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2102.04074
Cited By
Learning Curve Theory
8 February 2021
Marcus Hutter
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Papers citing
"Learning Curve Theory"
50 / 56 papers shown
Zero-Shot Performance Prediction for Probabilistic Scaling Laws
Viktoria Schram
Markus Hiller
Daniel Beck
Trevor Cohn
175
0
0
19 Oct 2025
Efficient Prediction of Pass@k Scaling in Large Language Models
Joshua Kazdan
Rylan Schaeffer
Youssef Allouah
Colin Sullivan
Kyssen Yu
Noam Levi
Sanmi Koyejo
OffRL
194
6
0
06 Oct 2025
xLSTM Scaling Laws: Competitive Performance with Linear Time-Complexity
Maximilian Beck
Kajetan Schweighofer
Sebastian Böck
Sebastian Lehner
Sepp Hochreiter
178
1
1
02 Oct 2025
Evaluating the Robustness of Chinchilla Compute-Optimal Scaling
Rylan Schaeffer
Noam Levi
Andreas Kirsch
Theo Guenais
Brando Miranda
Elyas Obbad
Sanmi Koyejo
LRM
220
3
0
28 Sep 2025
Neural Scaling Laws for Deep Regression
Tilen Cadez
Kyoung-Min Kim
258
0
0
12 Sep 2025
Scaling Laws Are Unreliable for Downstream Tasks: A Reality Check
Nicholas Lourie
Michael Y. Hu
Dong Wang
215
18
0
01 Jul 2025
Complexity Scaling Laws for Neural Models using Combinatorial Optimization
Lowell Weissman
Michael Krumdick
A. Lynn Abbott
352
1
0
15 Jun 2025
Improved Scaling Laws in Linear Regression via Data Reuse
Licong Lin
Jingfeng Wu
Peter Bartlett
232
2
0
10 Jun 2025
When Models Don't Collapse: On the Consistency of Iterative MLE
Daniel Barzilai
Ohad Shamir
SyDa
253
5
0
25 May 2025
Superposition Yields Robust Neural Scaling
Yizhou Liu
Ziming Liu
Jeff Gore
MILM
749
11
0
15 May 2025
Scaling Laws and Representation Learning in Simple Hierarchical Languages: Transformers vs. Convolutional Architectures
Francesco Cagnetta
Alessandro Favero
Antonio Sclocchi
Matthieu Wyart
442
3
0
11 May 2025
Learning curves theory for hierarchically compositional data with power-law distributed features
Francesco Cagnetta
Hyunmo Kang
Matthieu Wyart
390
6
0
11 May 2025
Quiet Feature Learning in Algorithmic Tasks
Prudhviraj Naidu
Zixian Wang
Leon Bergen
R. Paturi
VLM
430
0
0
06 May 2025
A Multi-Power Law for Loss Curve Prediction Across Learning Rate Schedules
International Conference on Learning Representations (ICLR), 2025
Kairong Luo
Haodong Wen
Shengding Hu
Zhenbo Sun
Zhiyuan Liu
Maosong Sun
Kaifeng Lyu
Wenguang Chen
CLL
325
19
0
17 Mar 2025
Position: Solve Layerwise Linear Models First to Understand Neural Dynamical Phenomena (Neural Collapse, Emergence, Lazy/Rich Regime, and Grokking)
Yoonsoo Nam
Seok Hyeong Lee
Clementine Domine
Yea Chan Park
Charles London
Wonyl Choi
Niclas Goring
Seungjai Lee
AI4CE
632
5
0
28 Feb 2025
How to Upscale Neural Networks with Scaling Law? A Survey and Practical Guidelines
Ayan Sengupta
Ayan Sengupta
Tanmoy Chakraborty
604
4
0
17 Feb 2025
