Many of my papers are available on arXiv and linked from dblp and Google Scholar.
Statistical-computational trade-offs in tensor PCA and related problems via communication complexity
The Annals of Statistics, 52(1):131-156, 2024.
[ local pdf file | external link | talk slides | aos link | bibtex ]
Transformers, parallel computation, and logarithmic depth
Preprint, 2024.
[ external link | bibtex ]
Multi-group learning for hierarchical groups
Preprint, 2024.
[ external link | bibtex ]
On the sample complexity of parameter estimation in logistic regression with normal design
Preprint, 2024.
[ external link | bibtex ]
Efficient estimation of the central mean subspace via smoothed gradient outer products
Preprint, 2023.
[ external link | bibtex ]
Representational strengths and limitations of transformers
In Advances in Neural Information Processing Systems 36, 2023.
[ external link | talk slides | bibtex ]
Intrinsic dimensionality and generalization properties of the \(\mathcal{R}\)-norm inductive bias
In Thirty-Sixth Annual Conference on Learning Theory, 2023.
[ external link | bibtex ]
Masked prediction: a parameter identifiability view
In Advances in Neural Information Processing Systems 35, 2022.
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Unbiased estimators for random design regression
Journal of Machine Learning Research, 23(167):1-46, 2022.
[ external link | arxiv link | bibtex ]
Near-optimal statistical query lower bounds for agnostically learning intersections of halfspaces with Gaussian marginals
In Thirty-Fifth Annual Conference on Learning Theory, 2022.
[ external link | pmlr link | bibtex ]
Learning tensor representations for meta-learning
In Twenty-Fifth International Conference on Artificial Intelligence and Statistics, 2022.
[ external link | bibtex ]
Simple and near-optimal algorithms for hidden stratification and multi-group learning
In Thirty-Ninth International Conference on Machine Learning, 2022.
[ external link | talk slides | errata | arxiv link | bibtex ]
Contrastive estimation reveals topic posterior information to linear models
Journal of Machine Learning Research, 22(281):1-31, 2021.
[ external link | talk slides | bibtex ]
Bayesian decision-making under misspecified priors with applications to meta-learning
In Advances in Neural Information Processing Systems 34, 2021.
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Support vector machines and linear regression coincide with very high-dimensional features
In Advances in Neural Information Processing Systems 34, 2021.
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Classification vs regression in overparameterized regimes: Does the loss function matter?
Journal of Machine Learning Research, 22(222):1-69, 2021.
[ external link | arxiv link | bibtex ]
On the approximation power of two-layer networks of random ReLUs
In Thirty-Fourth Annual Conference on Learning Theory, 2021.
[ external link | talk slides | note about kernels | pmlr link | blog post | bibtex ]
Statistical query lower bounds for tensor PCA
Journal of Machine Learning Research, 22(83):1-51, 2021.
[ external link | jmlr link | bibtex ]
Generalization bounds via distillation
In Ninth International Conference on Learning Representations, 2021.
[ external link | bibtex ]
On the proliferation of support vectors in high dimensions
In Twenty-Fourth International Conference on Artificial Intelligence and Statistics, 2021.
[ external link | reviews | response | pmlr link | bibtex ]
Contrastive learning, multi-view redundancy, and linear models
In Thirty-Second International Conference on Algorithmic Learning Theory, 2021.
[ external link | pmlr link | bibtex ]
Cross-lingual text classification with minimal resources by transferring a sparse teacher
In Conference on Empirical Methods in Natural Language Processing: Findings, 2020.
[ external link | aclweb link | bibtex ]
Interpreting deep learning models for weak lensing
Phys. Rev. D, 102:123506, Dec 2020.
[ external link | aps link | bibtex ]
Ensuring fairness beyond the training data
In Advances in Neural Information Processing Systems 33, 2020.
[ external link | bibtex ]
Diameter-based interactive structure discovery
In Twenty-Third International Conference on Artificial Intelligence and Statistics, 2020.
[ external link | pmlr link | bibtex ]
Two models of double descent for weak features
SIAM Journal on Mathematics of Data Science, 2(4):1167–1180, 2020.
[ external link | arxiv link | bibtex ]
Kernel approximation methods for speech recognition
Journal of Machine Learning Research, 20(59):1-36, 2019.
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On the number of variables to use in principal component regression
In Advances in Neural Information Processing Systems 32, 2019.
