational Mathematics",
  number = "3",
  pages = "569--600",
  title = "Random design analysis of ridge regression",
  volume = "14",
  year = "2014"
}
@article{anandkumar2014mixed,
  author = "Anandkumar, Anima and Ge, Rong and Hsu, Daniel and Kakade, Sham M.",
  journal = "Journal of Machine Learning Research",
  number = "Jun",
  pages = "2239--2312",
  title = "A tensor approach to learning mixed membership community models",
  volume = "15",
  year = "2014"
}
@inproceedings{anandkumar2013when,
  author = "Anandkumar, Anima and Hsu, Daniel and Janzamin, Majid and Kakade, Sham M.",
  booktitle = "Advances in Neural Information Processing Systems 26",
  title = "When are overcomplete topic models identifiable? Uniqueness of tensor Tucker decompositions with structured sparsity",
  year = "2013"
}
@inproceedings{zou2013contrastive,
  author = "Zou, James and Hsu, Daniel and Parkes, David and Adams, Ryan P.",
  booktitle = "Advances in Neural Information Processing Systems 26",
  title = "Contrastive learning using spectral methods",
  year = "2013"
}
@inproceedings{anandkumar2013mixed,
  author = "Anandkumar, Anima and Ge, Rong and Hsu, Daniel and Kakade, Sham M.",
  booktitle = "Twenty-Sixth Annual Conference on Learning Theory",
  title = "A tensor spectral approach to learning mixed membership community models",
  year = "2013"
}
@inproceedings{anandkumar2013learning,
  author = "Anandkumar, Anima and Hsu, Daniel and Javanmard, Adel and Kakade, Sham M.",
  booktitle = "Thirtieth International Conference on Machine Learning",
  title = "Learning linear {Bayesian} networks with latent variables",
  year = "2013"
}
@inproceedings{hsu2013learning,
  author = "Hsu, Daniel and Kakade, Sham M.",
  booktitle = "Fourth Innovations in Theoretical Computer Science",
  title = "Learning mixtures of spherical Gaussians: moment methods and spectral decompositions",
  year = "2013"
}
@article{agarwal2013stochastic,
  author = "Agarwal, Alekh and Foster, Dean P. and Hsu, Daniel and Kakade, Sham M. and Rakhlin, Alexander",
  journal = "SIAM Journal on Optimization",
  number = "1",
  pages = "213--240",
  title = "Stochastic convex optimization with bandit feedback",
  volume = "23",
  year = "2013"
}
@inproceedings{anandkumar2012spectral,
  author = {Anandkumar, Anima and Foster, Dean P. and Hsu, Daniel and Kakade, Sham M. and Liu, Yi-Kai},
  booktitle = {Advances in Neural Information Processing Systems 25},
  title = {A spectral algorithm for latent Dirichlet allocation},
  year = {2012}
}
@inproceedings{anandkumar2012learning,
  author = "Anandkumar, Anima and Hsu, Daniel and Huang, Furong and Kakade, Sham M.",
  booktitle = "Advances in Neural Information Processing Systems 25",
  title = "Learning mixtures of tree graphical models",
  year = "2012"
}
@inproceedings{hsu2012identifiability,
  author = "Hsu, Daniel and Kakade, Sham M. and Liang, Percy",
  booktitle = "Advances in Neural Information Processing Systems 25",
  title = "Identifiability and unmixing of latent parse trees",
  year = "2012"
}
@inproceedings{hsu2012random,
  author = "Hsu, Daniel and Kakade, Sham M. and Zhang, Tong",
  booktitle = "Twenty-Fifth Annual Conference on Learning Theory",
  title = "Random design analysis of ridge regression",
  year = "2012"
}
@inproceedings{anandkumar2012method,
  author = "Anandkumar, Anima and Hsu, Daniel and Kakade, Sham M.",
  booktitle = "Twenty-Fifth Annual Conference on Learning Theory",
  title = "A method of moments for mixture models and hidden Markov models",
  year = "2012"
}
@inproceedings{chaudhuri2012convergence,
  author = "Chaudhuri, Kamalika and Hsu, Daniel",
  booktitle = "Twenty-Ninth International Conference on Machine Learning",
  title = "Convergence rates for differentially private statistical estimation",
  year = "2012"
}
@article{hsu2012tail,
  author = "Hsu, Daniel and Kakade, Sham M. and Zhang, Tong",
  journal = "Electronic Communications in Probability",
  number = "14",
  pages = "1--13",
  title = "Tail inequalities for sums of random matrices that depend on the intrinsic dimension",
  volume = "17",
  year = "2012"
}
@article{hsu2012spectral,
  author = "Hsu, Daniel and Kakade, Sham M. and Zhang, Tong",
  journal = "Journal of Computer and System Sciences",
  number = "5",
  pages = "1460--1480",
