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Online Learning Rate Adaptation with Hypergradient Descent

Online Learning Rate Adaptation with Hypergradient Descent

14 March 2017
A. G. Baydin
R. Cornish
David Martínez-Rubio
Mark W. Schmidt
Frank Wood
    ODL
ArXivPDFHTML

Papers citing "Online Learning Rate Adaptation with Hypergradient Descent"

50 / 57 papers shown
Title
B-STaR: Monitoring and Balancing Exploration and Exploitation in Self-Taught Reasoners
B-STaR: Monitoring and Balancing Exploration and Exploitation in Self-Taught Reasoners
Weihao Zeng
Yuzhen Huang
Lulu Zhao
Yijun Wang
Zifei Shan
Junxian He
LRM
55
9
0
23 Dec 2024
DeepMpMRI: Tensor-decomposition Regularized Learning for Fast and High-Fidelity Multi-Parametric Microstructural MR Imaging
DeepMpMRI: Tensor-decomposition Regularized Learning for Fast and High-Fidelity Multi-Parametric Microstructural MR Imaging
Wen-Jie Fan
Jian Cheng
Qiyuan Tian
Xinrui Ma
Jing Yang
J. Zou
Shanshan Wang
MedIm
32
1
0
06 May 2024
Downstream Task Guided Masking Learning in Masked Autoencoders Using Multi-Level Optimization
Downstream Task Guided Masking Learning in Masked Autoencoders Using Multi-Level Optimization
Han Guo
Ramtin Hosseini
Ruiyi Zhang
Sai Ashish Somayajula
Ranak Roy Chowdhury
Rajesh K. Gupta
Pengtao Xie
39
0
0
28 Feb 2024
Tuning-Free Stochastic Optimization
Tuning-Free Stochastic Optimization
Ahmed Khaled
Chi Jin
32
7
0
12 Feb 2024
MADA: Meta-Adaptive Optimizers through hyper-gradient Descent
MADA: Meta-Adaptive Optimizers through hyper-gradient Descent
Kaan Ozkara
Can Karakus
Parameswaran Raman
Mingyi Hong
Shoham Sabach
B. Kveton
V. Cevher
27
2
0
17 Jan 2024
SCoTTi: Save Computation at Training Time with an adaptive framework
SCoTTi: Save Computation at Training Time with an adaptive framework
Ziyu Li
Enzo Tartaglione
Van-Tam Nguyen
42
0
0
19 Dec 2023
Learning How to Propagate Messages in Graph Neural Networks
Learning How to Propagate Messages in Graph Neural Networks
Teng Xiao
Zhengyu Chen
Donglin Wang
Suhang Wang
GNN
34
76
0
01 Oct 2023
Differentiable Arbitrating in Zero-sum Markov Games
Differentiable Arbitrating in Zero-sum Markov Games
Jing Wang
Meichen Song
Feng Gao
Boyi Liu
Zhaoran Wang
Yi Wu
43
2
0
20 Feb 2023
Contrastive Learning with Consistent Representations
Contrastive Learning with Consistent Representations
Zihu Wang
Yu Wang
Hanbin Hu
Peng Li
CLL
32
5
0
03 Feb 2023
QLABGrad: a Hyperparameter-Free and Convergence-Guaranteed Scheme for
  Deep Learning
QLABGrad: a Hyperparameter-Free and Convergence-Guaranteed Scheme for Deep Learning
Minghan Fu
Fang-Xiang Wu
ODL
24
7
0
01 Feb 2023
Online Loss Function Learning
Online Loss Function Learning
Christian Raymond
Qi Chen
Bing Xue
Mengjie Zhang
38
5
0
30 Jan 2023
Read the Signs: Towards Invariance to Gradient Descent's Hyperparameter
  Initialization
Read the Signs: Towards Invariance to Gradient Descent's Hyperparameter Initialization
Davood Wadi
M. Fredette
S. Sénécal
ODL
AI4CE
8
0
0
24 Jan 2023
A Nonstochastic Control Approach to Optimization
A Nonstochastic Control Approach to Optimization
Xinyi Chen
Elad Hazan
47
5
0
19 Jan 2023
Federated Automatic Differentiation
Federated Automatic Differentiation
Keith Rush
Zachary B. Charles
Zachary Garrett
FedML
34
1
0
18 Jan 2023
Federated Hypergradient Descent
Federated Hypergradient Descent
A. K. Kan
FedML
39
3
0
03 Nov 2022
Differentiable Self-Adaptive Learning Rate
Differentiable Self-Adaptive Learning Rate
Bozhou Chen
Hongzhi Wang
Chenmin Ba
ODL
22
4
0
19 Oct 2022
On Stability and Generalization of Bilevel Optimization Problem
Meng Ding
Ming Lei
Yunwen Lei
Di Wang
Jinhui Xu
32
1
0
03 Oct 2022
