Communities
Connect sessions
AI calendar
Organizations
Join Slack
Contact Sales
Search
Open menu
Home
Papers
1812.11118
Cited By
v1
v2 (latest)
Reconciling modern machine learning practice and the bias-variance trade-off
28 December 2018
M. Belkin
Daniel J. Hsu
Siyuan Ma
Soumik Mandal
Re-assign community
ArXiv (abs)
PDF
HTML
Papers citing
"Reconciling modern machine learning practice and the bias-variance trade-off"
50 / 945 papers shown
Bayesian Interpolation with Deep Linear Networks
Proceedings of the National Academy of Sciences of the United States of America (PNAS), 2022
Boris Hanin
Alexander Zlokapa
424
29
0
29 Dec 2022
Problem-Dependent Power of Quantum Neural Networks on Multi-Class Classification
Physical Review Letters (PRL), 2022
Yuxuan Du
Jianlong Wu
Dacheng Tao
Min-hsiu Hsieh
425
31
0
29 Dec 2022
On Implicit Bias in Overparameterized Bilevel Optimization
International Conference on Machine Learning (ICML), 2022
Paul Vicol
Jon Lorraine
Fabian Pedregosa
David Duvenaud
Roger C. Grosse
AI4CE
253
46
0
28 Dec 2022
Homophily modulates double descent generalization in graph convolution networks
Proceedings of the National Academy of Sciences of the United States of America (PNAS), 2022
Chengzhi Shi
Liming Pan
Hong Hu
Ivan Dokmanić
397
13
0
26 Dec 2022
The Quantum Path Kernel: a Generalized Quantum Neural Tangent Kernel for Deep Quantum Machine Learning
IEEE Transactions on Quantum Engineering (IEEE Trans. Quantum Eng.), 2022
Massimiliano Incudini
Michele Grossi
Antonio Mandarino
S. Vallecorsa
Alessandra Di Pierro
David Windridge
269
14
0
22 Dec 2022
Reproducible scaling laws for contrastive language-image learning
Computer Vision and Pattern Recognition (CVPR), 2022
Mehdi Cherti
Romain Beaumont
Ross Wightman
Mitchell Wortsman
Gabriel Ilharco
Cade Gordon
Christoph Schuhmann
Ludwig Schmidt
J. Jitsev
VLM
CLIP
496
1,161
0
14 Dec 2022
Gradient flow in the gaussian covariate model: exact solution of learning curves and multiple descent structures
Antione Bodin
N. Macris
208
4
0
13 Dec 2022
Reliable extrapolation of deep neural operators informed by physics or sparse observations
Social Science Research Network (SSRN), 2022
Min Zhu
Handi Zhang
Anran Jiao
George Karniadakis
Lu Lu
260
127
0
13 Dec 2022
Tight bounds for maximum
ℓ
1
\ell_1
ℓ
1
-margin classifiers
Stefan Stojanovic
Konstantin Donhauser
Fanny Yang
291
0
0
07 Dec 2022
Improved Convergence Guarantees for Shallow Neural Networks
A. Razborov
ODL
217
1
0
05 Dec 2022
High Dimensional Binary Classification under Label Shift: Phase Transition and Regularization
Sampling Theory, Signal Processing, and Data Analysis (SampTA), 2022
Jiahui Cheng
Minshuo Chen
Hao Liu
Tuo Zhao
Wenjing Liao
315
1
0
01 Dec 2022
Regularization Trade-offs with Fake Features
European Signal Processing Conference (EUSIPCO), 2022
Martin Hellkvist
Ayça Özçelikkale
Anders Ahlén
346
0
0
01 Dec 2022
Task Discovery: Finding the Tasks that Neural Networks Generalize on
Neural Information Processing Systems (NeurIPS), 2022
Andrei Atanov
Andrei Filatov
Teresa Yeo
Ajay Sohmshetty
Amir Zamir
OOD
378
11
0
01 Dec 2022
Nonlinear Advantage: Trained Networks Might Not Be As Complex as You Think
International Conference on Machine Learning (ICML), 2022
Christian H. X. Ali Mehmeti-Göpel
Jan Disselhoff
184
6
0
30 Nov 2022
Why Neural Networks Work
Intelligent Systems with Applications (ISA), 2022
Sayan Mukherjee
Bernardo A. Huberman
124
2
0
26 Nov 2022
The Vanishing Decision Boundary Complexity and the Strong First Component
Hengshuai Yao
UQCV
166
0
0
25 Nov 2022
The smooth output assumption, and why deep networks are better than wide ones
Luis Sa-Couto
J. M. Ramos
Andreas Wichert
103
0
0
25 Nov 2022
A Survey of Learning Curves with Bad Behavior: or How More Data Need Not Lead to Better Performance
Marco Loog
T. Viering
185
2
0
25 Nov 2022
Frozen Overparameterization: A Double Descent Perspective on Transfer Learning of Deep Neural Networks
Yehuda Dar
Lorenzo Luzi
Richard G. Baraniuk
AI4CE
183
2
0
20 Nov 2022
Understanding the double descent curve in Machine Learning
Luis Sa-Couto
J. M. Ramos
Miguel Almeida
Andreas Wichert
131
3
0
18 Nov 2022
Emergence of Concepts in DNNs?
