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07/18/2018
Distributed Second-order Convex Optimization
Convex optimization problems arise frequently in diverse machine learnin...
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02/26/2018
GPU Accelerated Sub-Sampled Newton's Method
First order methods, which solely rely on gradient information, are comm...
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02/17/2018
Out-of-sample extension of graph adjacency spectral embedding
Many popular dimensionality reduction procedures have out-of-sample exte...
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11/24/2017
Invariance of Weight Distributions in Rectified MLPs
An interesting approach to analyzing and developing tools for neural net...
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09/11/2017
GIANT: Globally Improved Approximate Newton Method for Distributed Optimization
For distributed computing environments, we consider the canonical machin...
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08/25/2017
Second-Order Optimization for Non-Convex Machine Learning: An Empirical Study
The resurgence of deep learning, as a highly effective machine learning ...
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08/23/2017
Newton-Type Methods for Non-Convex Optimization Under Inexact Hessian Information
We consider variants of trust-region and cubic regularization methods fo...
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05/22/2017
Union of Intersections (UoI) for Interpretable Data Driven Discovery and Prediction
The increasing size and complexity of scientific data could dramatically...
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07/02/2016
Sub-sampled Newton Methods with Non-uniform Sampling
We consider the problem of finding the minimizer of a convex function F:...
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05/26/2016
FLAG n' FLARE: Fast Linearly-Coupled Adaptive Gradient Methods
We consider first order gradient methods for effectively optimizing a co...
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01/18/2016
Sub-Sampled Newton Methods II: Local Convergence Rates
Many data-fitting applications require the solution of an optimization p...
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01/18/2016