Arya Mazumdar

Actively Learning Halfspaces without Synthetic Data COLT 2026 Exact Recovery of Sparse Binary Vectors from Generalized Linear Measurements ICML 2025 Learning Partitions with Optimal Query and Round Complexities COLT 2025 Learning sparse generalized linear models with binary outcomes via iterative hard thresholding COLT 2025 Optimal Graph Reconstruction by Counting Connected Components in Induced Subgraphs COLT 2025 Optimal Transfer Learning for Missing Not-at-Random Matrix Completion ICML 2025 Sharper Guarantees for Learning Neural Network Classifiers with Gradient Methods ICLR 2025 Agnostic Learning of Mixed Linear Regressions with EM and AM Algorithms ICML 2024 Clustering with Non-adaptive Subset Queries NeurIPS 2024 On the sample complexity of parameter estimation in logistic regression with normal design COLT 2024 Random Subgraph Detection Using Queries JMLR 2024 Transfer Learning for Latent Variable Network Models NeurIPS 2024 Community Recovery in the Geometric Block Model JMLR 2023 Lower Bounds on the Total Variation Distance Between Mixtures of Two Gaussians ALT 2022 On Learning Mixture Models with Sparse Parameters AISTATS 2022 On Learning Mixture of Linear Regressions in the Non-Realizable Setting ICML 2022 Fuzzy Clustering with Similarity Queries NeurIPS 2021 Support Recovery of Sparse Signals from a Mixture of Linear Measurements NeurIPS 2021 vqSGD: Vector Quantized Stochastic Gradient Descent AISTATS 2021 Algebraic and Analytic Approaches for Parameter Learning in Mixture Models ALT 2020 Distributed Newton Can Communicate Less and Resist Byzantine Workers NeurIPS 2020 High Dimensional Discrete Integration over the Hypergrid UAI 2020 Multilabel Classification by Hierarchical Partitioning and Data-dependent Grouping NeurIPS 2020 Recovery of sparse linear classifiers from mixture of responses NeurIPS 2020 Recovery of Sparse Signals from a Mixture of Linear Samples ICML 2020 Same-Cluster Querying for Overlapping Clusters NeurIPS 2019 Sample Complexity of Learning Mixture of Sparse Linear Regressions NeurIPS 2019 Superset Technique for Approximate Recovery in One-Bit Compressed Sensing NeurIPS 2019 Clustering with Noisy Queries NeurIPS 2017 Efficient Rank Aggregation via Lehmer Codes AISTATS 2017 Multilabel Classification with Group Testing and Codes ICML 2017 Query Complexity of Clustering with Side Information NeurIPS 2017 Semisupervised Clustering, AND-Queries and Locally Encodable Source Coding NeurIPS 2017 Associative Memory via a Sparse Recovery Model NeurIPS 2015 Low Rank Approximation using Error Correcting Coding Matrices ICML 2015