NIPS Proceedings
^{β}
Books
Nati Srebro
18 Papers
Exploring Generalization in Deep Learning
(2017)
Implicit Regularization in Matrix Factorization
(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)