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

Distributed Gradient Descent in Bacterial Food Search Shashank Singh∗1 , Sabrina Rashid∗2 , Saket Navlakha3 , Ziv Bar-Joseph4† 1 Machine Learning Department and Department of Statistics, Carnegie Mellon University,

Source URL: www.snl.salk.edu

Stat 928: Statistical Learning Theory Lecture: 22 Exponentiated Gradient Descent Instructor: Sham Kakade

Source URL: stat.wharton.upenn.edu

Pattern Recognition And Machine Learning - EPFL - Fall 2015 Emtiyaz Khan, Timur Bagautdinov, Carlos Becker, Ilija Bogunovic & Ksenia Konyushkova 2. Linear Regression and Gradient Descent 2.1

Source URL: emtiyaz.github.io

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

Source URL: emtiyaz.github.io

Vector Derivatives, Gradients, and Generalized Gradient Descent Algorithms ECE 275A – Statistical Parameter Estimation Ken Kreutz-Delgado ECE Department, UC San Diego

Source URL: dsp.ucsd.edu

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