A Survey of Optimization Methods from a Machine Learning Perspective

17 June 2019

Papers citing "A Survey of Optimization Methods from a Machine Learning Perspective"

25 / 25 papers shown

Title
A Balanced Approach of Rapid Genetic Exploration and Surrogate Exploitation for Hyperparameter Optimization Chul Kim Inwhee Joe 45 2 0 10 Apr 2025
Unleashing the Potential of Large Language Models as Prompt Optimizers: Analogical Analysis with Gradient-based Model Optimizers Xinyu Tang Xiaolei Wang Wayne Xin Zhao Siyuan Lu Yaliang Li Ji-Rong Wen LRM 74 16 0 28 Jan 2025
Toward Automated Algorithm Design: A Survey and Practical Guide to Meta-Black-Box-Optimization Zeyuan Ma Hongshu Guo Yue-Jiao Gong Jun Zhang Kay Chen Tan 208 4 0 01 Nov 2024
A Full Adagrad algorithm with O(Nd) operations Antoine Godichon-Baggioni Wei Lu Bruno Portier ODL 70 0 0 03 May 2024
Recent Advances in Recurrent Neural Networks Hojjat Salehinejad Sharan Sankar Joseph Barfett E. Colak S. Valaee AI4TS 79 578 0 29 Dec 2017
Non-convex Optimization for Machine Learning Prateek Jain Purushottam Kar 100 480 0 21 Dec 2017
Improving Generalization Performance by Switching from Adam to SGD N. Keskar R. Socher ODL 64 522 0 20 Dec 2017
Deep Reinforcement Learning: An Overview Yuxi Li OffRL VLM 134 1,517 0 25 Jan 2017
Photo-Realistic Single Image Super-Resolution Using a Generative Adversarial Network C. Ledig Lucas Theis Ferenc Huszár Jose Caballero Andrew Cunningham ... Andrew P. Aitken Alykhan Tejani J. Totz Zehan Wang Wenzhe Shi GAN 229 10,646 0 15 Sep 2016
Sub-sampled Newton Methods with Non-uniform Sampling Peng Xu Jiyan Yang Farbod Roosta-Khorasani Christopher Ré Michael W. Mahoney 45 115 0 02 Jul 2016
Learning to learn by gradient descent by gradient descent Marcin Andrychowicz Misha Denil Sergio Gomez Colmenarejo Matthew W. Hoffman David Pfau Tom Schaul Brendan Shillingford Nando de Freitas 77 2,000 0 14 Jun 2016
Matching Networks for One Shot Learning Oriol Vinyals Charles Blundell Timothy Lillicrap Koray Kavukcuoglu Daan Wierstra VLM 280 7,286 0 13 Jun 2016
Pixel Recurrent Neural Networks Aaron van den Oord Nal Kalchbrenner Koray Kavukcuoglu SSeg GAN 382 2,563 0 25 Jan 2016
Continuous control with deep reinforcement learning Timothy Lillicrap Jonathan J. Hunt Alexander Pritzel N. Heess Tom Erez Yuval Tassa David Silver Daan Wierstra 171 13,174 0 09 Sep 2015
DRAW: A Recurrent Neural Network For Image Generation Karol Gregor Ivo Danihelka Alex Graves Danilo Jimenez Rezende Daan Wierstra GAN DRL 142 1,959 0 16 Feb 2015
Memory Networks Jason Weston S. Chopra Antoine Bordes GNN KELM 117 1,702 0 15 Oct 2014
SAGA: A Fast Incremental Gradient Method With Support for Non-Strongly Convex Composite Objectives Aaron Defazio Francis R. Bach Simon Lacoste-Julien ODL 95 1,817 0 01 Jul 2014
A Stochastic Quasi-Newton Method for Large-Scale Optimization R. Byrd Samantha Hansen J. Nocedal Y. Singer ODL 68 470 0 27 Jan 2014
Gaussian Processes for Big Data J. Hensman Nicolò Fusi Neil D. Lawrence GP 77 1,226 0 26 Sep 2013
Minimizing Finite Sums with the Stochastic Average Gradient Mark Schmidt Nicolas Le Roux Francis R. Bach 241 1,245 0 10 Sep 2013
ADADELTA: An Adaptive Learning Rate Method Matthew D. Zeiler ODL 101 6,619 0 22 Dec 2012
Low-rank Matrix Completion using Alternating Minimization Prateek Jain Praneeth Netrapalli Sujay Sanghavi 134 1,066 0 03 Dec 2012
Stochastic Variational Inference Matt Hoffman David M. Blei Chong-Jun Wang John Paisley BDL 182 2,605 0 29 Jun 2012
Bayesian Posterior Sampling via Stochastic Gradient Fisher Scoring S. Ahn Anoop Korattikara Balan Max Welling 51 305 0 27 Jun 2012
The No-U-Turn Sampler: Adaptively Setting Path Lengths in Hamiltonian Monte Carlo Matthew D. Hoffman Andrew Gelman 128 4,275 0 18 Nov 2011