  title = "A spectral algorithm for learning hidden Markov models",
  volume = "78",
  year = "2012"
}
@article{hsu2012inequality,
  author = "Hsu, Daniel and Kakade, Sham M. and Zhang, Tong",
  journal = "Electronic Communications in Probability",
  number = "52",
  pages = "1--6",
  title = "A tail inequality for quadratic forms of subgaussian random vectors",
  volume = "17",
  year = "2012"
}
@inproceedings{agarwal2011stochastic,
  author = "Agarwal, Alekh and Foster, Dean P. and Hsu, Daniel and Kakade, Sham M. and Rakhlin, Alexander",
  booktitle = "Advances in Neural Information Processing Systems 24",
  title = "Stochastic convex optimization with bandit feedback",
  year = "2011"
}
@inproceedings{anandkumar2011spectral,
  author = "Anandkumar, Anima and Chaudhuri, Kamalika and Hsu, Daniel and Kakade, Sham M. and Song, Le and Zhang, Tong",
  booktitle = "Advances in Neural Information Processing Systems 24",
  title = "Spectral methods for learning multivariate latent tree structure",
  year = "2011"
}
@inproceedings{chaudhuri2011sample,
  author = "Chaudhuri, Kamalika and Hsu, Daniel",
  booktitle = "Twenty-Fourth Annual Conference on Learning Theory",
  title = "Sample complexity bounds for differentially private learning",
  year = "2011"
}
@inproceedings{dudik2011efficient,
  author = "Dudik, Miroslav and Hsu, Daniel and Kale, Satyen and Karampatziakis, Nikos and Langford, John and Reyzin, Lev and Zhang, Tong",
  booktitle = "Twenty-Seventh Conference on Uncertainty in Artificial Intelligence",
  title = "Efficient optimal learning for contextual bandits",
  year = "2011"
}
@article{hsu2011robust,
  author = "Hsu, Daniel and Kakade, Sham M. and Zhang, Tong",
  journal = "IEEE Transactions on Information Theory",
  number = "11",
  pages = "7221--7234",
  title = "Robust matrix decomposition with sparse corruptions",
  volume = "57",
  year = "2011"
}
@inproceedings{beygelzimer2010agnostic,
  author = "Beygelzimer, Alina and Hsu, Daniel and Langford, John and Zhang, Tong",
  booktitle = "Advances in Neural Information Processing Systems 23",
  title = "Agnostic active learning without constraints",
  year = "2010"
}
@inproceedings{chaudhuri2010online,
  author = "Chaudhuri, Kamalika and Freund, Yoav and Hsu, Daniel",
  booktitle = "Twenty-Sixth Conference on Uncertainty in Artificial Intelligence",
  title = "An online learning-based framework for tracking",
  year = "2010"
}
@phdthesis{hsu2010algorithms,
  author = "Hsu, Daniel",
  school = "University of California, San Diego",
  title = "Algorithms for active learning",
  year = "2010"
}
@inproceedings{chaudhuri2009parameterfree,
  author = "Chaudhuri, Kamalika and Freund, Yoav and Hsu, Daniel",
  booktitle = "Advances in Neural Information Processing Systems 22",
  title = "A parameter-free hedging algorithm",
  year = "2009"
}
@inproceedings{hsu2009multilabel,
  author = "Hsu, Daniel and Kakade, Sham M. and Langford, John and Zhang, Tong",
  booktitle = "Advances in Neural Information Processing Systems 22",
  title = "Multi-label prediction via compressed sensing",
  year = "2009"
}
@inproceedings{hsu2009spectral,
  author = "Hsu, Daniel and Kakade, Sham M. and Zhang, Tong",
  booktitle = "Twenty-Second Annual Conference on Learning Theory",
  title = "A spectral algorithm for learning hidden Markov models",
  year = "2009"
}
@inproceedings{dasgupta2008hierarchical,
  author = "Dasgupta, Sanjoy and Hsu, Daniel",
  booktitle = "Twenty-Fifth International Conference on Machine Learning",
  title = "Hierarchical sampling for active learning",
  year = "2008"
}
@inproceedings{dasgupta2007general,
  author = "Dasgupta, Sanjoy and Hsu, Daniel and Monteleoni, Claire",
  booktitle = "Advances in Neural Information Processing Systems 20",
  title = "A general agnostic active learning algorithm",
  year = "2007"
}
@inproceedings{dasgupta2007online,
  author = "Dasgupta, Sanjoy and Hsu, Daniel",
  booktitle = "Twentieth Annual Conference on Learning Theory",
  title = "On-line estimation with the multivariate Gaussian distribution",
  year = "2007"
}
@inproceedings{dasgupta2006concentration,
  author = "Dasgupta, Sanjoy and Hsu, Daniel and Verma, Nakul",
  booktitle = "Twenty-Second Conference on Uncertainty in Artificial Intelligence",
  title = "A concentration theorem for projections",
  year = "2006"
}