Arindam Banerjee

Publication Activity (10 Years)

Years Active: 2002-2024
Publications (10 Years): 79

Top Venues

CoRR

NIPS

AAAI

ICML

Publications

Rohan Deb, Yikun Ban, Shiliang Zuo, Jingrui He, Arindam Banerjee
Contextual Bandits with Online Neural Regression. ICLR (2024)
Arindam Banerjee, Qiaobo Li, Yingxue Zhou
Loss Gradient Gaussian Width based Generalization and Optimization Guarantees. CoRR (2024)
Adam J. Stewart, Nils Lehmann, Isaac A. Corley, Yi Wang, Yi-Chia Chang, Nassim Ait Ali Braham, Shradha Sehgal, Caleb Robinson, Arindam Banerjee
SSL4EO-L: Datasets and Foundation Models for Landsat Imagery. NeurIPS (2023)
Adam J. Stewart, Nils Lehmann, Isaac A. Corley, Yi Wang, Yi-Chia Chang, Nassim Ait Ali Braham, Shradha Sehgal, Caleb Robinson, Arindam Banerjee
SSL4EO-L: Datasets and Foundation Models for Landsat Imagery. CoRR (2023)
Yingxue Zhou, Xinyan Li, Arindam Banerjee
Noisy Truncated SGD: Optimization and Generalization. SDM (2022)
Sijie He, Xinyan Li, Laurie Trenary, Benjamin A. Cash, Timothy DelSole, Arindam Banerjee
Learning and Dynamical Models for Sub-seasonal Climate Forecasting: Comparison and Collaboration. AAAI (2022)
Vidyashankar Sivakumar, Shiliang Zuo, Arindam Banerjee
Smoothed Adversarial Linear Contextual Bandits with Knapsacks. ICML (2022)
Arindam Banerjee, Tiancong Chen, Xinyan Li, Yingxue Zhou
Stability Based Generalization Bounds for Exponential Family Langevin Dynamics. ICML (2022)
Adam J. Stewart, Caleb Robinson, Isaac A. Corley, Anthony Ortiz, Juan M. Lavista Ferres, Arindam Banerjee
TorchGeo: deep learning with geospatial data. SIGSPATIAL/GIS (2022)
Arindam Banerjee, Tiancong Chen, Xinyan Li, Yingxue Zhou
Stability Based Generalization Bounds for Exponential Family Langevin Dynamics. CoRR (2022)
Adam J. Stewart, Caleb Robinson, Isaac A. Corley, Anthony Ortiz, Juan M. Lavista Ferres, Arindam Banerjee
TorchGeo: deep learning with geospatial data. CoRR (2021)
Yingxue Zhou, Xinyan Li, Arindam Banerjee
Noisy Truncated SGD: Optimization and Generalization. CoRR (2021)
Yingxue Zhou, Steven Wu, Arindam Banerjee
Bypassing the Ambient Dimension: Private SGD with Gradient Subspace Identification. ICLR (2021)
Xinyan Li, Arindam Banerjee
Experiments with Rich Regime Training for Deep Learning. CoRR (2021)
Vishwak Srinivasan, Justin Khim, Arindam Banerjee, Pradeep Ravikumar
Subseasonal climate prediction in the western US using Bayesian spatial models. UAI (2021)
Sijie He, Xinyan Li, Laurie Trenary, Benjamin A. Cash, Timothy DelSole, Arindam Banerjee
Learning and Dynamical Models for Sub-seasonal Climate Forecasting: Comparison and Collaboration. CoRR (2021)
Sijie He, Xinyan Li, Timothy DelSole, Pradeep Ravikumar, Arindam Banerjee
Sub-Seasonal Climate Forecasting via Machine Learning: Challenges, Analysis, and Advances. AAAI (2021)
Yingxue Zhou, Xiangyi Chen, Mingyi Hong, Zhiwei Steven Wu, Arindam Banerjee
Private Stochastic Non-Convex Optimization: Adaptive Algorithms and Tighter Generalization Bounds. CoRR (2020)
