173 citations · 876 across the 56 of their papers we have counts for
4 papers · 1 filter
Quasi-Monte Carlo Feature Maps for Shift-Invariant Kernels
Haim Avron, Vikas Sindhwani, Jiyan Yang +1
We consider the problem of improving the efficiency of randomized Fourier feature maps to accelerate training and testing speed of kernel methods on large datasets. These approxima…
Learning Machines Implemented on Non-Deterministic Hardware
Suyog Gupta, Vikas Sindhwani, Kailash Gopalakrishnan
This paper highlights new opportunities for designing large-scale machine learning systems as a consequence of blurring traditional boundaries that have allowed algorithm designers…
High-performance Kernel Machines with Implicit Distributed Optimization and Randomization
Vikas Sindhwani, Haim Avron
In order to fully utilize "big data", it is often required to use "big models". Such models tend to grow with the complexity and size of the training data, and do not make strong p…
Scalable Matrix-valued Kernel Learning for High-dimensional Nonlinear Multivariate Regression and Granger Causality
Vikas Sindhwani, Ha Quang Minh, Aurelie Lozano
We propose a general matrix-valued multiple kernel learning framework for high-dimensional nonlinear multivariate regression problems. This framework allows a broad class of mixed…