@article{karamanolakis2024interactive,
author = "Karamanolakis, Giannis and Hsu, Daniel and Gravano, Luis",
journal = "Transactions of the Association for Computational Linguistics",
pages = "1441--1459",
title = "Interactive machine teaching by labeling rules and instances",
volume = "12",
year = "2024"
}
@inproceedings{deng2024groupwise,
author = "Deng, Samuel and Hsu, Daniel and Liu, Jingwen",
booktitle = "Advances in Neural Information Processing Systems 37",
title = "Group-wise oracle-efficient algorithms for online multi-group learning",
year = "2024"
}
@article{sanford2024one,
author = "Sanford, Clayton and Hsu, Daniel and Telgarsky, Matus",
journal = "arXiv preprint arXiv:2408.14332",
title = "One-layer transformers fail to solve the induction heads task",
year = "2024"
}
@inproceedings{wang2024transformers,
author = "Wang, Zixuan and Wei, Stanley and Hsu, Daniel and Lee, Jason D.",
booktitle = "Forty-First International Conference on Machine Learning",
title = "Transformers provably learn sparse token selection while fully-connected nets cannot",
year = "2024"
}
@inproceedings{sanford2024transformers,
author = "Sanford, Clayton and Hsu, Daniel and Telgarsky, Matus",
booktitle = "Forty-First International Conference on Machine Learning",
title = "Transformers, parallel computation, and logarithmic depth",
year = "2024"
}
@inproceedings{deng2024multi,
author = "Deng, Samuel and Hsu, Daniel",
booktitle = "Forty-First International Conference on Machine Learning",
title = "Multi-group learning for hierarchical groups",
year = "2024"
}
@inproceedings{hsu2024sample,
author = "Hsu, Daniel and Mazumdar, Arya",
booktitle = "Thirty-Seventh Annual Conference on Learning Theory",
title = "On the sample complexity of parameter estimation in logistic regression with normal design",
year = "2024"
}
@inproceedings{hsu2024auditing,
author = "Hsu, Daniel and Huang, Jizhou and Juba, Brendan",
booktitle = "Fifth Symposium on Foundations of Responsible Computing",
title = "Distribution-specific auditing for subgroup fairness",
year = "2024"
}
@article{dudeja2024statistical,
author = "Dudeja, Rishabh and Hsu, Daniel",
journal = "The Annals of Statistics",
title = "Statistical-computational trade-offs in tensor {PCA} and related problems via communication complexity",
volume = "52",
number = "1",
pages = "131--156",
year = "2024"
}
@article{yuan2023efficient,
author = "Yuan, Gan and Xu, Mingyue and Kpotufe, Samory and Hsu, Daniel",
journal = "arXiv preprint arXiv:2312.15469",
title = "Efficient estimation of the central mean subspace via smoothed gradient outer products",
year = "2023"
}
@inproceedings{sanford2023representational,
author = "Sanford, Clayton and Hsu, Daniel and Telgarsky, Matus",
booktitle = "Advances in Neural Information Processing Systems 36",
title = "Representational strengths and limitations of transformers",
year = "2023"
}
@inproceedings{ardeshir2023intrinsic,
author = "Ardeshir, Navid and Hsu, Daniel and Sanford, Clayton",
booktitle = "Thirty-Sixth Annual Conference on Learning Theory",
title = "Intrinsic dimensionality and generalization properties of the $\mathcal{R}$-norm inductive bias",
year = "2023"
}
@inproceedings{liu2022masked,
author = "Liu, Bingbin and Hsu, Daniel and Ravikumar, Pradeep and Risteski, Andrej",
booktitle = "Advances in Neural Information Processing Systems 35",
title = "Masked prediction: a parameter identifiability view",
year = "2022"
}
@article{derezinski2022unbiased,
author = "Dereziński, Michał and Warmuth, Manfred K. and Hsu, Daniel",
journal = "Journal of Machine Learning Research",
volume = "23",
number = "167",
pages = "1--46",
title = "Unbiased estimators for random design regression",
year = "2022"
}
@inproceedings{hsu2022nearoptimal,
author = "Hsu, Daniel and Sanford, Clayton and Servedio, Rocco A. and Vlatakis-Gkaragkounis, Emmanouil-Vasileios",
booktitle = "Thirty-Fifth Annual Conference on Learning Theory",
title = "Near-optimal statistical query lower bounds for agnostically learning intersections of halfspaces with {Gaussian} marginals",
year = "2022"
}
@inproceedings{deng2022learning,
title="Learning tensor representations for meta-learning",
author="Deng, Samuel and Guo, Yilin and Hsu, Daniel and Mandal, Debmalya",
booktitle = "Twenty-Fifth International Conference on Artificial Intelligence and Statistics",