Tim Räz
62
0
0
11 Nov 2022
Do highly over-parameterized neural networks generalize since bad solutions are rare?
IEEE Transactions on Neural Networks and Learning Systems (TNNLS), 2022
Julius Martinetz
T. Martinetz
427
1
0
07 Nov 2022
Reward-Predictive Clustering
Lucas Lehnert
M. Frank
Michael L. Littman
OffRL
206
0
0
07 Nov 2022
Instance-Dependent Generalization Bounds via Optimal Transport
Journal of machine learning research (JMLR), 2022
Songyan Hou
Parnian Kassraie
Anastasis Kratsios
Andreas Krause
Jonas Rothfuss
500
12
0
02 Nov 2022
Transfer Learning with Kernel Methods
Nature Communications (Nat Commun), 2022
Adityanarayanan Radhakrishnan
Max Ruiz Luyten
Neha Prasad
Caroline Uhler
153
30
0
01 Nov 2022
Globally Gated Deep Linear Networks
Neural Information Processing Systems (NeurIPS), 2022
Qianyi Li
H. Sompolinsky
AI4CE
251
15
0
31 Oct 2022
A Law of Data Separation in Deep Learning
Proceedings of the National Academy of Sciences of the United States of America (PNAS), 2022
Hangfeng He
Weijie J. Su
OOD
344
49
0
31 Oct 2022
A Solvable Model of Neural Scaling Laws
A. Maloney
Daniel A. Roberts
J. Sully
261
79
0
30 Oct 2022
Grokking phase transitions in learning local rules with gradient descent
Journal of machine learning research (JMLR), 2022
Bojan Žunkovič
E. Ilievski
275
22
0
26 Oct 2022
Learning Ability of Interpolating Deep Convolutional Neural Networks
Social Science Research Network (SSRN), 2022
Tiancong Zhou
X. Huo
AI4CE
183
14
0
25 Oct 2022
Deep Neural Networks as the Semi-classical Limit of Topological Quantum Neural Networks: The problem of generalisation
A. Marcianò
De-Wei Chen
Filippo Fabrocini
C. Fields
M. Lulli
Emanuele Zappala
GNN
115
6
0
25 Oct 2022
Pruning's Effect on Generalization Through the Lens of Training and Regularization
Neural Information Processing Systems (NeurIPS), 2022
Tian Jin
Michael Carbin
Daniel M. Roy
Jonathan Frankle
Gintare Karolina Dziugaite
236
33
0
25 Oct 2022
On double-descent in uncertainty quantification in overparametrized models
International Conference on Artificial Intelligence and Statistics (AISTATS), 2022
Lucas Clarté
Bruno Loureiro
Florent Krzakala
Lenka Zdeborová
UQCV
462
14
0
23 Oct 2022
Monotonicity and Double Descent in Uncertainty Estimation with Gaussian Processes
International Conference on Machine Learning (ICML), 2022
Liam Hodgkinson
Christopher van der Heide
Fred Roosta
Michael W. Mahoney
UQCV
257
7
0
14 Oct 2022
Identification of quantum entanglement with Siamese convolutional neural networks and semi-supervised learning
Physical Review Applied (Phys. Rev. Appl.), 2022
J. Pawłowski
Mateusz Krawczyk
243
6
0
13 Oct 2022
The good, the bad and the ugly sides of data augmentation: An implicit spectral regularization perspective
