Banerjee, Arindam

79 publications

UAI 2025 Computationally Efficient Methods for Invariant Feature Selection with Sparsity Jane Du, Arindam Banerjee

ICLR 2025 Conservative Contextual Bandits: Beyond Linear Representations Rohan Deb, Mohammad Ghavamzadeh, Arindam Banerjee

AISTATS 2025 Loss Gradient Gaussian Width Based Generalization and Optimization Guarantees Arindam Banerjee, Qiaobo Li, Yingxue Zhou

UAI 2025 MSP-SR: Multi-Stage Probabilistic Generative Super Resolution with Scarce High-Resolution Data Ruike Zhu, Matthew Charles Weston, Hanwen Zhang, Arindam Banerjee

TMLR 2025 Optimization and Generalization Guarantees for Weight Normalization Pedro Cisneros-Velarde, Zhijie Chen, Sanmi Koyejo, Arindam Banerjee

ICML 2025 Optimization for Neural Operators Can Benefit from Width Pedro Cisneros-Velarde, Bhavesh Shrimali, Arindam Banerjee

NeurIPS 2025 Sketched Adaptive Distributed Deep Learning: A Sharp Convergence Analysis Zhijie Chen, Qiaobo Li, Arindam Banerjee

NeurIPS 2025 Sketched Gaussian Mechanism for Private Federated Learning Qiaobo Li, Zhijie Chen, Arindam Banerjee

ICLRW 2025 Truncate Without Fear: Module Aggregation and Redistribution in Federated Low-Rank Adaptation Zhijie Chen, Yuxing Liu, Arindam Banerjee

TMLR 2024 AmbientFlow: Invertible Generative Models from Incomplete, Noisy Measurements Varun A. Kelkar, Rucha Deshpande, Arindam Banerjee, Mark Anastasio

ICLR 2024 Contextual Bandits with Online Neural Regression Rohan Deb, Yikun Ban, Shiliang Zuo, Jingrui He, Arindam Banerjee

NeurIPS 2024 Robust Neural Contextual Bandit Against Adversarial Corruptions Yunzhe Qi, Yikun Ban, Arindam Banerjee, Jingrui He

NeurIPS 2024 Sketching for Distributed Deep Learning: A Sharper Analysis Mayank Shrivastava, Berivan Isik, Qiaobo Li, Sanmi Koyejo, Arindam Banerjee

AISTATS 2024 Think Before You Duel: Understanding Complexities of Preference Learning Under Constrained Resources Rohan Deb, Aadirupa Saha, Arindam Banerjee

NeurIPSW 2023 AmbientFlow: Invertible Generative Models from Incomplete, Noisy Imaging Measurements Varun A. Kelkar, Rucha Deshpande, Arindam Banerjee, Mark Anastasio

UAI 2023 Neural Tangent Kernel at Initialization: Linear Width Suffices Arindam Banerjee, Pedro Cisneros-Velarde, Libin Zhu, Mikhail Belkin

ICLR 2023 Restricted Strong Convexity of Deep Learning Models with Smooth Activations Arindam Banerjee, Pedro Cisneros-Velarde, Libin Zhu, Misha Belkin

NeurIPS 2023 SSL4EO-L: Datasets and Foundation Models for Landsat Imagery Adam Stewart, Nils Lehmann, Isaac Corley, Yi Wang, Yi-Chia Chang, Nassim Ait Ait Ali Braham, Shradha Sehgal, Caleb Robinson, Arindam Banerjee

ICLR 2022 EE-Net: Exploitation-Exploration Neural Networks in Contextual Bandits Yikun Ban, Yuchen Yan, Arindam Banerjee, Jingrui He

NeurIPS 2022 Improved Algorithms for Neural Active Learning Yikun Ban, Yuheng Zhang, Hanghang Tong, Arindam Banerjee, Jingrui He

AAAI 2022 Learning and Dynamical Models for Sub-Seasonal Climate Forecasting: Comparison and Collaboration Sijie He, Xinyan Li, Laurie Trenary, Benjamin A. Cash, Timothy DelSole, Arindam Banerjee

ICML 2022 Smoothed Adversarial Linear Contextual Bandits with Knapsacks Vidyashankar Sivakumar, Shiliang Zuo, Arindam Banerjee

ICML 2022 Stability Based Generalization Bounds for Exponential Family Langevin Dynamics Arindam Banerjee, Tiancong Chen, Xinyan Li, Yingxue Zhou

