Hybrid Approximate Gradient and Stochastic Descent for Falsification of Nonlinear Systems Shakiba Yaghoubi and Georgios Fainekos Abstract— Studying transient properties of nonlinear systems is an important problem for

Source URL: www.public.asu.edu

• Applied mathematics
• Electrical engineering
• Epistemology
• Control engineering
• Control theory
• Cybernetics
• Global optimization
• Falsifiability
• Linear time-invariant system
• PROPT
• Conjugate gradient method

Understanding and Optimizing Asynchronous Low-Precision Stochastic Gradient Descent Christopher De Sa Matthew Feldman Christopher Ré Kunle Olukotun Departments of Electrical Engineering and Computer Science Stanford Uni

Source URL: www.cs.cornell.edu

MAP estimate on GLMs Stochastic Gradient Descent (SGD) MAP to Bayesian Inference

Source URL: emtiyaz.github.io

Stochastic Gradient Descent Training for L1-regularized Log-linear Models with Cumulative Penalty Yoshimasa Tsuruoka†‡ Jun’ichi Tsujii†‡∗ Sophia Ananiadou†‡ †

Source URL: aclweb.org

Accelerated Stochastic Gradient Descent

Source URL: ljk.imag.fr

Stochastic Gradient Descent Tricks L´eon Bottou Microsoft Research, Redmond, WA http://leon.bottou.org

Source URL: cilvr.cs.nyu.edu

Parallelized Stochastic Gradient Descent Markus Weimer Yahoo! Labs Sunnyvale, CA 94089

Source URL: www.research.rutgers.edu

Accelerating Stochastic Gradient Descent using Predictive Variance Reduction Rie Johnson RJ Research Consulting Tarrytown NY, USA

Source URL: papers.nips.cc

SpeeDO: Parallelizing Stochastic Gradient Descent for Deep Convolutional Neural Network Zhongyang Zheng HTC Research Beijing, China

Source URL: learningsys.org

Mittagsseminar Natural Gradient in Evolution Strategies Sebastian U. Stich ETH Z¨ urich

Source URL: sstich.ch

• Numerical analysis
• Mathematical analysis
• Mathematics
• Evolutionary algorithms
• Stochastic optimization
• Ensemble learning
• Natural evolution strategy
• Mathematical optimization
• Gradient descent
• AdaBoost
• Gradient