Learning to Optimize Neural Nets

1 March 2017

Papers citing "Learning to Optimize Neural Nets"

50 / 70 papers shown

Title
QuickSplat: Fast 3D Surface Reconstruction via Learned Gaussian Initialization Yueh-Cheng Liu Lukas Höllein Matthias Nießner Angela Dai 3DGS 29 0 0 08 May 2025
Optimization Problem Solving Can Transition to Evolutionary Agentic Workflows Wenhao Li Bo Jin Mingyi Hong Changhong Lu Xiangfeng Wang 48 0 0 07 May 2025
Improving Learning to Optimize Using Parameter Symmetries Guy Zamir Aryan Dokania B. Zhao Rose Yu 22 0 0 21 Apr 2025
Reinforcement Teaching Alex Lewandowski Calarina Muslimani Dale Schuurmans Matthew E. Taylor Jun-Jie Luo 81 1 0 28 Jan 2025
Meta-Sparsity: Learning Optimal Sparse Structures in Multi-task Networks through Meta-learning Richa Upadhyay Ronald Phlypo Rajkumar Saini Marcus Liwicki 35 0 0 21 Jan 2025
Large Language Models for Human-Machine Collaborative Particle Accelerator Tuning through Natural Language Jan Kaiser Annika Eichler Anne Lauscher LM&MA 45 4 0 14 May 2024
Learning to optimize with convergence guarantees using nonlinear system theory Andrea Martin Luca Furieri 19 6 0 14 Mar 2024
Dynamic Memory Based Adaptive Optimization Balázs Szegedy Domonkos Czifra Péter Korösi-Szabó ODL 27 0 0 23 Feb 2024
Artificial Intelligence for Operations Research: Revolutionizing the Operations Research Process Zhenan Fan Bissan Ghaddar Xinglu Wang Linzi Xing Yong Zhang Zirui Zhou AI4CE 45 11 0 06 Jan 2024
Subspace Adaptation Prior for Few-Shot Learning Mike Huisman Aske Plaat Jan N. van Rijn VLM 24 2 0 13 Oct 2023
Deep Model Predictive Optimization Jacob Sacks Rwik Rana Kevin Huang Alex Spitzer Guanya Shi Byron Boots 38 7 0 06 Oct 2023
Learning to Do or Learning While Doing: Reinforcement Learning and Bayesian Optimisation for Online Continuous Tuning Jan Kaiser Chenran Xu Annika Eichler Andrea Santamaria Garcia O. Stein ... H. Dinter F. Mayet T. Vinatier F. Burkart H. Schlarb OffRL 14 4 0 06 Jun 2023
HUB: Guiding Learned Optimizers with Continuous Prompt Tuning Gaole Dai Wei Yu Wu Ziyu Wang Jie Fu Shanghang Zhang Tiejun Huang AIFin 14 0 0 26 May 2023
Low-Variance Gradient Estimation in Unrolled Computation Graphs with ES-Single Paul Vicol Zico Kolter Kevin Swersky 13 6 0 21 Apr 2023
Learning To Optimize Quantum Neural Network Without Gradients Ankit Kulshrestha Xiaoyuan Liu Hayato Ushijima-Mwesigwa Ilya Safro 20 5 0 15 Apr 2023
A Nonstochastic Control Approach to Optimization Xinyi Chen Elad Hazan 47 5 0 19 Jan 2023
Federated Automatic Differentiation Keith Rush Zachary B. Charles Zachary Garrett FedML 34 1 0 18 Jan 2023
Learning to Optimize in Model Predictive Control Jacob Sacks Byron Boots 14 22 0 05 Dec 2022
VeLO: Training Versatile Learned Optimizers by Scaling Up Luke Metz James Harrison C. Freeman Amil Merchant Lucas Beyer ... Naman Agrawal Ben Poole Igor Mordatch Adam Roberts Jascha Narain Sohl-Dickstein 29 60 0 17 Nov 2022
Learning to Optimize Quasi-Newton Methods Isaac Liao Rumen Dangovski Jakob N. Foerster Marin Soljacic 36 4 0 11 Oct 2022
Learning to Learn with Generative Models of Neural Network Checkpoints William S. Peebles Ilija Radosavovic Tim Brooks Alexei A. Efros Jitendra Malik UQCV 73 64 0 26 Sep 2022
A Closer Look at Learned Optimization: Stability, Robustness, and Inductive Biases James Harrison Luke Metz Jascha Narain Sohl-Dickstein 44 22 0 22 Sep 2022
Practical tradeoffs between memory, compute, and performance in learned optimizers Luke Metz C. Freeman James Harrison Niru Maheswaranathan Jascha Narain Sohl-Dickstein 33 32 0 22 Mar 2022
Symbolic Learning to Optimize: Towards Interpretability and Scalability Wenqing Zheng Tianlong Chen Ting-Kuei Hu Zhangyang Wang 39 18 0 13 Mar 2022