ICLR 2021 Bypassing the Ambient Dimension: Private SGD with Gradient Subspace Identification Yingxue Zhou, Steven Wu, Arindam Banerjee

AAAI 2021 Sub-Seasonal Climate Forecasting via Machine Learning: Challenges, Analysis, and Advances Sijie He, Xinyan Li, Timothy DelSole, Pradeep Ravikumar, Arindam Banerjee

UAI 2021 Subseasonal Climate Prediction in the Western US Using Bayesian Spatial Models Vishwak Srinivasan, Justin Khim, Arindam Banerjee, Pradeep Ravikumar

NeurIPS 2020 Gradient Boosted Normalizing Flows Robert Giaquinto, Arindam Banerjee

ICML 2020 Structured Linear Contextual Bandits: A Sharp and Geometric Smoothed Analysis Vidyashankar Sivakumar, Steven Wu, Arindam Banerjee

ICMLW 2019 Data Enrichment: Multi-Task Learning in High Dimension with Theoretical Guarantees Amir Asiaee, Samet Oymak, Kevin R. Coombes, Arindam Banerjee

AAAI 2019 Interpretable Predictive Modeling for Climate Variables with Weighted Lasso Sijie He, Xinyan Li, Vidyashankar Sivakumar, Arindam Banerjee

NeurIPS 2019 Random Quadratic Forms with Dependence: Applications to Restricted Isometry and Beyond Arindam Banerjee, Qilong Gu, Vidyashankar Sivakumar, Steven Z. Wu

IJCAI 2019 Sketched Iterative Algorithms for Structured Generalized Linear Models Qilong Gu, Arindam Banerjee

NeurIPS 2018 An Improved Analysis of Alternating Minimization for Structured Multi-Response Regression Sheng Chen, Arindam Banerjee

AISTATS 2018 Sparse Linear Isotonic Models Sheng Chen, Arindam Banerjee

UAI 2018 Stable Gradient Descent Yingxue Zhou, Sheng Chen, Arindam Banerjee

AAAI 2018 Topic Modeling on Health Journals with Regularized Variational Inference Robert A. Giaquinto, Arindam Banerjee

JMLR 2017 A Spectral Algorithm for Inference in Hidden Semi-Markov Models Igor Melnyk, Arindam Banerjee

NeurIPS 2017 Alternating Estimation for Structured High-Dimensional Multi-Response Models Sheng Chen, Arindam Banerjee

ICML 2017 High-Dimensional Structured Quantile Regression Vidyashankar Sivakumar, Arindam Banerjee

ICML 2017 Robust Structured Estimation with Single-Index Models Sheng Chen, Arindam Banerjee

AAAI 2017 Spatial Projection of Multiple Climate Variables Using Hierarchical Multitask Learning André R. Gonçalves, Arindam Banerjee, Fernando J. Von Zuben

ICML 2016 Estimating Structured Vector Autoregressive Models Igor Melnyk, Arindam Banerjee

ICML 2016 Generalized Direct Change Estimation in Ising Model Structure Farideh Fazayeli, Arindam Banerjee

NeurIPS 2016 High Dimensional Structured Superposition Models Qilong Gu, Arindam Banerjee

JMLR 2016 Multi-Task Sparse Structure Learning with Gaussian Copula Models André R. Gonçalves, Fernando J. Von Zuben, Arindam Banerjee

NeurIPS 2016 Structured Matrix Recovery via the Generalized Dantzig Selector Sheng Chen, Arindam Banerjee

ECML-PKDD 2016 The Matrix Generalized Inverse Gaussian Distribution: Properties and Applications Farideh Fazayeli, Arindam Banerjee

AAAI 2016 Understanding Dominant Factors for Precipitation over the Great Lakes Region Soumyadeep Chatterjee, Stefan Liess, Arindam Banerjee, Vipin Kumar

AISTATS 2015 A Spectral Algorithm for Inference in Hidden Semi-Markov Models Igor Melnyk, Arindam Banerjee

NeurIPS 2015 Beyond Sub-Gaussian Measurements: High-Dimensional Structured Estimation with Sub-Exponential Designs Vidyashankar Sivakumar, Arindam Banerjee, Pradeep K Ravikumar

IJCAI 2015 Multi-Label Structure Learning with Ising Model Selection André R. Gonçalves, Fernando J. Von Zuben, Arindam Banerjee

AISTATS 2015 One-Bit Compressed Sensing with the K-Support Norm Sheng Chen, Arindam Banerjee