Learning to Learn with Generative Models of Neural Network Checkpoints
Learning to Learn with Generative Models of Neural Network Checkpoints
William S. Peebles
Ilija Radosavovic
Tim Brooks
Alexei A. Efros
Jitendra Malik
UQCV
75
65
0
26 Sep 2022
A Closer Look at Learned Optimization: Stability, Robustness, and
  Inductive Biases
A Closer Look at Learned Optimization: Stability, Robustness, and Inductive Biases
James Harrison
Luke Metz
Jascha Narain Sohl-Dickstein
49
22
0
22 Sep 2022
Learning Symbolic Model-Agnostic Loss Functions via Meta-Learning
Learning Symbolic Model-Agnostic Loss Functions via Meta-Learning
Christian Raymond
Qi Chen
Bing Xue
Mengjie Zhang
FedML
31
11
0
19 Sep 2022
Online Meta-Learning for Model Update Aggregation in Federated Learning
  for Click-Through Rate Prediction
Online Meta-Learning for Model Update Aggregation in Federated Learning for Click-Through Rate Prediction
Xianghang Liu
Bartlomiej Twardowski
Tri Kurniawan Wijaya
FedML
33
1
0
30 Aug 2022
Betty: An Automatic Differentiation Library for Multilevel Optimization
Betty: An Automatic Differentiation Library for Multilevel Optimization
Sang Keun Choe
Willie Neiswanger
P. Xie
Eric P. Xing
AI4CE
31
30
0
05 Jul 2022
Grad-GradaGrad? A Non-Monotone Adaptive Stochastic Gradient Method
Grad-GradaGrad? A Non-Monotone Adaptive Stochastic Gradient Method
Aaron Defazio
Baoyu Zhou
Lin Xiao
ODL
27
5
0
14 Jun 2022
Automated Dynamic Algorithm Configuration
Automated Dynamic Algorithm Configuration
Steven Adriaensen
André Biedenkapp
Gresa Shala
Noor H. Awad
Theresa Eimer
Marius Lindauer
Frank Hutter
34
36
0
27 May 2022
DLTTA: Dynamic Learning Rate for Test-time Adaptation on Cross-domain
  Medical Images
DLTTA: Dynamic Learning Rate for Test-time Adaptation on Cross-domain Medical Images
Hongzheng Yang
Cheng Chen
Meirui Jiang
Quande Liu
Jianfeng Cao
Pheng Ann Heng
Qi Dou
OOD
40
26
0
27 May 2022
Amortized Proximal Optimization
Amortized Proximal Optimization
Juhan Bae
Paul Vicol
Jeff Z. HaoChen
Roger C. Grosse
ODL
29
14
0
28 Feb 2022
Step-size Adaptation Using Exponentiated Gradient Updates
Step-size Adaptation Using Exponentiated Gradient Updates
Ehsan Amid
Rohan Anil
Christopher Fifty
Manfred K. Warmuth
37
9
0
31 Jan 2022
A Stochastic Bundle Method for Interpolating Networks
A Stochastic Bundle Method for Interpolating Networks
Alasdair Paren
Leonard Berrada
Rudra P. K. Poudel
M. P. Kumar
24
4
0
29 Jan 2022
DDG-DA: Data Distribution Generation for Predictable Concept Drift
  Adaptation
DDG-DA: Data Distribution Generation for Predictable Concept Drift Adaptation
Wendi Li
Xiao Yang
Weiqing Liu
Yingce Xia
Jiang Bian
DiffM
AI4TS
28
51
0
11 Jan 2022
Unbiased Gradient Estimation in Unrolled Computation Graphs with
  Persistent Evolution Strategies
Unbiased Gradient Estimation in Unrolled Computation Graphs with Persistent Evolution Strategies
Paul Vicol
Luke Metz
Jascha Narain Sohl-Dickstein
27
68
0
27 Dec 2021
Automated Deep Learning: Neural Architecture Search Is Not the End
Automated Deep Learning: Neural Architecture Search Is Not the End
Xuanyi Dong
D. Kedziora
Katarzyna Musial
Bogdan Gabrys
29
26
0
16 Dec 2021
Scalable One-Pass Optimisation of High-Dimensional Weight-Update
  Hyperparameters by Implicit Differentiation
Scalable One-Pass Optimisation of High-Dimensional Weight-Update Hyperparameters by Implicit Differentiation
Ross M. Clarke
E. T. Oldewage
José Miguel Hernández-Lobato
31
9
0
20 Oct 2021
Learning by Examples Based on Multi-level Optimization
Learning by Examples Based on Multi-level Optimization
Shentong Mo
P. Xie
29
0
0
22 Sep 2021
Graph Contrastive Learning Automated
Graph Contrastive Learning Automated