Vidyashankar Sivakumar, Zhiwei Steven Wu, Arindam Banerjee
Structured Linear Contextual Bandits: A Sharp and Geometric Smoothed Analysis. ICML (2020)
Robert A. Giaquinto, Arindam Banerjee
Gradient Boosted Flows. CoRR (2020)
Vidyashankar Sivakumar, Zhiwei Steven Wu, Arindam Banerjee
Structured Linear Contextual Bandits: A Sharp and Geometric Smoothed Analysis. CoRR (2020)
Robert A. Giaquinto, Arindam Banerjee
Gradient Boosted Normalizing Flows. NeurIPS (2020)
Yingxue Zhou, Zhiwei Steven Wu, Arindam Banerjee
Bypassing the Ambient Dimension: Private SGD with Gradient Subspace Identification. CoRR (2020)
Sijie He, Xinyan Li, Timothy DelSole, Pradeep Ravikumar, Arindam Banerjee
Sub-Seasonal Climate Forecasting via Machine Learning: Challenges, Analysis, and Advances. CoRR (2020)
Arindam Banerjee, Tiancong Chen, Yingxue Zhou
De-randomized PAC-Bayes Margin Bounds: Applications to Non-convex and Non-smooth Predictors. CoRR (2020)
Xinyan Li, Qilong Gu, Yingxue Zhou, Tiancong Chen, Arindam Banerjee
Hessian based analysis of SGD for Deep Nets: Dynamics and Generalization. SDM (2020)
Qilong Gu, Joshua D. Trzasko, Arindam Banerjee
Scalable algorithms for locally low-rank matrix modeling. Knowl. Inf. Syst. 61 (3) (2019)
Arindam Banerjee, Qilong Gu, Vidyashankar Sivakumar, Zhiwei Steven Wu
Random Quadratic Forms with Dependence: Applications to Restricted Isometry and Beyond. CoRR (2019)
Qilong Gu, Arindam Banerjee
Sketched Iterative Algorithms for Structured Generalized Linear Models. IJCAI (2019)
Konstantina Christakopoulou, Arindam Banerjee
Adversarial attacks on an oblivious recommender. RecSys (2019)
André R. Gonçalves, Xiaoli Liu, Arindam Banerjee
Two-block vs. Multi-block ADMM: An empirical evaluation of convergence. CoRR (2019)
Sijie He, Xinyan Li, Vidyashankar Sivakumar, Arindam Banerjee
Interpretable Predictive Modeling for Climate Variables with Weighted Lasso. AAAI (2019)
Arindam Banerjee, Qilong Gu, Vidyashankar Sivakumar, Zhiwei Steven Wu
Random Quadratic Forms with Dependence: Applications to Restricted Isometry and Beyond. NeurIPS (2019)
Xinyan Li, Qilong Gu, Yingxue Zhou, Tiancong Chen, Arindam Banerjee
Hessian based analysis of SGD for Deep Nets: Dynamics and Generalization. CoRR (2019)
Yolanda Gil, Suzanne A. Pierce, Hassan A. Babaie, Arindam Banerjee, Kirk D. Borne, Gary S. Bust, Michelle Cheatham, Imme Ebert-Uphoff, Carla P. Gomes, Mary C. Hill, John D. Horel, Leslie Hsu, Jim Kinter, Craig A. Knoblock, David M. Krum, Vipin Kumar, Pierre Lermusiaux, Yan Liu, Chris North, Victor Pankratius, Shanan Peters, Beth Plale, Allen Pope, Sai Ravela, Juan Restrepo, Aaron J. Ridley, Hanan Samet, Shashi Shekhar
Intelligent systems for geosciences: an essential research agenda. Commun. ACM 62 (1) (2019)
Xiaoli Liu, Peng Cao, André R. Gonçalves, Dazhe Zhao, Arindam Banerjee
Modeling Alzheimer's Disease Progression with Fused Laplacian Sparse Group Lasso. ACM Trans. Knowl. Discov. Data 12 (6) (2018)
Robert A. Giaquinto, Arindam Banerjee
