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2301.07733
Cited By
Learning-Rate-Free Learning by D-Adaptation
18 January 2023
Aaron Defazio
Konstantin Mishchenko
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Papers citing
"Learning-Rate-Free Learning by D-Adaptation"
50 / 65 papers shown
Title
Analysis of an Idealized Stochastic Polyak Method and its Application to Black-Box Model Distillation
Robert M. Gower
Guillaume Garrigos
Nicolas Loizou
Dimitris Oikonomou
Konstantin Mishchenko
Fabian Schaipp
31
0
0
02 Apr 2025
Benefits of Learning Rate Annealing for Tuning-Robustness in Stochastic Optimization
Amit Attia
Tomer Koren
65
1
0
13 Mar 2025
Towards hyperparameter-free optimization with differential privacy
Zhiqi Bu
Ruixuan Liu
24
1
0
02 Mar 2025
Adaptive Accelerated Proximal Gradient Methods with Variance Reduction for Composite Nonconvex Finite-Sum Minimization
Ganzhao Yuan
35
0
0
28 Feb 2025
LOB-Bench: Benchmarking Generative AI for Finance - an Application to Limit Order Book Data
Peer Nagy
Sascha Frey
Kang Li
Bidipta Sarkar
Svitlana Vyetrenko
Stefan Zohren
Ani Calinescu
Jakob Foerster
84
1
0
13 Feb 2025
A Hessian-informed hyperparameter optimization for differential learning rate
Shiyun Xu
Zhiqi Bu
Yiliang Zhang
Ian J. Barnett
39
1
0
12 Jan 2025
Temporal Context Consistency Above All: Enhancing Long-Term Anticipation by Learning and Enforcing Temporal Constraints
Alberto Maté
Mariella Dimiccoli
AI4TS
26
0
0
27 Dec 2024
MARINA-P: Superior Performance in Non-smooth Federated Optimization with Adaptive Stepsizes
Igor Sokolov
Peter Richtárik
77
1
0
22 Dec 2024
An Energy-Based Self-Adaptive Learning Rate for Stochastic Gradient Descent: Enhancing Unconstrained Optimization with VAV method
Jiahao Zhang
Christian Moya
Guang Lin
26
0
0
10 Nov 2024
CRONOS: Enhancing Deep Learning with Scalable GPU Accelerated Convex Neural Networks
Miria Feng
Zachary Frangella
Mert Pilanci
BDL
38
1
0
02 Nov 2024
Unlearning as multi-task optimization: A normalized gradient difference approach with an adaptive learning rate
Zhiqi Bu
Xiaomeng Jin
Bhanukiran Vinzamuri
Anil Ramakrishna
Kai-Wei Chang
V. Cevher
Mingyi Hong
MU
83
6
0
29 Oct 2024
Tuning-free coreset Markov chain Monte Carlo
Naitong Chen
Jonathan H. Huggins
Trevor Campbell
25
0
0
24 Oct 2024
A second-order-like optimizer with adaptive gradient scaling for deep learning
Jérôme Bolte
Ryan Boustany
Edouard Pauwels
Andrei Purica
ODL
30
0
0
08 Oct 2024
Diffusing to the Top: Boost Graph Neural Networks with Minimal Hyperparameter Tuning
Lequan Lin
Dai Shi
Andi Han
Zhiyong Wang
Junbin Gao
23
0
0
08 Oct 2024
Old Optimizer, New Norm: An Anthology
Jeremy Bernstein
Laker Newhouse
ODL
36
12
0
30 Sep 2024
State-free Reinforcement Learning
Mingyu Chen
Aldo Pacchiano
Xuezhou Zhang
61
0
0
27 Sep 2024
VMAS: Video-to-Music Generation via Semantic Alignment in Web Music Videos
Yan-Bo Lin
Yu Tian
L. Yang
Gedas Bertasius
Heng Wang
VGen
34
7
0
11 Sep 2024
Exploring Foundation Models for Synthetic Medical Imaging: A Study on Chest X-Rays and Fine-Tuning Techniques
Davide Clode da Silva
Marina Musse Bernardes
Nathalia Giacomini Ceretta
Gabriel Vaz de Souza
Gabriel Fonseca Silva
Rafael Heitor Bordini
S. Musse
MedIm
LM&MA
23
0
0
06 Sep 2024
Stepping on the Edge: Curvature Aware Learning Rate Tuners
Vincent Roulet
Atish Agarwala
Jean-Bastien Grill
Grzegorz Swirszcz
Mathieu Blondel
Fabian Pedregosa
34
1
0
08 Jul 2024
An Adaptive Stochastic Gradient Method with Non-negative Gauss-Newton Stepsizes
Antonio Orvieto
Lin Xiao
37
2
0
05 Jul 2024
Dreamguider: Improved Training free Diffusion-based Conditional Generation
Nithin Gopalakrishnan Nair
Vishal M. Patel
30
2
0
04 Jun 2024
Learning-Rate-Free Stochastic Optimization over Riemannian Manifolds
Daniel Dodd
Louis Sharrock
Christopher Nemeth
36
0
0
04 Jun 2024
Fully Unconstrained Online Learning
Ashok Cutkosky
Zakaria Mhammedi
CLL
27
1
0
30 May 2024
The High Line: Exact Risk and Learning Rate Curves of Stochastic Adaptive Learning Rate Algorithms
Elizabeth Collins-Woodfin
Inbar Seroussi
Begona García Malaxechebarría
