NIPS Proceedings
^{β}
Books
Inderjit S. Dhillon
28 Papers
AutoAssist: A Framework to Accelerate Training of Deep Neural Networks
(2019)
Inverting Deep Generative models, One layer at a time
(2019)
Primal-Dual Block Generalized Frank-Wolfe
(2019)
Provable Non-linear Inductive Matrix Completion
(2019)
Think Globally, Act Locally: A Deep Neural Network Approach to High-Dimensional Time Series Forecasting
(2019)
A Greedy Approach for Budgeted Maximum Inner Product Search
(2017)
Asynchronous Parallel Greedy Coordinate Descent
(2016)
Coordinate-wise Power Method
(2016)
Dual Decomposed Learning with Factorwise Oracle for Structural SVM of Large Output Domain
(2016)
Mixed Linear Regression with Multiple Components
(2016)
Structured Sparse Regression via Greedy Hard Thresholding
(2016)
Temporal Regularized Matrix Factorization for High-dimensional Time Series Prediction
(2016)
Collaborative Filtering with Graph Information: Consistency and Scalable Methods
(2015)
Consistent Multilabel Classification
(2015)
Fixed-Length Poisson MRF: Adding Dependencies to the Multinomial
(2015)
Matrix Completion with Noisy Side Information
(2015)
Sparse Linear Programming via Primal and Dual Augmented Coordinate Descent
(2015)
Capturing Semantically Meaningful Word Dependencies with an Admixture of Poisson MRFs
(2014)
Consistent Binary Classification with Generalized Performance Metrics
(2014)
Constant Nullspace Strong Convexity and Fast Convergence of Proximal Methods under High-Dimensional Settings
(2014)
Fast Prediction for Large-Scale Kernel Machines
(2014)
Multi-Scale Spectral Decomposition of Massive Graphs
(2014)
Proximal Quasi-Newton for Computationally Intensive L1-regularized M-estimators
(2014)
QUIC & DIRTY: A Quadratic Approximation Approach for Dirty Statistical Models
(2014)
Sparse Random Feature Algorithm as Coordinate Descent in Hilbert Space
(2014)
BIG & QUIC: Sparse Inverse Covariance Estimation for a Million Variables
(2013)
Large Scale Distributed Sparse Precision Estimation
(2013)
Learning with Noisy Labels
(2013)