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Leveraging just a few keywords for fine-grained aspect detection through weakly supervised co-training
In Conference on Empirical Methods in Natural Language Processing, 2019.
[ external link | talk slides | bibtex ]
Privacy accounting and quality control in the Sage differentially private ML platform
In Twenty-Seventh ACM Symposium on Operating Systems Principles, 2019.
[ external link | bibtex ]
Weak lensing cosmology with convolutional neural networks on noisy data
Monthly Notices of the Royal Astronomical Society, 490(2):1843–1860, 2019.
[ external link | arxiv link | bibtex ]
Reconciling modern machine learning practice and the bias-variance trade-off
Proceedings of the National Academy of Sciences, 116(32):15849-15854, 2019.
[ local pdf file | pnas link | arxiv link | bibtex ]
Mixing time estimation in reversible Markov chains from a single sample path
The Annals of Applied Probability, 29(4):2439–2480, 2019.
[ local pdf file | aap link | bibtex ]
Using a machine learning approach to determine the space group of a structure from the atomic pair distribution function
Acta Crystallographica Section A, 75(4):633–643, 2019.
[ external link | arxiv | bibtex ]
Teaching a black-box learner
In Thirty-Sixth International Conference on Machine Learning, 2019.
[ local pdf file | pmlr link | bibtex ]
A gradual, semi-discrete approach to generative network training via explicit Wasserstein minimization
In Thirty-Sixth International Conference on Machine Learning, 2019.
[ external link | pmlr link | bibtex ]
Certified robustness to adversarial examples with differential privacy
In IEEE Symposium on Security and Privacy, 2019.
[ external link | bibtex ]
Correcting the bias in least squares regression with volume-rescaled sampling
In Twenty-Second International Conference on Artificial Intelligence and Statistics, 2019.
[ local pdf file | arxiv link | pmlr link | bibtex ]
Attribute-efficient learning of monomials over highly-correlated variables
In Thirtieth International Conference on Algorithmic Learning Theory, 2019.
[ local pdf file | bibtex ]
Overfitting or perfect fitting? Risk bounds for classification and regression rules that interpolate
In Advances in Neural Information Processing Systems 31, 2018.
[ local pdf file | external link | short version | talk slides | bibtex ]
Leveraged volume sampling for linear regression
In Advances in Neural Information Processing Systems 31, 2018.
[ local pdf file | external link | bibtex ]
Benefits of over-parameterization with EM
In Advances in Neural Information Processing Systems 31, 2018.
[ external link | bibtex ]
Learning single-index models in Gaussian space
In Thirty-First Annual Conference on Learning Theory, 2018.
[ local pdf file | pmlr link | bibtex ]
Non-Gaussian information from weak lensing data via deep learning
Phys. Rev. D, 97:103515, May 2018.
[ external link | aps link | bibtex ]
Discovering foodborne illness in online restaurant reviews
Journal of the American Medical Informatics Association, 25(12):1586-1592, 2018.
[ external link | bibtex ]
Coding sets with asymmetric information
Preprint, 2017.
[ external link | bibtex ]
Linear regression without correspondence
In Advances in Neural Information Processing Systems 30, 2017.
[ external link | talk slides | bibtex ]
Subregional nowcasts of seasonal influenza using search trends
Journal of Medical Internet Research, 19(11):e370, 2017.
[ external link | bibtex ]
Greedy approaches to symmetric orthogonal tensor decomposition
SIAM Journal on Matrix Analysis and Applications, 38(4):1210-1226, 2017.
[ local pdf file | arxiv link | siam link | bibtex ]
Parameter identification in Markov chain choice models
In Twenty-Eighth International Conference on Algorithmic Learning Theory, 2017.
[ external link | pmlr link | bibtex ]
Correspondence retrieval
In Thirtieth Annual Conference on Learning Theory, 2017.
[ local pdf file | talk slides | pmlr link | bibtex ]
FairTest: discovering unwarranted associations in data-driven applications
In Second IEEE European Symposium on Security and Privacy, 2017.
[ external link | slides from privacycon | bibtex ]
Kernel ridge vs. principal component regression: minimax bounds and the qualification of regularization operators
Electronic Journal of Statistics, 1(1):1022–1047, 2017.
[ local pdf file | ejs link | bibtex ]
Greedy bi-criteria approximations for \(k\)-medians and \(k\)-means
Preprint, 2016.
