Daniel Hsu

Group-realizable multi-group learning by minimizing empirical risk ALT 2026 Learning Gaussian Multi-Index Models with Gradient Flow: Time Complexity and Directional Convergence AISTATS 2025 Learning Compositional Functions with Transformers from Easy-to-Hard Data COLT 2025 On the sample complexity of parameter estimation in logistic regression with normal design COLT 2024 Group-wise oracle-efficient algorithms for online multi-group learning NIPS 2024 Algorithmic Learning Theory 2024: Preface ALT 2024 Transformers Provably Learn Sparse Token Selection While Fully-Connected Nets Cannot ICML 2024 Transformers, parallel computation, and logarithmic depth ICML 2024 Multi-group Learning for Hierarchical Groups ICML 2024 Simple and near-optimal algorithms for hidden stratification and multi-group learning ICML 2022 Unbiased estimators for random design regression JMLR 2022 Learning Tensor Representations for Meta-Learning AISTATS 2022 Generalization bounds via distillation ICLR 2021 On the Approximation Power of Two-Layer Networks of Random ReLUs COLT 2021 Quantifying the Effects of COVID-19 on Restaurant Reviews NAACL 2021 On the proliferation of support vectors in high dimensions AISTATS 2021 Contrastive learning, multi-view redundancy, and linear models ALT 2021 Contrastive Estimation Reveals Topic Posterior Information to Linear Models JMLR 2021 Classification vs regression in overparameterized regimes: Does the loss function matter? JMLR 2021 Statistical Query Lower Bounds for Tensor PCA JMLR 2021 Detecting Foodborne Illness Complaints in Multiple Languages Using English Annotations Only EMNLP 2020 Diameter-based Interactive Structure Discovery AISTATS 2020 Cross-Lingual Text Classification with Minimal Resources by Transferring a Sparse Teacher EMNLP 2020 Weakly Supervised Attention Networks for Fine-Grained Opinion Mining and Public Health EMNLP 2019 Leveraging Just a Few Keywords for Fine-Grained Aspect Detection Through Weakly Supervised Co-Training EMNLP 2019 Conference on Learning Theory 2019: Preface COLT 2019 A Gradual, Semi-Discrete Approach to Generative Network Training via Explicit Wasserstein Minimization ICML 2019 Teaching a black-box learner ICML 2019 Leveraging Just a Few Keywords for Fine-Grained Aspect Detection Through Weakly Supervised Co-Training IJCNLP 2019 Kernel Approximation Methods for Speech Recognition JMLR 2019 Attribute-efficient learning of monomials over highly-correlated variables ALT 2019 Correcting the bias in least squares regression with volume-rescaled sampling AISTATS 2019 Learning Single-Index Models in Gaussian Space COLT 2018 Correspondence retrieval COLT 2017 Parameter identification in Markov chain choice models ALT 2017 Loss Minimization and Parameter Estimation with Heavy Tails JMLR 2016 Model-based Word Embeddings from Decompositions of Count Matrices ACL 2015 Learning Sparse Low-Threshold Linear Classifiers JMLR 2015 When Are Overcomplete Topic Models Identifiable? Uniqueness of Tensor Tucker Decompositions with Structured Sparsity JMLR 2015 Model-based Word Embeddings from Decompositions of Count Matrices IJCNLP 2015 Heavy-tailed regression with a generalized median-of-means ICML 2014 A Tensor Approach to Learning Mixed Membership Community Models JMLR 2014 Tensor Decompositions for Learning Latent Variable Models JMLR 2014 Taming the Monster: A Fast and Simple Algorithm for Contextual Bandits ICML 2014 A Tensor Spectral Approach to Learning Mixed Membership Community Models COLT 2013 Learning Linear Bayesian Networks with Latent Variables ICML 2013 Random Design Analysis of Ridge Regression COLT 2012 A Method of Moments for Mixture Models and Hidden Markov Models COLT 2012 Sample Complexity Bounds for Differentially Private Learning COLT 2011