Amortized Proximal Optimization Juhan Bae Paul Vicol Jeff Z. HaoChen Roger C. Grosse ODL 25 14 0 28 Feb 2022
Tutorial on amortized optimization Brandon Amos OffRL 75 43 0 01 Feb 2022
Unbiased Gradient Estimation in Unrolled Computation Graphs with Persistent Evolution Strategies Paul Vicol Luke Metz Jascha Narain Sohl-Dickstein 19 67 0 27 Dec 2021
Reinforcement Learning based Sequential Batch-sampling for Bayesian Optimal Experimental Design Yonatan Ashenafi Piyush Pandita Sayan Ghosh OffRL 30 6 0 21 Dec 2021
Efficient Meta Subspace Optimization Yoni Choukroun Michael Katz 20 1 0 28 Oct 2021
MetaAlign: Coordinating Domain Alignment and Classification for Unsupervised Domain Adaptation Guoqiang Wei Cuiling Lan Wenjun Zeng Zhibo Chen 13 106 0 25 Mar 2021
Learning to Optimize: A Primer and A Benchmark Tianlong Chen Xiaohan Chen Wuyang Chen Howard Heaton Jialin Liu Zhangyang Wang W. Yin 38 225 0 23 Mar 2021
Meta Learning Backpropagation And Improving It Louis Kirsch Jürgen Schmidhuber 51 56 0 29 Dec 2020
Discriminative Adversarial Domain Generalization with Meta-learning based Cross-domain Validation Keyu Chen Di Zhuang Jerome Chang OOD 6 44 0 01 Nov 2020
Learning to Optimise General TSP Instances N. Sultana Jeffrey Chan •. A. K. Qin Tabinda Sarwar 60 13 0 23 Oct 2020
A Survey of Deep Meta-Learning Mike Huisman Jan N. van Rijn Aske Plaat 17 329 0 07 Oct 2020
Tasks, stability, architecture, and compute: Training more effective learned optimizers, and using them to train themselves Luke Metz Niru Maheswaranathan C. Freeman Ben Poole Jascha Narain Sohl-Dickstein 22 62 0 23 Sep 2020
Efficient Reinforcement Learning Development with RLzoo Zihan Ding Tianyang Yu Yanhua Huang Hongming Zhang Guo Li Quancheng Guo Luo Mai Hao Dong OffRL OnRL 13 6 0 18 Sep 2020
Learning to Learn from Mistakes: Robust Optimization for Adversarial Noise A. Serban E. Poll Joost Visser AAML 18 0 0 12 Aug 2020
MLR-SNet: Transferable LR Schedules for Heterogeneous Tasks Jun Shu Yanwen Zhu Qian Zhao Zongben Xu Deyu Meng 18 7 0 29 Jul 2020
Learning Surrogates via Deep Embedding Yash J. Patel Tomás Hodan Jirí Matas 16 15 0 01 Jul 2020
Guarantees for Tuning the Step Size using a Learning-to-Learn Approach Xiang Wang Shuai Yuan Chenwei Wu Rong Ge 8 16 0 30 Jun 2020
Language Models are Few-Shot Learners Tom B. Brown Benjamin Mann Nick Ryder Melanie Subbiah Jared Kaplan ... Christopher Berner Sam McCandlish Alec Radford Ilya Sutskever Dario Amodei BDL 15 39,979 0 28 May 2020
Using a thousand optimization tasks to learn hyperparameter search strategies Luke Metz Niru Maheswaranathan Ruoxi Sun C. Freeman Ben Poole Jascha Narain Sohl-Dickstein 15 45 0 27 Feb 2020
MetalGAN: Multi-Domain Label-Less Image Synthesis Using cGANs and Meta-Learning Tomaso Fontanini Eleonora Iotti Luca Donati Andrea Prati GAN AI4CE 26 23 0 05 Dec 2019
Pyramid Convolutional RNN for MRI Image Reconstruction Eric Z. Chen Puyang Wang Xiao Chen Terrence Chen Shanhui Sun 13 41 0 02 Dec 2019
When MAML Can Adapt Fast and How to Assist When It Cannot Sébastien M. R. Arnold Shariq Iqbal Fei Sha 17 5 0 30 Oct 2019
Learning to Learn by Zeroth-Order Oracle Yangjun Ruan Yuanhao Xiong Sashank J. Reddi Sanjiv Kumar Cho-Jui Hsieh 14 17 0 21 Oct 2019
Improving Generalization in Meta Reinforcement Learning using Learned Objectives Louis Kirsch Sjoerd van Steenkiste Jürgen Schmidhuber OffRL 14 118 0 09 Oct 2019
Meta-Inverse Reinforcement Learning with Probabilistic Context Variables Lantao Yu Tianhe Yu Chelsea Finn Stefano Ermon OffRL BDL 17 71 0 20 Sep 2019
MetalGAN: a Cluster-based Adaptive Training for Few-Shot Adversarial Colorization Tomaso Fontanini Eleonora Iotti Andrea Prati GAN 31 4 0 17 Sep 2019