year="2022"
}
@inproceedings{tosh2022simple,
author = "Tosh, Christopher and Hsu, Daniel",
booktitle = "Thirty-Ninth International Conference on Machine Learning",
title = "Simple and near-optimal algorithms for hidden stratification and multi-group learning",
year = "2022"
}
@article{tosh2021contrastive,
author = "Tosh, Christopher and Krishnamurthy, Akshay and Hsu, Daniel",
journal = "Journal of Machine Learning Research",
title = "Contrastive estimation reveals topic posterior information to linear models",
number = "281",
volume = "22",
pages = "1-31",
year = "2021"
}
@inproceedings{simchowitz2021bayesian,
author = "Simchowitz, Max and Tosh, Christopher and Krishnamurthy, Akshay and Hsu, Daniel and Lykouris, Thodoris and Dudík, Miroslav and Schapire, Robert E.",
booktitle = "Advances in Neural Information Processing Systems 34",
title = "Bayesian decision-making under misspecified priors with applications to meta-learning",
year = "2021"
}
@inproceedings{ardeshir2021support,
author = "Ardeshir, Navid and Sanford, Clayton and Hsu, Daniel",
booktitle = "Advances in Neural Information Processing Systems 34",
title = "Support vector machines and linear regression coincide with very high-dimensional features",
year = "2021"
}
@article{muthukumar2021classification,
author = "Muthukumar, Vidya and Narang, Adhyyan and Subramanian, Vignesh and Belkin, Mikhail and Hsu, Daniel and Sahai, Anant",
journal = "Journal of Machine Learning Research",
title = "Classification vs regression in overparameterized regimes: Does the loss function matter?",
number = "222",
volume = "22",
pages = "1-69",
year = "2021"
}
@inproceedings{hsu2021approximation,
author = "Hsu, Daniel and Sanford, Clayton and Servedio, Rocco A. and Vlatakis-Gkaragkounis, Emmanouil-Vasileios",
title = "On the approximation power of two-layer networks of random ReLUs",
booktitle = "Thirty-Fourth Annual Conference on Learning Theory",
year = "2021"
}
@article{dudeja2021statistical,
author = "Dudeja, Rishabh and Hsu, Daniel",
journal = "Journal of Machine Learning Research",
volume = "15",
number = "83",
pages = "1--51",
title = "Statistical query lower bounds for tensor PCA",
year = "2021"
}
@inproceedings{hsu2021generalization,
author = "Hsu, Daniel and Ji, Ziwei and Telgarsky, Matus and Wang, Lan",
title = "Generalization bounds via distillation",
booktitle = "Ninth International Conference on Learning Representations",
year = "2021"
}
@inproceedings{hsu2021proliferation,
author = "Hsu, Daniel and Muthukumar, Vidya and Xu, Ji",
booktitle = "Twenty-Fourth International Conference on Artificial Intelligence and Statistics",
title = "On the proliferation of support vectors in high dimensions",
year = "2021"
}
@inproceedings{tosh2021redundancy,
author = "Tosh, Christopher and Krishnamurthy, Akshay and Hsu, Daniel",
booktitle = "Thirty-Second International Conference on Algorithmic Learning Theory",
title = "Contrastive learning, multi-view redundancy, and linear models",
year = "2021"
}
@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{zorrilla2020interpreting,
title = "Interpreting deep learning models for weak lensing",
author = "Matilla, Jos\'e Manuel Zorrilla and Sharma, Manasi and Hsu, Daniel and Haiman, Zolt\'an",
journal = "Phys. Rev. D",
volume = "102",
issue = "12",
pages = "123506",
numpages = "13",
year = "2020",
month = "Dec",
}
@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"
}
@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{belkin2020two,
author = "Belkin, Mikhail and Hsu, Daniel and Xu, Ji",
journal = "SIAM Journal on Mathematics of Data Science",
title = "Two models of double descent for weak features",
volume = "2",
number = "4",
pages = "1167-1180",
year = "2020"
}
@article{may2019kernel,
author = "May, Avner and Garakani, Alireza Bagheri and Lu, Zhiyun and Guo, Dong and Liu, Kuan and Bellet, Aur{\'e}lien and Fan, Linxi and Collins, Michael and Hsu, Daniel and Kingsbury, Brian",
journal = "Journal of Machine Learning Research",
volume = "20",
number = "59",
pages = "1--36",
title = "Kernel approximation methods for speech recognition",
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"
}
@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"
}
@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"
}