Yuning You
Tianlong Chen
Yang Shen
Zhangyang Wang
24
448
0
10 Jun 2021
AutoLRS: Automatic Learning-Rate Schedule by Bayesian Optimization on
  the Fly
AutoLRS: Automatic Learning-Rate Schedule by Bayesian Optimization on the Fly
Yuchen Jin
Dinesh Manocha
Liangyu Zhao
Yibo Zhu
Chuanxiong Guo
Marco Canini
Arvind Krishnamurthy
37
18
0
22 May 2021
AngularGrad: A New Optimization Technique for Angular Convergence of
  Convolutional Neural Networks
AngularGrad: A New Optimization Technique for Angular Convergence of Convolutional Neural Networks
S. K. Roy
Mercedes Eugenia Paoletti
J. Haut
S. Dubey
Purushottam Kar
A. Plaza
B. B. Chaudhuri
ODL
27
18
0
21 May 2021
Robust MAML: Prioritization task buffer with adaptive learning process
  for model-agnostic meta-learning
Robust MAML: Prioritization task buffer with adaptive learning process for model-agnostic meta-learning
Thanh Nguyen
Tung M. Luu
T. Pham
Sanzhar Rakhimkul
Chang D. Yoo
22
10
0
15 Mar 2021
Investigating Bi-Level Optimization for Learning and Vision from a
  Unified Perspective: A Survey and Beyond
Investigating Bi-Level Optimization for Learning and Vision from a Unified Perspective: A Survey and Beyond
Risheng Liu
Jiaxin Gao
Jin Zhang
Deyu Meng
Zhouchen Lin
AI4CE
62
223
0
27 Jan 2021
Self-Tuning Stochastic Optimization with Curvature-Aware Gradient
  Filtering
Self-Tuning Stochastic Optimization with Curvature-Aware Gradient Filtering
Ricky T. Q. Chen
Dami Choi
Lukas Balles
David Duvenaud
Philipp Hennig
ODL
44
6
0
09 Nov 2020
A straightforward line search approach on the expected empirical loss
  for stochastic deep learning problems
A straightforward line search approach on the expected empirical loss for stochastic deep learning problems
Max Mutschler
A. Zell
36
0
0
02 Oct 2020
Improved Bilevel Model: Fast and Optimal Algorithm with Theoretical
  Guarantee
Improved Bilevel Model: Fast and Optimal Algorithm with Theoretical Guarantee
Junyi Li
Bin Gu
Heng-Chiao Huang
18
41
0
01 Sep 2020
learn2learn: A Library for Meta-Learning Research
learn2learn: A Library for Meta-Learning Research
Sébastien M. R. Arnold
Praateek Mahajan
Debajyoti Datta
Ian Bunner
Konstantinos Saitas Zarkias
34
95
0
27 Aug 2020
Hippo: Taming Hyper-parameter Optimization of Deep Learning with Stage
  Trees
Hippo: Taming Hyper-parameter Optimization of Deep Learning with Stage Trees
Ahnjae Shin
Do Yoon Kim
Joo Seong Jeong
Byung-Gon Chun
20
4
0
22 Jun 2020
Balancing Training for Multilingual Neural Machine Translation
Balancing Training for Multilingual Neural Machine Translation
Xinyi Wang
Yulia Tsvetkov
Graham Neubig
16
99
0
14 Apr 2020
Meta-Learning in Neural Networks: A Survey
Meta-Learning in Neural Networks: A Survey
Timothy M. Hospedales
Antreas Antoniou
P. Micaelli
Amos Storkey
OOD
93
1,935
0
11 Apr 2020
Meta Pseudo Labels
Meta Pseudo Labels
Hieu H. Pham
Zihang Dai
Qizhe Xie
Minh-Thang Luong
Quoc V. Le
VLM
262
658
0
23 Mar 2020
Statistical Adaptive Stochastic Gradient Methods
Statistical Adaptive Stochastic Gradient Methods
Pengchuan Zhang
Hunter Lang
Qiang Liu
Lin Xiao
ODL
15
11
0
25 Feb 2020
Optimizing Data Usage via Differentiable Rewards
Optimizing Data Usage via Differentiable Rewards
Xinyi Wang
Hieu H. Pham
Paul Michel
Antonios Anastasopoulos
J. Carbonell
Graham Neubig
18
60
0
22 Nov 2019
On the adequacy of untuned warmup for adaptive optimization
On the adequacy of untuned warmup for adaptive optimization
Jerry Ma
Denis Yarats
59
70
0
09 Oct 2019
Learning an Adaptive Learning Rate Schedule
Learning an Adaptive Learning Rate Schedule
Zhen Xu
Andrew M. Dai
Jonas Kemp
Luke Metz
22
61
0
20 Sep 2019
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