Search Results for author: S. Sundararajan

Found 7 papers, 0 papers with code

Distributed Newton Methods for Deep Neural Networks

no code implementations1 Feb 2018 Chien-Chih Wang, Kent Loong Tan, Chun-Ting Chen, Yu-Hsiang Lin, S. Sathiya Keerthi, Dhruv Mahajan, S. Sundararajan, Chih-Jen Lin

First, to reduce the communication cost, we propose a diagonalization method such that an approximate Newton direction can be obtained without communication between machines.

A Sparse Nonlinear Classifier Design Using AUC Optimization

no code implementations27 Dec 2016 Vishal Kakkar, Shirish K. Shevade, S. Sundararajan, Dinesh Garg

Batch learning methods for solving the kernelized version of this problem suffer from scalability and may not result in sparse classifiers.

A Distributed Algorithm for Training Nonlinear Kernel Machines

no code implementations18 May 2014 Dhruv Mahajan, S. Sathiya Keerthi, S. Sundararajan

This paper concerns the distributed training of nonlinear kernel machines on Map-Reduce.

A distributed block coordinate descent method for training $l_1$ regularized linear classifiers

no code implementations18 May 2014 Dhruv Mahajan, S. Sathiya Keerthi, S. Sundararajan

In this paper we design a distributed algorithm for $l_1$ regularization that is much better suited for such systems than existing algorithms.

An efficient distributed learning algorithm based on effective local functional approximations

no code implementations31 Oct 2013 Dhruv Mahajan, Nikunj Agrawal, S. Sathiya Keerthi, S. Sundararajan, Leon Bottou

In this paper we give a novel approach to the distributed training of linear classifiers (involving smooth losses and L2 regularization) that is designed to reduce the total communication costs.

L2 Regularization

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