1.9k citations · 6.5k across the 132 of their papers we have counts for
4 papers · 2 filters
Minimizing The Misclassification Error Rate Using a Surrogate Convex Loss
Shai Ben-David, David Loker, Nathan Srebro +1
We carefully study how well minimizing convex surrogate loss functions, corresponds to minimizing the misclassification error rate for the problem of binary classification with lin…
The Kernelized Stochastic Batch Perceptron
Andrew Cotter, Shai Shalev-Shwartz, Nathan Srebro
We present a novel approach for training kernel Support Vector Machines, establish learning runtime guarantees for our method that are better then those of any other known kerneliz…
Semi-supervised Learning with Density Based Distances
Avleen S. Bijral, Nathan Ratliff, Nathan Srebro
We present a simple, yet effective, approach to Semi-Supervised Learning. Our approach is based on estimating density-based distances (DBD) using a shortest path calculation on a g…
Clustering using Max-norm Constrained Optimization
Ali Jalali, Nathan Srebro
We suggest using the max-norm as a convex surrogate constraint for clustering. We show how this yields a better exact cluster recovery guarantee than previously suggested nuclear-n…