Loss-to-Loss Prediction: Scaling Laws for All Datasets
David Brandfonbrener
Nikhil Anand
Nikhil Vyas
Eran Malach
Sham Kakade
335
12
0
19 Nov 2024
Scaling Laws for Pre-training Agents and World Models
Tim Pearce
Tabish Rashid
Dave Bignell
Raluca Georgescu
Sam Devlin
Katja Hofmann
LM&Ro
431
19
0
07 Nov 2024
A Simple Model of Inference Scaling Laws
Noam Levi
LRM
265
24
0
21 Oct 2024
Adaptive Data Optimization: Dynamic Sample Selection with Scaling Laws
International Conference on Learning Representations (ICLR), 2024
Yiding Jiang
Allan Zhou
Zhili Feng
Sadhika Malladi
J. Zico Kolter
307
41
0
15 Oct 2024
Analyzing Neural Scaling Laws in Two-Layer Networks with Power-Law Data Spectra
International Conference on Learning Representations (ICLR), 2024
Roman Worschech
B. Rosenow
443
3
0
11 Oct 2024
Unified Neural Network Scaling Laws and Scale-time Equivalence
Akhilan Boopathy
Ila Fiete
551
3
0
09 Sep 2024
Breaking Neural Network Scaling Laws with Modularity
International Conference on Learning Representations (ICLR), 2024
Akhilan Boopathy
Sunshine Jiang
William Yue
Jaedong Hwang
Abhiram Iyer
Ila Fiete
OOD
488
7
0
09 Sep 2024
Towards Exact Computation of Inductive Bias
Akhilan Boopathy
William Yue
Jaedong Hwang
Abhiram Iyer
Ila Fiete
357
5
0
22 Jun 2024
Reconciling Kaplan and Chinchilla Scaling Laws
Tim Pearce
Jinyeop Song
445
27
0
12 Jun 2024
Scaling Laws in Linear Regression: Compute, Parameters, and Data
Licong Lin
Jingfeng Wu
Sham Kakade
Peter L. Bartlett
Jason D. Lee
LRM
556
42
0
12 Jun 2024
Scaling Laws for the Value of Individual Data Points in Machine Learning
Ian Covert
Wenlong Ji
Tatsunori Hashimoto
James Zou
TDI
314
11
0
30 May 2024
Data Mixing Laws: Optimizing Data Mixtures by Predicting Language Modeling Performance
Jiasheng Ye
Peiju Liu
Tianxiang Sun
Yunhua Zhou
Jun Zhan
Xipeng Qiu
522
131
0
25 Mar 2024
How much data do you need? Part 2: Predicting DL class specific training dataset sizes
Thomas Mühlenstädt
Jelena Frtunikj
178
4
0
10 Mar 2024
A Tale of Tails: Model Collapse as a Change of Scaling Laws
International Conference on Machine Learning (ICML), 2024
Elvis Dohmatob
Yunzhen Feng
Pu Yang
Francois Charton
Julia Kempe
345
117
0
10 Feb 2024
Scaling Laws for Downstream Task Performance of Large Language Models
International Conference on Learning Representations (ICLR), 2024
Berivan Isik
Natalia Ponomareva
Hussein Hazimeh
Dimitris Paparas
Sergei Vassilvitskii
Sanmi Koyejo
383
52
0
06 Feb 2024
Scaling Laws for Associative Memories
International Conference on Learning Representations (ICLR), 2023
Vivien A. Cabannes
Elvis Dohmatob
A. Bietti
470
26
0
04 Oct 2023
Pareto Frontiers in Neural Feature Learning: Data, Compute, Width, and Luck
Benjamin L. Edelman
Surbhi Goel
Sham Kakade
Eran Malach
Cyril Zhang
347
12
0
07 Sep 2023
Is One Epoch All You Need For Multi-Fidelity Hyperparameter Optimization?