COLT 2015 Open Problem: Restricted Eigenvalue Condition for Heavy Tailed Designs Arindam Banerjee, Sheng Chen, Vidyashankar Sivakumar

UAI 2015 Revisiting Non-Progressive Influence Models: Scalable Influence Maximization in Social Networks Golshan Golnari, Amir Asiaee Tabatabaei, Arindam Banerjee, Zhi-Li Zhang

NeurIPS 2015 Structured Estimation with Atomic Norms: General Bounds and Applications Sheng Chen, Arindam Banerjee

NeurIPS 2015 Unified View of Matrix Completion Under General Structural Constraints Suriya Gunasekar, Arindam Banerjee, Joydeep Ghosh

NeurIPS 2014 Bregman Alternating Direction Method of Multipliers Huahua Wang, Arindam Banerjee

NeurIPS 2014 Estimation with Norm Regularization Arindam Banerjee, Sheng Chen, Farideh Fazayeli, Vidyashankar Sivakumar

AISTATS 2014 Gaussian Copula Precision Estimation with Missing Values Huahua Wang, Farideh Fazayeli, Soumyadeep Chatterjee, Arindam Banerjee

NeurIPS 2014 Generalized Dantzig Selector: Application to the K-Support Norm Soumyadeep Chatterjee, Sheng Chen, Arindam Banerjee

AAAI 2014 Online Portfolio Selection with Group Sparsity Puja Das, Nicholas Johnson, Arindam Banerjee

NeurIPS 2014 Parallel Direction Method of Multipliers Huahua Wang, Arindam Banerjee, Zhi-Quan Luo

UAI 2013 Bethe-ADMM for Tree Decomposition Based Parallel MAP Inference Qiang Fu, Huahua Wang, Arindam Banerjee

NeurIPS 2013 Large Scale Distributed Sparse Precision Estimation Huahua Wang, Arindam Banerjee, Cho-Jui Hsieh, Pradeep K Ravikumar, Inderjit S Dhillon

AAAI 2013 Online Lazy Updates for Portfolio Selection with Transaction Costs Puja Das, Nicholas Johnson, Arindam Banerjee

NeurIPS 2012 A Divide-and-Conquer Method for Sparse Inverse Covariance Estimation Cho-jui Hsieh, Arindam Banerjee, Inderjit S. Dhillon, Pradeep K. Ravikumar

ICML 2012 Gap Filling in the Plant Kingdom - Trait Prediction Using Hierarchical Probabilistic Matrix Factorization Hanhuai Shan, Jens Kattge, Peter B. Reich, Arindam Banerjee, Franziska Schrodt, Markus Reichstein

ICML 2012 Online Alternating Direction Method Huahua Wang, Arindam Banerjee

NeurIPS 2012 Online L1-Dictionary Learning with Application to Novel Document Detection Shiva P. Kasiviswanathan, Huahua Wang, Arindam Banerjee, Prem Melville

ICCV 2011 Efficient Similarity Search for Covariance Matrices via the Jensen-Bregman LogDet Divergence Anoop Cherian, Suvrit Sra, Arindam Banerjee, Nikolaos Papanikolopoulos

ICML 2011 Probabilistic Matrix Addition Amrudin Agovic, Arindam Banerjee, Snigdhansu Chatterjee

UAI 2010 Gaussian Process Topic Models Amrudin Agovic, Arindam Banerjee

ALT 2009 Approximation Algorithms for Tensor Clustering Stefanie Jegelka, Suvrit Sra, Arindam Banerjee

JMLR 2007 A Generalized Maximum Entropy Approach to Bregman Co-Clustering and Matrix Approximation Arindam Banerjee, Inderjit Dhillon, Joydeep Ghosh, Srujana Merugu, Dharmendra S. Modha

ICML 2006 On Bayesian Bounds Arindam Banerjee

JMLR 2005 Clustering on the Unit Hypersphere Using Von Mises-Fisher Distributions Arindam Banerjee, Inderjit S. Dhillon, Joydeep Ghosh, Suvrit Sra

JMLR 2005 Clustering with Bregman Divergences Arindam Banerjee, Srujana Merugu, Inderjit S. Dhillon, Joydeep Ghosh

ICML 2004 An Information Theoretic Analysis of Maximum Likelihood Mixture Estimation for Exponential Families Arindam Banerjee, Inderjit S. Dhillon, Joydeep Ghosh, Srujana Merugu

ICML 2002 Semi-Supervised Clustering by Seeding Sugato Basu, Arindam Banerjee, Raymond J. Mooney