Topic Modeling on Health Journals with Regularized Variational Inference. CoRR (2018)
Konstantina Christakopoulou, Arindam Banerjee
Learning to Interact with Users: A Collaborative-Bandit Approach. SDM (2018)
Konstantina Christakopoulou, Arindam Banerjee
Adversarial Recommendation: Attack of the Learned Fake Users. CoRR (2018)
Robert A. Giaquinto, Arindam Banerjee
DAPPER: Scaling Dynamic Author Persona Topic Model to Billion Word Corpora. ICDM (2018)
Amir Asiaee T., Hardik Goel, Shalini Ghosh, Vinod Yegneswaran, Arindam Banerjee
Time Series Deinterleaving of DNS Traffic. CoRR (2018)
Amir Asiaee T., Hardik Goel, Shalini Ghosh, Vinod Yegneswaran, Arindam Banerjee
Time Series Deinterleaving of DNS Traffic. IEEE Symposium on Security and Privacy Workshops (2018)
Amir Asiaee T., Samet Oymak, Kevin R. Coombes, Arindam Banerjee
High Dimensional Data Enrichment: Interpretable, Fast, and Data-Efficient. CoRR (2018)
Sheng Chen, Arindam Banerjee
Sparse Linear Isotonic Models. AISTATS (2018)
Lisa Singh, Amol Deshpande, Wenchao Zhou, Arindam Banerjee, Alex J. Bowers, Sorelle A. Friedler, H. V. Jagadish, George Karypis, Zoran Obradovic, Anil Vullikanti, Wangda Zuo
NSF BIGDATA PI Meeting - Domain-Specific Research Directions and Data Sets. SIGMOD Rec. 47 (3) (2018)
Xiaoli Liu, André R. Gonçalves, Peng Cao, Dazhe Zhao, Arindam Banerjee
Modeling Alzheimer's disease cognitive scores using multi-task sparse group lasso. Comput. Medical Imaging Graph. 66 (2018)
Yingxue Zhou, Sheng Chen, Arindam Banerjee
Stable Gradient Descent. UAI (2018)
Robert A. Giaquinto, Arindam Banerjee
Topic Modeling on Health Journals With Regularized Variational Inference. AAAI (2018)
Sheng Chen, Arindam Banerjee
An Improved Analysis of Alternating Minimization for Structured Multi-Response Regression. NeurIPS (2018)
Robert A. Giaquinto, Arindam Banerjee
DAPPER: Scaling Dynamic Author Persona Topic Model to Billion Word Corpora. CoRR (2018)
Konstantina Christakopoulou, Jaya Kawale, Arindam Banerjee
Recommendation with Capacity Constraints. CIKM (2017)
Sheng Chen, Arindam Banerjee
Robust Structured Estimation with Single-Index Models. ICML (2017)
Rosana Veroneze, Arindam Banerjee, Fernando J. Von Zuben
Enumerating all maximal biclusters in numerical datasets. Inf. Sci. 379 (2017)
Jamal Golmohammadi, Imme Ebert-Uphoff, Sijie He, Yi Deng, Arindam Banerjee
High-Dimensional Dependency Structure Learning for Physical Processes. ICDM (2017)
Konstantina Christakopoulou, Jaya Kawale, Arindam Banerjee
Recommendation under Capacity Constraints. CoRR (2017)
Sheng Chen, Arindam Banerjee
Alternating Estimation for Structured High-Dimensional Multi-Response Models. NIPS (2017)
André R. Gonçalves, Arindam Banerjee, Fernando J. Von Zuben
Spatial Projection of Multiple Climate Variables Using Hierarchical Multitask Learning. AAAI (2017)
Hardik Goel, Igor Melnyk, Arindam Banerjee
R2N2: Residual Recurrent Neural Networks for Multivariate Time Series Forecasting. CoRR (2017)
Qilong Gu, Arindam Banerjee
