Inderjit S. Dhillon

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