Journal of machine learning research (JMLR), 2022
Chi-Heng Lin
Chiraag Kaushik
Eva L. Dyer
Vidya Muthukumar
381
42
0
10 Oct 2022
Second-order regression models exhibit progressive sharpening to the edge of stability
International Conference on Machine Learning (ICML), 2022
Atish Agarwala
Fabian Pedregosa
Jeffrey Pennington
252
32
0
10 Oct 2022
Goal Misgeneralization: Why Correct Specifications Aren't Enough For Correct Goals
Rohin Shah
Vikrant Varma
Ramana Kumar
Mary Phuong
Victoria Krakovna
J. Uesato
Zachary Kenton
428
105
0
04 Oct 2022
Block-wise Training of Residual Networks via the Minimizing Movement Scheme
Skander Karkar
Ibrahim Ayed
Emmanuel de Bézenac
Patrick Gallinari
214
1
0
03 Oct 2022
Ten Years after ImageNet: A 360° Perspective on AI
Sanjay Chawla
Preslav Nakov
Ahmed Ali
Wendy Hall
Issa M. Khalil
Xiaosong Ma
Husrev Taha Sencar
Ingmar Weber
Michael Wooldridge
Tingyue Yu
91
0
0
01 Oct 2022
On the Impossible Safety of Large AI Models
El-Mahdi El-Mhamdi
Sadegh Farhadkhani
R. Guerraoui
Nirupam Gupta
L. Hoang
Rafael Pinot
Sébastien Rouault
John Stephan
359
37
0
30 Sep 2022
Why neural networks find simple solutions: the many regularizers of geometric complexity
Neural Information Processing Systems (NeurIPS), 2022
Benoit Dherin
Michael Munn
M. Rosca
David Barrett
351
43
0
27 Sep 2022
In-context Learning and Induction Heads
Catherine Olsson
Nelson Elhage
Neel Nanda
Nicholas Joseph
Nova Dassarma
...
Tom B. Brown
Jack Clark
Jared Kaplan
Sam McCandlish
C. Olah
607
700
0
24 Sep 2022
Deep Double Descent via Smooth Interpolation
Matteo Gamba
Erik Englesson
Mårten Björkman
Hossein Azizpour
611
12
0
21 Sep 2022
Deep Linear Networks can Benignly Overfit when Shallow Ones Do
Journal of machine learning research (JMLR), 2022
Niladri S. Chatterji
Philip M. Long
236
11
0
19 Sep 2022
Lazy vs hasty: linearization in deep networks impacts learning schedule based on example difficulty
Thomas George
Guillaume Lajoie
A. Baratin
193
7
0
19 Sep 2022
Importance Tempering: Group Robustness for Overparameterized Models
Yiping Lu
Wenlong Ji
Zachary Izzo
Lexing Ying
270
7
0
19 Sep 2022
Random Fourier Features for Asymmetric Kernels
Machine-mediated learning (ML), 2022
Ming-qian He
Fan He
Fanghui Liu
Xiaolin Huang
231
5
0
18 Sep 2022
Generalization in Neural Networks: A Broad Survey
Neurocomputing (Neurocomputing), 2022
Chris Rohlfs
OOD
AI4CE
279
19
0
04 Sep 2022
Towards Understanding the Overfitting Phenomenon of Deep Click-Through Rate Prediction Models
International Conference on Information and Knowledge Management (CIKM), 2022
Zhaorui Zhang
Xiang-Rong Sheng
Yujing Zhang
Biye Jiang
Shuguang Han
Hongbo Deng
Bo Zheng
CML
199
47
0
04 Sep 2022
Previous
1
2
3
...
8
9
10
...
17
18
19
Next
