Topic 187: Optimization 109


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Convex Optimization: Algorithms and Complexity Sebastien Bubeck 2015
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Tutorial on: Optimization I Jimmy Ba 2018
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Optimizing inputs François Fleuret 2019
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Optimization Razvan C. Bunescu 2017
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Training and Optimization Stephen Clark 2017
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Gradient, Subgradient and how they may affect your grade(ient) David Sontag 2016
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Loss and risk François Fleuret 2019
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Regularization and optimization Sida Wang 2018
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Optimization Roger Grosse 2018
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Gradient descent François Fleuret 2019
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Advanced training Svetlana Lazebnik 2018
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Bayesian Hyperparameter Optimization Roger Grosse 2018
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Mathematics for Machine Learning: Continuous Optimization Marc Peter Deisenroth, A Aldo Faisal, Cheng Soon Ong 2018
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Optimization for ML Matt Gormley 2016
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Back-propagation François Fleuret 2019
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Baum-Welch and Entropic Training Ricardo Gutierrez-Osuna 2013
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Autograd François Fleuret 2019
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Optimization for Deep Learning Yangfeng Ji 2018
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Stochastic Gradient Descent David McAllester 2017
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Writing an autograd function François Fleuret 2019
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Generalization and Regularization Xavier Bresso 2017
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Deeper into Deep Learning and Optimizations Efstratios Gavves 2018
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Looking at parameters François Fleuret 2019
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Optimization Algorithms Kian Katanforoosh 2018
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Training neural networks - optimization Hugo Larochelle 2017
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Looking at activations François Fleuret 2019
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Optimization and Neural Nets Pieter Abbeel, Dan Klein 2018
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Training neural networks - backpropagation algorithm Hugo Larochelle 2017
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Optimization: Part II Jorge Nocedal 2018
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Visualizing the processing in the input François Fleuret 2019
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(Sub)gradient Descent Furong Huang 2018
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Statistical machine learning and convex optimization Francis Bach 2018
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Title (link) Author Date Votes Error
Convex Optimization – Boyd and Vandenberghe Stephen Boyd, Lieven Vandenberghe 2014
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Additional Exercises for Convex Optimization Stephen Boyd, Lieven Vandenberghe 2017
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Matrix and Tensor Factorization R Tutorial Dr. Panagiotis Symeonidis 2016
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Convex Optimization Stephen Boyd, Lieven Vandenberghe 2017
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Convex Optimization Slides Stephen Boyd, Lieven Vandenberghe 2017
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An overview of gradient descent optimization algorithms Sebastian Ruder 2017
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Hyperparameter Optimization Matthias Feurer, Frank Hutter 2018
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Auto-WEKA: Automatic model selection and hyperparameter optimization in WEKA Lars Kotthoff, Chris Thornton, Holger H. Hoos, Frank Hutter, Kevin Leyton-Brown 2018
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Convex Optimization Overview Zico Kolter 2007
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Chapter 6: Optimization from Numerical Python Robert Johansson 2017
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Nevergrad: An open source tool for derivative-free optimization Olivier Teytaud, Jeremy Rapin 2018
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PPO2 John Schulman, Filip Wolski, Prafulla Dhariwal, Alec Radford, Oleg Klimov 2017
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Adam — latest trends in deep learning optimization Vitaly Bushaev 2018
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Deep Learning 14 : Optimization, an Overview Irene Li 2016
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Linear Regression using Gradient Descent Adarsh Menon 2018
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Adam Optimization algorithms in Deep Learning Deepak Battini 2018
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How to Escape Saddle Points Efficiently Chi Jin*, Rong Ge, Praneeth Netrapalli , Sham M. Kakade, Michael I. Jordan 2017
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Implementation of Gradient Descent in Python Deepak Battini 2018
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Laplacian Solvers and Their Algorithmic Applications Nisheeth K. Vishnoi 2012
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Understanding Hyperparameters Optimization in Deep Learning Models: Concepts and Tools Jesus Rodriguez 2018
