NIPS Proceedings
^{β}
Books
Nati Srebro
23 Papers
Graph Oracle Models, Lower Bounds, and Gaps for Parallel Stochastic Optimization
(2018)
Implicit Bias of Gradient Descent on Linear Convolutional Networks
(2018)
On preserving non-discrimination when combining expert advice
(2018)
The Everlasting Database: Statistical Validity at a Fair Price
(2018)
Exploring Generalization in Deep Learning
(2017)
Implicit Regularization in Matrix Factorization
(2017)
Stochastic Approximation for Canonical Correlation Analysis
(2017)
The Marginal Value of Adaptive Gradient Methods in Machine Learning
(2017)
Efficient Globally Convergent Stochastic Optimization for Canonical Correlation Analysis
(2016)
Equality of Opportunity in Supervised Learning
(2016)
Global Optimality of Local Search for Low Rank Matrix Recovery
(2016)
Normalized Spectral Map Synchronization
(2016)
Path-Normalized Optimization of Recurrent Neural Networks with ReLU Activations
(2016)
Tight Complexity Bounds for Optimizing Composite Objectives
(2016)
Path-SGD: Path-Normalized Optimization in Deep Neural Networks
(2015)
Stochastic Gradient Descent, Weighted Sampling, and the Randomized Kaczmarz algorithm
(2014)
Auditing: Active Learning with Outcome-Dependent Query Costs
(2013)
Stochastic Optimization of PCA with Capped MSG
(2013)
The Power of Asymmetry in Binary Hashing
(2013)
Beating SGD: Learning SVMs in Sublinear Time
(2011)
Better Mini-Batch Algorithms via Accelerated Gradient Methods
(2011)
Learning with the weighted trace-norm under arbitrary sampling distributions
(2011)
On the Universality of Online Mirror Descent
(2011)