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09/06/2023
Adaptive Consensus: A network pruning approach for decentralized optimization
We consider network-based decentralized optimization problems, where eac...
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01/01/2023
A Sequential Quadratic Programming Method with High Probability Complexity Bounds for Nonlinear Equality Constrained Stochastic Optimization
A step-search sequential quadratic programming method is proposed for so...
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06/24/2021
A Stochastic Sequential Quadratic Optimization Algorithm for Nonlinear Equality Constrained Optimization with Rank-Deficient Jacobians
A sequential quadratic optimization algorithm is proposed for solving sm...
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06/06/2020
SONIA: A Symmetric Blockwise Truncated Optimization Algorithm
This work presents a new algorithm for empirical risk minimization. The ...
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06/02/2020
Finite Difference Neural Networks: Fast Prediction of Partial Differential Equations
Discovering the underlying behavior of complex systems is an important t...
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05/30/2019
Scaling Up Quasi-Newton Algorithms: Communication Efficient Distributed SR1
In this paper, we present a scalable distributed implementation of the s...
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05/29/2019
Linear interpolation gives better gradients than Gaussian smoothing in derivative-free optimization
In this paper, we consider derivative free optimization problems, where ...
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01/28/2019
Quasi-Newton Methods for Deep Learning: Forget the Past, Just Sample
We present two sampled quasi-Newton methods for deep learning: sampled L...
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07/26/2017
A Robust Multi-Batch L-BFGS Method for Machine Learning
This paper describes an implementation of the L-BFGS method designed to ...
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05/17/2017
An Investigation of Newton-Sketch and Subsampled Newton Methods
The concepts of sketching and subsampling have recently received much at...
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05/19/2016
A Multi-Batch L-BFGS Method for Machine Learning
The question of how to parallelize the stochastic gradient descent (SGD)...
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11/04/2015