High Dimensional Structured Superposition Models. CoRR (2017)
Vidyashankar Sivakumar, Arindam Banerjee
High-Dimensional Structured Quantile Regression. ICML (2017)
Igor Melnyk, Arindam Banerjee
A Spectral Algorithm for Inference in Hidden semi-Markov Models. J. Mach. Learn. Res. 18 (2017)
Jamal Golmohammadi, Imme Ebert-Uphoff, Sijie He, Yi Deng, Arindam Banerjee
High-Dimensional Dependency Structure Learning for Physical Processes. CoRR (2017)
Qilong Gu, Joshua D. Trzasko, Arindam Banerjee
Scalable Algorithms for Locally Low-Rank Matrix Modeling. ICDM (2017)
Anuj Karpatne, Gowtham Atluri, James H. Faghmous, Michael S. Steinbach, Arindam Banerjee, Auroop R. Ganguly, Shashi Shekhar, Nagiza F. Samatova, Vipin Kumar
Theory-Guided Data Science: A New Paradigm for Scientific Discovery from Data. IEEE Trans. Knowl. Data Eng. 29 (10) (2017)
André R. Gonçalves, Arindam Banerjee, Fernando J. Von Zuben
Spatial Projection of Multiple Climate Variables using Hierarchical Multitask Learning. CoRR (2017)
Farideh Fazayeli, Arindam Banerjee
Generalized Direct Change Estimation in Ising Model Structure. CoRR (2016)
Igor Melnyk, Bryan L. Matthews, Hamed Valizadegan, Arindam Banerjee, Nikunj C. Oza
Vector Autoregressive Model-Based Anomaly Detection in Aviation Systems. J. Aerosp. Inf. Syst. 13 (4) (2016)
Igor Melnyk, Arindam Banerjee, Bryan L. Matthews, Nikunj C. Oza
Semi-Markov Switching Vector Autoregressive Model-based Anomaly Detection in Aviation Systems. CoRR (2016)
Nicholas Johnson, Vidyashankar Sivakumar, Arindam Banerjee
Structured Stochastic Linear Bandits. CoRR (2016)
Igor Melnyk, Arindam Banerjee
Estimating Structured Vector Autoregressive Models. ICML (2016)
Amir Asiaee T., Soumyadeep Chatterjee, Arindam Banerjee
High Dimensional Structured Estimation with Noisy Designs. SDM (2016)
Qilong Gu, Arindam Banerjee
High Dimensional Structured Superposition Models. NIPS (2016)
Farideh Fazayeli, Arindam Banerjee
Generalized Direct Change Estimation in Ising Model Structure. ICML (2016)
Sheng Chen, Arindam Banerjee
Structured Matrix Recovery via the Generalized Dantzig Selector. NIPS (2016)
Farideh Fazayeli, Arindam Banerjee
The Matrix Generalized Inverse Gaussian Distribution: Properties and Applications. ECML/PKDD (1) (2016)
André R. Gonçalves, Fernando J. Von Zuben, Arindam Banerjee
Multi-task Sparse Structure Learning with Gaussian Copula Models. J. Mach. Learn. Res. 17 (2016)
Anuj Karpatne, Gowtham Atluri, James H. Faghmous, Michael S. Steinbach, Arindam Banerjee, Auroop R. Ganguly, Shashi Shekhar, Nagiza F. Samatova, Vipin Kumar
Theory-guided Data Science: A New Paradigm for Scientific Discovery. CoRR (2016)
Igor Melnyk, Arindam Banerjee, Bryan L. Matthews, Nikunj C. Oza
Semi-Markov Switching Vector Autoregressive Model-Based Anomaly Detection in Aviation Systems. KDD (2016)
Soumyadeep Chatterjee, Stefan Liess, Arindam Banerjee, Vipin Kumar
Understanding Dominant Factors for Precipitation over the Great Lakes Region. AAAI (2016)