[ external link | bibtex ]
Search improves label for active learning
In Advances in Neural Information Processing Systems 29, 2016.
[ local pdf file | arxiv link | video advert | bibtex ]
Global analysis of Expectation Maximization for mixtures of two Gaussians
In Advances in Neural Information Processing Systems 29, 2016.
[ local pdf file | short version | summary | arxiv link | bibtex ]
Do dark matter halos explain lensing peaks?
Phys. Rev. D, 94:083506, Oct 2016.
[ external link | aps link | bibtex ]
Unsupervised part-of-speech tagging with anchor hidden Markov models
Transactions of the Association for Computational Linguistics, 4:245–257, 2016.
[ external link | bibtex ]
Compact kernel models for acoustic modeling via random feature selection
In Forty-First IEEE International Conference on Acoustics, Speech and Signal Processing, 2016.
[ external link | bibtex ]
Loss minimization and parameter estimation with heavy tails
Journal of Machine Learning Research, 17(18):1–40, 2016.
[ external link | slides for related talk | bibtex ]
Mixing time estimation in reversible Markov chains from a single sample path
In Advances in Neural Information Processing Systems 28, 2015.
[ external link | talk slides | bibtex ]
Efficient and parsimonious agnostic active learning
In Advances in Neural Information Processing Systems 28, 2015.
[ external link | bibtex ]
Sunlight: fine-grained targeting detection at scale with statistical confidence
In Twenty-Second ACM Conference on Computer and Communications Security, 2015.
[ local pdf file | project website | bibtex ]
Model-based word embeddings from decompositions of count matrices
In Fifty-Third Annual Meeting of the Association for Computational Linguistics, 2015.
[ local pdf file | acl link | bibtex ]
When are overcomplete topic models identifiable?
Journal of Machine Learning Research, 16(Dec):2643–2694, 2015.
[ external link | bibtex ]
Successive rank-one approximations for nearly orthogonally decomposable symmetric tensors
SIAM Journal on Matrix Analysis and Applications, 36(4):1638–1659, 2015.
[ external link | siam link | bibtex ]
A spectral algorithm for latent Dirichlet allocation
Algorithmica, 72(1):193–214, 2015.
[ local pdf file | springer link | bibtex ]
Learning sparse low-threshold linear classifiers
Journal of Machine Learning Research, 16(Jul):1275–1304, 2015.
[ external link | bibtex ]
Scalable nonlinear learning with adaptive polynomial expansions
In Advances in Neural Information Processing Systems 27, 2014.
[ external link | bibtex ]
The large margin mechanism for differentially private maximization
In Advances in Neural Information Processing Systems 27, 2014.
[ external link | bibtex ]
A spectral algorithm for learning class-based \(n\)-gram models of natural language
In Thirtieth Conference on Uncertainty in Artificial Intelligence, 2014.
[ local pdf file | auai link | code by Karl | more code by Karl | bibtex ]
Taming the monster: a fast and simple algorithm for contextual bandits
In Thirty-First International Conference on Machine Learning, 2014.
[ local pdf file | talk slides | arxiv link | bibtex ]
Heavy-tailed regression with a generalized median-of-means
In Thirty-First International Conference on Machine Learning, 2014.
[ external link | arxiv link | bibtex ]
Tensor decompositions for learning latent variable models
Journal of Machine Learning Research, 15(Aug):2773–2831, 2014.
[ local pdf file | tutorial slides | jmlr link | bibtex ]
Random design analysis of ridge regression
Foundations of Computational Mathematics, 14(3):569–600, 2014.
[ local pdf file | springer link | arxiv link | bibtex ]
A tensor approach to learning mixed membership community models
Journal of Machine Learning Research, 15(Jun):2239–2312, 2014.
[ external link | arxiv link | bibtex ]
When are overcomplete topic models identifiable?
In Advances in Neural Information Processing Systems 26, 2013.
[ external link | bibtex ]
Contrastive learning using spectral methods
In Advances in Neural Information Processing Systems 26, 2013.
[ local pdf file | bibtex ]
A tensor spectral approach to learning mixed membership community models
In Twenty-Sixth Annual Conference on Learning Theory, 2013.
[ external link | journal version with better title | arxiv link | bibtex ]
Learning linear Bayesian networks with latent variables
In Thirtieth International Conference on Machine Learning, 2013.
