99 citations · 600 across the 38 of their papers we have counts for
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A Stochastic Trust Region Algorithm Based on Careful Step Normalization
Frank E. Curtis, Katya Scheinberg, Rui Shi
An algorithm is proposed for solving stochastic and finite sum minimization problems. Based on a trust region methodology, the algorithm employs normalized steps, at least as long…
Smooth Pinball Neural Network for Probabilistic Forecasting of Wind Power
Kostas Hatalis, Alberto J. Lamadrid, Katya Scheinberg +1
Uncertainty analysis in the form of probabilistic forecasting can significantly improve decision making processes in the smart power grid for better integrating renewable energy so…
Optimization Methods for Supervised Machine Learning: From Linear Models to Deep Learning
Frank E. Curtis, Katya Scheinberg
The goal of this tutorial is to introduce key models, algorithms, and open questions related to the use of optimization methods for solving problems arising in machine learning. It…
Stochastic Recursive Gradient Algorithm for Nonconvex Optimization
Lam M. Nguyen, Jie Liu, Katya Scheinberg +1
In this paper, we study and analyze the mini-batch version of StochAstic Recursive grAdient algoritHm (SARAH), a method employing the stochastic recursive gradient, for solving emp…
Black-Box Optimization in Machine Learning with Trust Region Based Derivative Free Algorithm
Hiva Ghanbari, Katya Scheinberg
In this work, we utilize a Trust Region based Derivative Free Optimization (DFO-TR) method to directly maximize the Area Under Receiver Operating Characteristic Curve (AUC), which…
SARAH: A Novel Method for Machine Learning Problems Using Stochastic Recursive Gradient
Lam M. Nguyen, Jie Liu, Katya Scheinberg +1
In this paper, we propose a StochAstic Recursive grAdient algoritHm (SARAH), as well as its practical variant SARAH+, as a novel approach to the finite-sum minimization problems. D…