Andrew W. Mackenzie
Elliot Paquette
Courtney Paquette
28
1
0
30 May 2024
The Road Less Scheduled
Aaron Defazio
Xingyu Yang
Yang
Harsh Mehta
Konstantin Mishchenko
Ahmed Khaled
Ashok Cutkosky
28
45
0
24 May 2024
Scalable Optimization in the Modular Norm
Tim Large
Yang Liu
Minyoung Huh
Hyojin Bahng
Phillip Isola
Jeremy Bernstein
39
12
0
23 May 2024
Unleash Graph Neural Networks from Heavy Tuning
Lequan Lin
Dai Shi
Andi Han
Zhiyong Wang
Junbin Gao
AI4CE
27
2
0
21 May 2024
Towards Stability of Parameter-free Optimization
Yijiang Pang
Shuyang Yu
Hoang Bao
Jiayu Zhou
29
1
0
07 May 2024
Remove that Square Root: A New Efficient Scale-Invariant Version of AdaGrad
Sayantan Choudhury
N. Tupitsa
Nicolas Loizou
Samuel Horváth
Martin Takáč
Eduard A. Gorbunov
30
1
0
05 Mar 2024
Data-Efficient Operator Learning via Unsupervised Pretraining and In-Context Learning
Wuyang Chen
Jialin Song
Pu Ren
Shashank Subramanian
Dmitriy Morozov
Michael W. Mahoney
AI4CE
35
9
0
24 Feb 2024
Tuning-Free Stochastic Optimization
Ahmed Khaled
Chi Jin
30
7
0
12 Feb 2024
AdaBatchGrad: Combining Adaptive Batch Size and Adaptive Step Size
P. Ostroukhov
Aigerim Zhumabayeva
Chulu Xiang
Alexander Gasnikov
Martin Takáč
Dmitry Kamzolov
ODL
38
2
0
07 Feb 2024
How Free is Parameter-Free Stochastic Optimization?
Amit Attia
Tomer Koren
ODL
39
4
0
05 Feb 2024
MetaOptimize: A Framework for Optimizing Step Sizes and Other Meta-parameters
Arsalan Sharifnassab
Saber Salehkaleybar
Richard Sutton
27
3
0
04 Feb 2024
Enhancing Stochastic Gradient Descent: A Unified Framework and Novel Acceleration Methods for Faster Convergence
Yichuan Deng
Zhao-quan Song
Chiwun Yang
24
1
0
02 Feb 2024
Stochastic Weakly Convex Optimization Beyond Lipschitz Continuity
Wenzhi Gao
Qi Deng
22
1
0
25 Jan 2024
Masked Audio Generation using a Single Non-Autoregressive Transformer
Alon Ziv
Itai Gat
Gaël Le Lan
Tal Remez
Felix Kreuk
Alexandre Défossez
Jade Copet
Gabriel Synnaeve
Yossi Adi
40
36
0
09 Jan 2024
Interpreting Adaptive Gradient Methods by Parameter Scaling for Learning-Rate-Free Optimization
Min-Kook Suh
Seung-Woo Seo
ODL
27
0
0
06 Jan 2024
Mocap Everyone Everywhere: Lightweight Motion Capture With Smartwatches and a Head-Mounted Camera
Jiye Lee
Hanbyul Joo
26
16
0
01 Jan 2024
SANIA: Polyak-type Optimization Framework Leads to Scale Invariant Stochastic Algorithms
Farshed Abdukhakimov
Chulu Xiang
Dmitry Kamzolov
Robert Mansel Gower
Martin Takáč
32
2
0
28 Dec 2023
Locally Optimal Descent for Dynamic Stepsize Scheduling
Gilad Yehudai
Alon Cohen
Amit Daniely
Yoel Drori
Tomer Koren
Mariano Schain
24
0
0
23 Nov 2023
Non-Uniform Smoothness for Gradient Descent
A. Berahas
Lindon Roberts
Fred Roosta
20
3
0
15 Nov 2023
An Automatic Learning Rate Schedule Algorithm for Achieving Faster Convergence and Steeper Descent
Zhao-quan Song
Chiwun Yang
19
9
0
17 Oct 2023
A simple uniformly optimal method without line search for convex optimization
Tianjiao Li
Guanghui Lan
19
20
0
16 Oct 2023
Multiple Physics Pretraining for Physical Surrogate Models
Michael McCabe
Bruno Régaldo-Saint Blancard
Liam Parker
Ruben Ohana
M. Cranmer
...
Francois Lanusse
Mariel Pettee
Tiberiu Teşileanu
Kyunghyun Cho
Shirley Ho
PINN
AI4CE
23
51
0
04 Oct 2023
Small-scale proxies for large-scale Transformer training instabilities
Mitchell Wortsman
Peter J. Liu
Lechao Xiao
Katie Everett
A. Alemi
...
Jascha Narain Sohl-Dickstein
Kelvin Xu
Jaehoon Lee
Justin Gilmer
Simon Kornblith
35
80
0
25 Sep 2023
Ego3DPose: Capturing 3D Cues from Binocular Egocentric Views
Taeho Kang
Kyungjin Lee
Jinrui Zhang
Youngki Lee
EgoV
17
18
0
21 Sep 2023
Learning-Rate-Free Learning: Dissecting D-Adaptation and Probabilistic Line Search
Max McGuinness
ODL
13
0
0
06 Aug 2023
Adaptive Proximal Gradient Method for Convex Optimization
Yura Malitsky
Konstantin Mishchenko
16
21
0
04 Aug 2023
An Oblivious Stochastic Composite Optimization Algorithm for Eigenvalue Optimization Problems
Clément Lezane
Cristóbal Guzmán
Alexandre d’Aspremont
28
0
0
30 Jun 2023
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