Arindam Banerjee

Neural Exploitation and Exploration of Contextual Bandits JMLR 2026 Computationally Efficient Methods for Invariant Feature Selection with Sparsity UAI 2025 Conservative Contextual Bandits: Beyond Linear Representations ICLR 2025 Loss Gradient Gaussian Width based Generalization and Optimization Guarantees AISTATS 2025 MSP-SR: Multi-Stage Probabilistic Generative Super Resolution with Scarce High-Resolution Data UAI 2025 Optimization for Neural Operators can Benefit from Width ICML 2025 Contextual Bandits with Online Neural Regression ICLR 2024 Robust Neural Contextual Bandit against Adversarial Corruptions NeurIPS 2024 Sketching for Distributed Deep Learning: A Sharper Analysis NeurIPS 2024 Think Before You Duel: Understanding Complexities of Preference Learning under Constrained Resources AISTATS 2024 Neural tangent kernel at initialization: linear width suffices UAI 2023 Restricted Strong Convexity of Deep Learning Models with Smooth Activations ICLR 2023 SSL4EO-L: Datasets and Foundation Models for Landsat Imagery NeurIPS 2023 EE-Net: Exploitation-Exploration Neural Networks in Contextual Bandits ICLR 2022 Improved Algorithms for Neural Active Learning NeurIPS 2022 Learning and Dynamical Models for Sub-seasonal Climate Forecasting: Comparison and Collaboration AAAI 2022 Smoothed Adversarial Linear Contextual Bandits with Knapsacks ICML 2022 Stability Based Generalization Bounds for Exponential Family Langevin Dynamics ICML 2022 Bypassing the Ambient Dimension: Private SGD with Gradient Subspace Identification ICLR 2021 Sub-Seasonal Climate Forecasting via Machine Learning: Challenges, Analysis, and Advances AAAI 2021 Subseasonal climate prediction in the western US using Bayesian spatial models UAI 2021 Gradient Boosted Normalizing Flows NeurIPS 2020 Structured Linear Contextual Bandits: A Sharp and Geometric Smoothed Analysis ICML 2020 Interpretable Predictive Modeling for Climate Variables with Weighted Lasso AAAI 2019 Random Quadratic Forms with Dependence: Applications to Restricted Isometry and Beyond NeurIPS 2019 Sketched Iterative Algorithms for Structured Generalized Linear Models IJCAI 2019 An Improved Analysis of Alternating Minimization for Structured Multi-Response Regression NeurIPS 2018 Sparse Linear Isotonic Models AISTATS 2018 Alternating Estimation for Structured High-Dimensional Multi-Response Models NeurIPS 2017 A Spectral Algorithm for Inference in Hidden semi-Markov Models JMLR 2017 High-Dimensional Structured Quantile Regression ICML 2017 Robust Structured Estimation with Single-Index Models ICML 2017 Estimating Structured Vector Autoregressive Models ICML 2016 Generalized Direct Change Estimation in Ising Model Structure ICML 2016 High Dimensional Structured Superposition Models NeurIPS 2016 Multi-task Sparse Structure Learning with Gaussian Copula Models JMLR 2016 Structured Matrix Recovery via the Generalized Dantzig Selector NeurIPS 2016 A Spectral Algorithm for Inference in Hidden semi-Markov Models AISTATS 2015 Beyond Sub-Gaussian Measurements: High-Dimensional Structured Estimation with Sub-Exponential Designs NeurIPS 2015 Multi-Label Structure Learning with Ising Model Selection IJCAI 2015 One-bit Compressed Sensing with the k-Support Norm AISTATS 2015 Open Problem: Restricted Eigenvalue Condition for Heavy Tailed Designs COLT 2015 Structured Estimation with Atomic Norms: General Bounds and Applications NeurIPS 2015 Unified View of Matrix Completion under General Structural Constraints NeurIPS 2015 Bregman Alternating Direction Method of Multipliers NeurIPS 2014 Estimation with Norm Regularization NeurIPS 2014 Gaussian Copula Precision Estimation with Missing Values AISTATS 2014 Generalized Dantzig Selector: Application to the k-support norm NeurIPS 2014 Parallel Direction Method of Multipliers NeurIPS 2014 Large Scale Distributed Sparse Precision Estimation NeurIPS 2013 A Divide-and-Conquer Method for Sparse Inverse Covariance Estimation NeurIPS 2012 Online L1-Dictionary Learning with Application to Novel Document Detection NeurIPS 2012 A Generalized Maximum Entropy Approach to Bregman Co-clustering and Matrix Approximation JMLR 2007 Clustering on the Unit Hypersphere using von Mises-Fisher Distributions JMLR 2005 Clustering with Bregman Divergences JMLR 2005