Arindam Banerjee
54 papers · 2005–2025 · 9 conferences · across top CS/AI conferences
Achievements
Jump to papers ↓+17 more ↓ Show less ↑
π§ Keyword Pioneer π£ Hot Topic Early Bird π Interdisciplinary Bridge πΊοΈ Taxonomy Completionist (22) π Conference Polyglot (9)
π
Renaissance Researcher
(8)
π
Interdisciplinary Bridge
π
Cross-Pollinator
(12)
π
Conference Loyalist
(20)
π
Keyword Trendsetter Combo
(4)
π¬
Deep Specialist
(17)
π
Triple Crown
π±
Topic Pioneer
π
Keyword Champion
(2)
π
Grand Slam
π€
Dynamic Duo
(10)
ποΈ
Keyword Collector
(79)
π₯
Unstoppable
(14)
π
Trend Setter
π
Conference Pioneer
β‘
Prolific Year
(7)
π
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
Research topics
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