← Authors

Inderjit S Dhillon

56 papers · 2006–2026 · 5 conferences · across top CS/AI conferences

Achievements

πŸ—ΊοΈ Taxonomy Completionist (24) 🐝 Cross-Pollinator (13) πŸƒ Academic Marathon (20) 🌍 Conference Polyglot (5) 🌈 Renaissance Researcher (5) 🐣 Hot Topic Early Bird πŸŒ‰ Interdisciplinary Bridge 🧭 Keyword Pioneer 🌟 Keyword Trendsetter Combo (14) 🏠 Conference Loyalist (45) πŸ† Keyword Champion (2) πŸ”¬ Deep Specialist (12) 🀝 Dynamic Duo (21) 🌱 Topic Pioneer 🧬 Topic Evolution πŸ“ˆ Trend Setter πŸš€ Conference Pioneer πŸ—ƒοΈ Keyword Collector (97) πŸ”₯ Unstoppable (10) πŸ’Ž Century Club (56) ⚑ Prolific Year (6)

Conferences

NIPS (45) ICLR (6) ICML (3) EMNLP (1) WACV (1)

Top co-authors

Cho-jui Hsieh (21) Pradeep K Ravikumar (18) Inderjit S. Dhillon (17) Hsiang-Fu Yu (11) Prateek Jain (10) Kai Zhong (6) Ian En-Hsu Yen (5) Si Si (5) Sai Surya Duvvuri (5) Ambuj Tewari (4)

Keywords

convex optimization (6) sparse optimization (5) coordinate descent (5) matrix factorization (5) l1 regularization (4) high-dimensional optimization (4) matrix completion (4) greedy algorithm (4) sparse regression (3) low-rank approximation (3) graphical model (3) linear convergence (3) support vector machine (3) low-rank matrix (3) sparse inverse covariance (3) metric learning (2) high-dimensional statistics (2) high-dimensional estimation (2) graph structure (2) model compression (2)

Papers

Pyramidal Spectrum: Frequency-based Hierarchically Vector Quantized VAE for Videos WACV 2026
LoRA Done RITE: Robust Invariant Transformation Equilibration for LoRA Optimization ICLR 2025
LASER: Attention with Exponential Transformation ICML 2025
Retraining with Predicted Hard Labels Provably Increases Model Accuracy ICML 2025
Geometric Median (GM) Matching for Robust k-Subset Selection from Noisy Data ICML 2025
Large Language Models are Interpretable Learners ICLR 2025
PRISM: A New Lens for Improved Color Understanding EMNLP 2024
Dual-Encoders for Extreme Multi-label Classification ICLR 2024
Combining Axes Preconditioners through Kronecker Approximation for Deep Learning ICLR 2024
Two-stage LLM Fine-tuning with Less Specialization and More Generalization ICLR 2024
A Computationally Efficient Sparsified Online Newton Method NIPS 2023
Block Low-Rank Preconditioner with Shared Basis for Stochastic Optimization NIPS 2023
ELIAS: End-to-End Learning to Index and Search in Large Output Spaces NIPS 2022
Node Feature Extraction by Self-Supervised Multi-scale Neighborhood Prediction ICLR 2022
S3GC: Scalable Self-Supervised Graph Clustering NIPS 2022
Label Disentanglement in Partition-based Extreme Multilabel Classification NIPS 2021
DRONE: Data-aware Low-rank Compression for Large NLP Models NIPS 2021
Fast Multi-Resolution Transformer Fine-tuning for Extreme Multi-label Text Classification NIPS 2021
Inverting Deep Generative models, One layer at a time NIPS 2019
Primal-Dual Block Generalized Frank-Wolfe NIPS 2019
Provable Non-linear Inductive Matrix Completion NIPS 2019
AutoAssist: A Framework to Accelerate Training of Deep Neural Networks NIPS 2019
Think Globally, Act Locally: A Deep Neural Network Approach to High-Dimensional Time Series Forecasting NIPS 2019
A Greedy Approach for Budgeted Maximum Inner Product Search NIPS 2017
Mixed Linear Regression with Multiple Components NIPS 2016
Asynchronous Parallel Greedy Coordinate Descent NIPS 2016
Dual Decomposed Learning with Factorwise Oracle for Structural SVM of Large Output Domain NIPS 2016
Temporal Regularized Matrix Factorization for High-dimensional Time Series Prediction NIPS 2016
Coordinate-wise Power Method NIPS 2016
Structured Sparse Regression via Greedy Hard Thresholding NIPS 2016
Matrix Completion with Noisy Side Information NIPS 2015
Collaborative Filtering with Graph Information: Consistency and Scalable Methods NIPS 2015
Fixed-Length Poisson MRF: Adding Dependencies to the Multinomial NIPS 2015
Consistent Multilabel Classification NIPS 2015
Sparse Linear Programming via Primal and Dual Augmented Coordinate Descent NIPS 2015
Consistent Binary Classification with Generalized Performance Metrics NIPS 2014
Constant Nullspace Strong Convexity and Fast Convergence of Proximal Methods under High-Dimensional Settings NIPS 2014
Fast Prediction for Large-Scale Kernel Machines NIPS 2014
Multi-Scale Spectral Decomposition of Massive Graphs NIPS 2014
Proximal Quasi-Newton for Computationally Intensive L1-regularized M-estimators NIPS 2014
Sparse Random Feature Algorithm as Coordinate Descent in Hilbert Space NIPS 2014
QUIC & DIRTY: A Quadratic Approximation Approach for Dirty Statistical Models NIPS 2014
Capturing Semantically Meaningful Word Dependencies with an Admixture of Poisson MRFs NIPS 2014
Large Scale Distributed Sparse Precision Estimation NIPS 2013
Learning with Noisy Labels NIPS 2013
BIG & QUIC: Sparse Inverse Covariance Estimation for a Million Variables NIPS 2013
A Divide-and-Conquer Method for Sparse Inverse Covariance Estimation NIPS 2012
Orthogonal Matching Pursuit with Replacement NIPS 2011
Nearest Neighbor based Greedy Coordinate Descent NIPS 2011
Greedy Algorithms for Structurally Constrained High Dimensional Problems NIPS 2011
Sparse Inverse Covariance Matrix Estimation Using Quadratic Approximation NIPS 2011
Guaranteed Rank Minimization via Singular Value Projection NIPS 2010
Inductive Regularized Learning of Kernel Functions NIPS 2010
Matrix Completion from Power-Law Distributed Samples NIPS 2009
Online Metric Learning and Fast Similarity Search NIPS 2008
Differential Entropic Clustering of Multivariate Gaussians NIPS 2006