Inderjit S. Dhillon

40 papers · 2003–2023 · 8 conferences · across top CS/AI conferences

Achievements

+15 more ↓

🗺️ Taxonomy Completionist (23) 🧭 Keyword Pioneer 🌉 Interdisciplinary Bridge 🌈 Renaissance Researcher (5) 🐣 Hot Topic Early Bird

🐣 Hot Topic Early Bird 🌉 Interdisciplinary Bridge 🧭 Keyword Pioneer 🌟 Keyword Trendsetter Combo (6) 🤝 Dynamic Duo (17) 🔬 Deep Specialist (11) 🏆 Grand Slam 🌱 Topic Pioneer 🏆 Keyword Champion (2) 🔥 Unstoppable (5) ⚡ Prolific Year (5) 📈 Trend Setter 🗃️ Keyword Collector (103) 🚀 Conference Pioneer 💎 Century Club (40)

Conferences

NIPS (17) JMLR (11) ICML (5) AISTATS (3) AAAI (1) ICLR (1) IJCAI (1) UAI (1)

Top co-authors

Inderjit S Dhillon (17) Cho-jui Hsieh (14) Prateek Jain (9) Hsiang-Fu Yu (6) Ambuj Tewari (5) Pradeep K Ravikumar (4) Sujay Sanghavi (4) Pradeep K. Ravikumar (4) Brian Kulis (4) Arindam Banerjee (3)

Keywords

convex optimization (5) matrix completion (4) kernel matrix (4) low-rank matrix (4) sparse inverse covariance (3) metric learning (3) sparse optimization (3) multi-label classification (3) extreme multi-label classification (3) low-rank approximation (3) online learning (3) bregman divergence (3) gaussian markov random field (3) coordinate descent (2) information theory (2) mahalanobis distance (2) empirical risk minimization (2) dimensionality reduction (2) kernel learning (2) matrix factorization (2)

Papers

A Computationally Efficient Sparsified Online Newton Method NIPS 2023 Sample Efficiency of Data Augmentation Consistency Regularization AISTATS 2023 Block Low-Rank Preconditioner with Shared Basis for Stochastic Optimization NIPS 2023 Faster non-convex federated learning via global and local momentum UAI 2022 S3GC: Scalable Self-Supervised Graph Clustering NIPS 2022 ELIAS: End-to-End Learning to Index and Search in Large Output Spaces NIPS 2022 Robust Training in High Dimensions via Block Coordinate Geometric Median Descent AISTATS 2022 Linear Bandit Algorithms with Sublinear Time Complexity ICML 2022 PECOS: Prediction for Enormous and Correlated Output Spaces JMLR 2022 Top-k eXtreme Contextual Bandits with Arm Hierarchy ICML 2021 Fast Multi-Resolution Transformer Fine-tuning for Extreme Multi-label Text Classification NIPS 2021 Label Disentanglement in Partition-based Extreme Multilabel Classification NIPS 2021 DRONE: Data-aware Low-rank Compression for Large NLP Models NIPS 2021 Learning from eXtreme Bandit Feedback AAAI 2021 Parallel Asynchronous Stochastic Coordinate Descent with Auxiliary Variables AISTATS 2019 The Limitations of Adversarial Training and the Blind-Spot Attack ICLR 2019 Similarity Preserving Representation Learning for Time Series Clustering IJCAI 2019 Cost-Sensitive Learning with Noisy Labels JMLR 2018 Using Side Information to Reliably Learn Low-Rank Matrices from Missing and Corrupted Observations JMLR 2018 Memory Efficient Kernel Approximation JMLR 2017 Doubly Greedy Primal-Dual Coordinate Descent for Sparse Empirical Risk Minimization ICML 2017 Gradient Boosted Decision Trees for High Dimensional Sparse Output ICML 2017 Recovery Guarantees for One-hidden-layer Neural Networks ICML 2017 Prediction and Clustering in Signed Networks: A Local to Global Perspective JMLR 2014 QUIC: Quadratic Approximation for Sparse Inverse Covariance Estimation JMLR 2014 A Divide-and-Conquer Method for Sparse Inverse Covariance Estimation NIPS 2012 Metric and Kernel Learning Using a Linear Transformation JMLR 2012 Greedy Algorithms for Structurally Constrained High Dimensional Problems NIPS 2011 Orthogonal Matching Pursuit with Replacement NIPS 2011 Sparse Inverse Covariance Matrix Estimation Using Quadratic Approximation NIPS 2011 Nearest Neighbor based Greedy Coordinate Descent NIPS 2011 Inductive Regularized Learning of Kernel Functions NIPS 2010 Guaranteed Rank Minimization via Singular Value Projection NIPS 2010 Matrix Completion from Power-Law Distributed Samples NIPS 2009 Low-Rank Kernel Learning with Bregman Matrix Divergences JMLR 2009 Online Metric Learning and Fast Similarity Search NIPS 2008 Differential Entropic Clustering of Multivariate Gaussians NIPS 2006 Clustering with Bregman Divergences JMLR 2005 Clustering on the Unit Hypersphere using von Mises-Fisher Distributions JMLR 2005 A Divisive Information-Theoretic Feature Clustering Algorithm for Text Classification JMLR 2003