[ local pdf file | pmlr link | bibtex ]
Learning mixtures of spherical Gaussians: moment methods and spectral decompositions
In Fourth Innovations in Theoretical Computer Science, 2013.
[ local pdf file | talk slides | arxiv link | video advert | bibtex ]
Stochastic convex optimization with bandit feedback
SIAM Journal on Optimization, 23(1):213–240, 2013.
[ local pdf file | arxiv link | siam link | bibtex ]
A spectral algorithm for latent Dirichlet allocation
In Advances in Neural Information Processing Systems 25, 2012.
[ external link | journal version | springer link | bibtex ]
Learning mixtures of tree graphical models
In Advances in Neural Information Processing Systems 25, 2012.
[ external link | bibtex ]
Identifiability and unmixing of latent parse trees
In Advances in Neural Information Processing Systems 25, 2012.
[ local pdf file | arxiv link | bibtex ]
Random design analysis of ridge regression
In Twenty-Fifth Annual Conference on Learning Theory, 2012.
[ external link | journal version | arxiv link | bibtex ]
A method of moments for mixture models and hidden Markov models
In Twenty-Fifth Annual Conference on Learning Theory, 2012.
[ external link | talk slides | slides for related talk | pmlr link | bibtex ]
Convergence rates for differentially private statistical estimation
In Twenty-Ninth International Conference on Machine Learning, 2012.
[ local pdf file | bibtex ]
Tail inequalities for sums of random matrices that depend on the intrinsic dimension
Electronic Communications in Probability, 17(14):1–13, 2012.
[ local pdf file | errata | ecp link | bibtex ]
A spectral algorithm for learning hidden Markov models
Journal of Computer and System Sciences, 78(5):1460–1480, 2012.
[ local pdf file | errata | jcss link | arxiv link | bibtex ]
A tail inequality for quadratic forms of subgaussian random vectors
Electronic Communications in Probability, 17(52):1–6, 2012.
[ local pdf file | ecp link | bibtex ]
Stochastic convex optimization with bandit feedback
In Advances in Neural Information Processing Systems 24, 2011.
[ external link | journal version | siam link | bibtex ]
Spectral methods for learning multivariate latent tree structure
In Advances in Neural Information Processing Systems 24, 2011.
[ local pdf file | arxiv link | bibtex ]
Sample complexity bounds for differentially private learning
In Twenty-Fourth Annual Conference on Learning Theory, 2011.
[ local pdf file | pmlr link | bibtex ]
Efficient optimal learning for contextual bandits
In Twenty-Seventh Conference on Uncertainty in Artificial Intelligence, 2011.
[ local pdf file | bibtex ]
Robust matrix decomposition with sparse corruptions
IEEE Transactions on Information Theory, 57(11):7221–7234, 2011.
[ local pdf file | arxiv link | ieee link | bibtex ]
Agnostic active learning without constraints
In Advances in Neural Information Processing Systems 23, 2010.
[ local pdf file | arxiv link | bibtex ]
An online learning-based framework for tracking
In Twenty-Sixth Conference on Uncertainty in Artificial Intelligence, 2010.
[ external link | bibtex ]
Algorithms for active learning
Ph.D. dissertation, UC San Diego, 2010.
[ local pdf file | bibtex ]
A parameter-free hedging algorithm
In Advances in Neural Information Processing Systems 22, 2009.
[ local pdf file | note about \(\epsilon\)-quantile regret | bibtex ]
Multi-label prediction via compressed sensing
In Advances in Neural Information Processing Systems 22, 2009.
[ local pdf file | talk slides | arxiv link | bibtex ]
A spectral algorithm for learning hidden Markov models
In Twenty-Second Annual Conference on Learning Theory, 2009.
[ external link | journal version | errata | bibtex ]
Hierarchical sampling for active learning
In Twenty-Fifth International Conference on Machine Learning, 2008.
[ local pdf file | bibtex ]
A general agnostic active learning algorithm
In Advances in Neural Information Processing Systems 20, 2007.
[ local pdf file | video 1 | video 2 | video 3 | video 4 | bibtex ]
On-line estimation with the multivariate Gaussian distribution
In Twentieth Annual Conference on Learning Theory, 2007.
[ local pdf file | bibtex ]
A concentration theorem for projections
In Twenty-Second Conference on Uncertainty in Artificial Intelligence, 2006.
[ local pdf file | bibtex ]