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Gradient Descent Algorithm and Its Variants Imad Dabbura 2017
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Optimization in Python cookbook: bowl, plate and valley functions Alexandr Honchar 2018
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Can increasing depth serve to accelerate optimization? Nadav Cohen 2018
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Normalization in Gradient`s Point of View [ Manual Back Prop in TF ] Jae Duk Seo 2018
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An overview of gradient descent optimization algorithms Sebastian Ruder 2016
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Understanding the 3 Primary Types of Gradient Descent Daniel Gutierrez 2018
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Introduction to Optimization with Genetic Algorithm Ahmed Gad 2018
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How optimization for machine learning works, Part 1 Brandon 2018
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Gradient descent with Python Adrian Rosebrock 2016
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The intuitions behind Bayesian Optimization with Gaussian Processes Charles Brecque 2018
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Optimizers N/A 2019
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Optimizing Decision-making with the Minimax AI algorithm Shukant Pal 2019
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Entraînement : Optimisation continue Nicolas Le Roux 2018
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Optimization methods for machine learning Part 1 Jorge Nocedal 2012
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Optimization for Deep Learning Sebastian Ruder 2017
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Bayesian Optimization For Automated Model Selection Gustavo Malkomes, Chip Schaff, Roman Garnett 2017
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An overview of gradient descent optimization algorithms Sebastian Ruder 2017
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ConvNetJS Trainer demo on MNIST Andrej Karpathy 2013
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Meta-Learning Symposium Risto Miikkulainen, Quoc Le, Kenneth Stanley, Chrisantha Fernando 2017
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Gentle Introduction to the Adam Optimization Algorithm for Deep Learning Jason Brownlee 2017
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Evolving Multitask Neural Network Structure Risto Miikkulainen 2017
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Optimization for Machine Learning (Lecture 1) Suvrit Sra 2017
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Keep it simple! How to understand Gradient Descent algorithm Jahnavi Mahanta 2017
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Optimization for Machine Learning (Lecture 2) Suvrit Sra 2017
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Stochastic Gradient Methods for Large-Scale Machine Learning Leon Bottou, Frank E. Curtis, Jorge Nocedal 2016
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Optimization as a Model for Few-Shot Learning Hugo Larochelle 2017
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Optimization Algorithms Andrew Ng 2019
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Optimization for Machine Learning (Lecture 3a) Suvrit Sra 2017
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Optimization Methods for Machine Learning Part II – The theory of SG Leon Bottou, Frank E. Curtis, Jorge Nocedal 2016
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Guide to Gradient Descent in 3 Steps and 12 Drawings Charles Bordet 2018
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Hyperparameter tuning Andrew Ng 2019
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Optimization for Machine Learning (Lecture 3b) Suvrit Sra 2017
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Beyond SG: Noise Reduction and Second-Order Methods Leon Bottou, Frank E. Curtis, Jorge Nocedal 2016
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Gradients, Batch Normalization, and Layer Normalization Goku Mohandas 2016
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Optimization, regularization for NN Suriya Gunasekar 2018
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Tutorial on Optimization methods for machine learning Jorge Nocedal 2012
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Tutorial: PART 1 Optimization for machine learning Elad Hazan 2017
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Tutorial: Optimization for Machine Learning Elad Hazan 2018
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Question Answering from Unstructured Text by Retrieval and Comprehension Goku Mohandas 2017
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Expectation Maximization (EM) Karl Stratos 2018
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Sparse and Regularized Optimization Stephen Wright 2012
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Tutorial: PART 2 Optimization for machine learning Elad Hazan 2017
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Optimizing Human Language Learning Masato Hagiwara 2018
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Introduction to Gradient Descent Algorithm (along with variants) in Machine Learning Faizan Shaikh 2017
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Some Relevant Topics in Optimization Stephen Wright 2012
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The Beginner’s Guide to Gradient Descent Chi-Feng Wang 2018
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An overview of the Gradient Descent algorithm Nishit Jain 2019
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Types of Optimization Algorithms used in Neural Networks and Ways to Optimize Gradient Descent Anish Singh Walia 2017
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Sparse and Regularized Optimization Part 2 Stephen Wright 2012
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