Nicholas Johnson, Arindam Banerjee
Online Resource Allocation with Structured Diversification. SDM (2015)
Igor Melnyk, Arindam Banerjee
A Spectral Algorithm for Inference in Hidden semi-Markov Models. AISTATS (2015)
Mojtaba Kadkhodaie, Konstantina Christakopoulou, Maziar Sanjabi, Arindam Banerjee
Accelerated Alternating Direction Method of Multipliers. KDD (2015)
Nicholas Johnson, Arindam Banerjee
Structured Hedging for Resource Allocations with Leverage. KDD (2015)
André R. Gonçalves, Fernando J. Von Zuben, Arindam Banerjee
A Multitask Learning View on the Earth System Model Ensemble. Comput. Sci. Eng. 17 (6) (2015)
Karthik Subbian, Arindam Banerjee, Sugato Basu
PLUMS: Predicting Links Using Multiple Sources. SDM (2015)
Golshan Golnari, Amir Asiaee T., Arindam Banerjee, Zhi-Li Zhang
Revisiting Non-Progressive Influence Models: Scalable Influence Maximization in Social Networks. UAI (2015)
Sheng Chen, Arindam Banerjee
Structured Estimation with Atomic Norms: General Bounds and Applications. NIPS (2015)
Arindam Banerjee, Sheng Chen, Vidyashankar Sivakumar
Open Problem: Restricted Eigenvalue Condition for Heavy Tailed Designs. COLT (2015)
André R. Gonçalves, Fernando J. Von Zuben, Arindam Banerjee
Multi-Label Structure Learning with Ising Model Selection. IJCAI (2015)
Konstantina Christakopoulou, Arindam Banerjee
Collaborative Ranking with a Push at the Top. WWW (2015)
Vidyashankar Sivakumar, Arindam Banerjee, Pradeep Ravikumar
Beyond Sub-Gaussian Measurements: High-Dimensional Structured Estimation with Sub-Exponential Designs. NIPS (2015)
Suriya Gunasekar, Arindam Banerjee, Joydeep Ghosh
Unified View of Matrix Completion under General Structural Constraints. NIPS (2015)
Sheng Chen, Arindam Banerjee
One-bit Compressed Sensing with the k-Support Norm. AISTATS (2015)
Chen Jin, Qiang Fu, Huahua Wang, William Hendrix, Zhengzhang Chen, Ankit Agrawal, Arindam Banerjee, Alok N. Choudhary
Running MAP Inference on Million Node Graphical Models: A High Performance Computing Perspective. CCGRID (2015)
Arindam Banerjee, Sheng Chen, Farideh Fazayeli, Vidyashankar Sivakumar
Estimation with Norm Regularization. CoRR (2015)
Farideh Fazayeli, Arindam Banerjee, Jens Kattge, Franziska Schrodt, Peter B. Reich
Uncertainty Quantified Matrix Completion Using Bayesian Hierarchical Matrix Factorization. ICMLA (2014)
Puja Das, Nicholas Johnson, Arindam Banerjee
Online Portfolio Selection with Group Sparsity. AAAI (2014)
André R. Gonçalves, Puja Das, Soumyadeep Chatterjee, Vidyashankar Sivakumar, Fernando J. Von Zuben, Arindam Banerjee
Multi-task Sparse Structure Learning. CIKM (2014)
André R. Gonçalves, Puja Das, Soumyadeep Chatterjee, Vidyashankar Sivakumar, Fernando J. Von Zuben, Arindam Banerjee
Multi-task Sparse Structure Learning. CoRR (2014)
Huahua Wang, Arindam Banerjee, Zhi-Quan Luo
Parallel Direction Method of Multipliers. NIPS (2014)

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Publication Activity (10 Years)

Top Topics

Top Venues

Arindam Banerjee