The European Symposium on Artificial Neural Networks (ESANN), 2023
Romain Egele
Isabelle M Guyon
Yixuan Sun
Dali Wang
336
7
0
28 Jul 2023
The semantic landscape paradigm for neural networks
Shreyas Gokhale
425
3
0
18 Jul 2023
Delegated Classification
Neural Information Processing Systems (NeurIPS), 2023
Eden Saig
Inbal Talgam-Cohen
Nir Rosenfeld
282
13
0
20 Jun 2023
Getting ViT in Shape: Scaling Laws for Compute-Optimal Model Design
Neural Information Processing Systems (NeurIPS), 2023
Ibrahim Alabdulmohsin
Xiaohua Zhai
Alexander Kolesnikov
Lucas Beyer
VLM
686
102
0
22 May 2023
Model-agnostic Measure of Generalization Difficulty
International Conference on Machine Learning (ICML), 2023
Akhilan Boopathy
Kevin Liu
Jaedong Hwang
Shu Ge
Asaad Mohammedsaleh
Ila Fiete
444
8
0
01 May 2023
The Quantization Model of Neural Scaling
Neural Information Processing Systems (NeurIPS), 2023
Eric J. Michaud
Ziming Liu
Uzay Girit
Max Tegmark
MILM
450
133
0
23 Mar 2023
Scaling Laws for Multilingual Neural Machine Translation
International Conference on Machine Learning (ICML), 2023
Patrick Fernandes
Behrooz Ghorbani
Xavier Garcia
Markus Freitag
Orhan Firat
283
37
0
19 Feb 2023
Multiperiodic Processes: Ergodic Sources with a Sublinear Entropy
L. Debowski
MILM
433
11
0
17 Feb 2023
Languages You Know Influence Those You Learn: Impact of Language Characteristics on Multi-Lingual Text-to-Text Transfer
Benjamin Muller
Deepanshu Gupta
Siddharth Patwardhan
J. Fauconnier
David Vandyke
Sachin Agarwal
275
9
0
04 Dec 2022
Rethinking the transfer learning for FCN based polyp segmentation in colonoscopy
IEEE Access (IEEE Access), 2022
Yan-mao Wen
Lei Zhang
Xiangli Meng
Xujiong Ye
232
0
0
04 Nov 2022
A Solvable Model of Neural Scaling Laws
A. Maloney
Daniel A. Roberts
J. Sully
378
88
0
30 Oct 2022
Revisiting Neural Scaling Laws in Language and Vision
Neural Information Processing Systems (NeurIPS), 2022
Ibrahim Alabdulmohsin
Behnam Neyshabur
Xiaohua Zhai
645
157
0
13 Sep 2022
How Much More Data Do I Need? Estimating Requirements for Downstream Tasks
Computer Vision and Pattern Recognition (CVPR), 2022
Rafid Mahmood
James Lucas
David Acuna
Daiqing Li
Jonah Philion
Jose M. Alvarez
Zhiding Yu
Sanja Fidler
M. Law
233
36
0
04 Jul 2022
Unified Scaling Laws for Routed Language Models
International Conference on Machine Learning (ICML), 2022
Aidan Clark
Diego de Las Casas
Aurelia Guy
A. Mensch
Michela Paganini
...
Oriol Vinyals
Jack W. Rae
Erich Elsen
Koray Kavukcuoglu
Karen Simonyan
MoE
442
261
0
02 Feb 2022
Error Scaling Laws for Kernel Classification under Source and Capacity Conditions
Hugo Cui
Bruno Loureiro
Florent Krzakala
Lenka Zdeborová
368
16
0
29 Jan 2022
Scaling Law for Recommendation Models: Towards General-purpose User Representations
AAAI Conference on Artificial Intelligence (AAAI), 2021
Kyuyong Shin
Hanock Kwak
KyungHyun Kim
Max Nihlén Ramström
Jisu Jeong
Jung-Woo Ha
Seon Gyeom Kim
ELM
507
56
0
15 Nov 2021
Turing-Universal Learners with Optimal Scaling Laws
Preetum Nakkiran
225
6
0
09 Nov 2021
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