← Authors

Arindam Banerjee

54 papers · 2005–2025 · 9 conferences · across top CS/AI conferences

Achievements

🧭 Keyword Pioneer 🐣 Hot Topic Early Bird 🌍 Conference Polyglot (9) πŸ—ΊοΈ Taxonomy Completionist (22) πŸƒ Academic Marathon (20) 🌈 Renaissance Researcher (8) πŸŒ‰ Interdisciplinary Bridge 🐝 Cross-Pollinator (12) 🏠 Conference Loyalist (20) 🌟 Keyword Trendsetter Combo (4) πŸ”¬ Deep Specialist (17) πŸ‘‘ Triple Crown 🌱 Topic Pioneer πŸ† Keyword Champion (2) πŸ† Grand Slam 🀝 Dynamic Duo (10) πŸ—ƒοΈ Keyword Collector (79) πŸ”₯ Unstoppable (14) πŸ“ˆ Trend Setter πŸš€ Conference Pioneer ⚑ Prolific Year (7) πŸ’Ž Century Club (54)

Conferences

NIPS (20) ICML (8) AISTATS (6) ICLR (5) JMLR (5) UAI (4) AAAI (3) IJCAI (2) COLT (1)

Top co-authors

Sheng Chen (10) Vidyashankar Sivakumar (8) Huahua Wang (5) Joydeep Ghosh (4) Jingrui He (4) Xinyan Li (4) Yikun Ban (4) Qilong Gu (3) Farideh Fazayeli (3) Inderjit S. Dhillon (3)

Research topics

Statistics (1)

Keywords

gaussian width (5) convex optimization (5) regret bound (4) compressed sensing (4) sparse optimization (4) dantzig selector (3) climate prediction (3) high-dimensional estimation (3) sparse regression (3) bregman divergence (3) contextual bandit (3) precision matrix (3) k-support norm (3) high-dimensional regression (3) sample complexity (3) high-dimensional statistics (3) sparse estimation (3) alternating direction method of multiplier (3) structured estimation (2) machine learning (2)

Papers

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