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Spectrally-normalized margin bounds for neural networks
v1v2 (latest)

Spectrally-normalized margin bounds for neural networks

26 June 2017
Peter L. Bartlett
Dylan J. Foster
Matus Telgarsky
    ODL
ArXiv (abs)PDFHTML

Papers citing "Spectrally-normalized margin bounds for neural networks"

50 / 811 papers shown
Title
Neural-Fly Enables Rapid Learning for Agile Flight in Strong Winds
Neural-Fly Enables Rapid Learning for Agile Flight in Strong Winds
Michael O'Connell
Guanya Shi
Xichen Shi
Kamyar Azizzadenesheli
Anima Anandkumar
Yisong Yue
Soon-Jo Chung
149
181
0
13 May 2022
Investigating Generalization by Controlling Normalized Margin
Investigating Generalization by Controlling Normalized Margin
Alexander R. Farhang
Jeremy Bernstein
Kushal Tirumala
Yang Liu
Yisong Yue
83
6
0
08 May 2022
Deep Ensemble as a Gaussian Process Approximate Posterior
Deep Ensemble as a Gaussian Process Approximate Posterior
Zhijie Deng
Feng Zhou
Jianfei Chen
Guoqiang Wu
Jun Zhu
UQCV
41
5
0
30 Apr 2022
On the Optimization of Margin Distribution
On the Optimization of Margin Distribution
Meng-Zhang Qian
Zheng Ai
Teng Zhang
Wei Gao
25
1
0
29 Apr 2022
ELM: Embedding and Logit Margins for Long-Tail Learning
ELM: Embedding and Logit Margins for Long-Tail Learning
Wittawat Jitkrittum
A. Menon
A. S. Rawat
Surinder Kumar
78
11
0
27 Apr 2022
Meta-free few-shot learning via representation learning with weight
  averaging
Meta-free few-shot learning via representation learning with weight averaging
Kuilin Chen
Chi-Guhn Lee
56
5
0
26 Apr 2022
Imaging Conductivity from Current Density Magnitude using Neural
  Networks
Imaging Conductivity from Current Density Magnitude using Neural Networks
Bangti Jin
Xiyao Li
Xiliang Lu
64
13
0
05 Apr 2022
Chordal Sparsity for Lipschitz Constant Estimation of Deep Neural
  Networks
Chordal Sparsity for Lipschitz Constant Estimation of Deep Neural Networks
Anton Xue
Lars Lindemann
Alexander Robey
Hamed Hassani
George J. Pappas
Rajeev Alur
134
13
0
02 Apr 2022
Predicting the generalization gap in neural networks using topological
  data analysis
Predicting the generalization gap in neural networks using topological data analysis
Rubén Ballester
Xavier Arnal Clemente
Carles Casacuberta
Meysam Madadi
C. Corneanu
Sergio Escalera
81
4
0
23 Mar 2022
The activity-weight duality in feed forward neural networks: The
  geometric determinants of generalization
The activity-weight duality in feed forward neural networks: The geometric determinants of generalization
Yu Feng
Yuhai Tu
MLT
112
16
0
21 Mar 2022
On the Generalization Mystery in Deep Learning
On the Generalization Mystery in Deep Learning
S. Chatterjee
Piotr Zielinski
OOD
67
35
0
18 Mar 2022
Generalization Through The Lens Of Leave-One-Out Error
Generalization Through The Lens Of Leave-One-Out Error
Gregor Bachmann
Thomas Hofmann
Aurelien Lucchi
136
8
0
07 Mar 2022
Meta Mirror Descent: Optimiser Learning for Fast Convergence
Meta Mirror Descent: Optimiser Learning for Fast Convergence
Boyan Gao
Henry Gouk
Haebeom Lee
Timothy M. Hospedales
99
6
0
05 Mar 2022
An Information-Theoretic Framework for Supervised Learning
An Information-Theoretic Framework for Supervised Learning
Hong Jun Jeon
Yifan Zhu
Benjamin Van Roy
92
7
0
01 Mar 2022
Adversarial robustness of sparse local Lipschitz predictors
Adversarial robustness of sparse local Lipschitz predictors
Ramchandran Muthukumar
Jeremias Sulam
AAML
92
13
0
26 Feb 2022
Benefit of Interpolation in Nearest Neighbor Algorithms
Benefit of Interpolation in Nearest Neighbor Algorithms
Yue Xing
Qifan Song
Guang Cheng
89
30
0
23 Feb 2022
On PAC-Bayesian reconstruction guarantees for VAEs
On PAC-Bayesian reconstruction guarantees for VAEs
Badr-Eddine Chérief-Abdellatif
Yuyang Shi
Arnaud Doucet
Benjamin Guedj
DRL
109
19
0
23 Feb 2022
From Optimization Dynamics to Generalization Bounds via Łojasiewicz
  Gradient Inequality
From Optimization Dynamics to Generalization Bounds via Łojasiewicz Gradient Inequality
Fusheng Liu
Haizhao Yang
Soufiane Hayou
Qianxiao Li
AI4CE
51
2
0
22 Feb 2022
On the Implicit Bias Towards Minimal Depth of Deep Neural Networks
On the Implicit Bias Towards Minimal Depth of Deep Neural Networks
Tomer Galanti
Liane Galanti
Ido Ben-Shaul
52
14
0
18 Feb 2022
On Measuring Excess Capacity in Neural Networks
On Measuring Excess Capacity in Neural Networks
Florian Graf
Sebastian Zeng
Bastian Rieck
Marc Niethammer
Roland Kwitt
94
10
0
16 Feb 2022
Benign Overfitting in Two-layer Convolutional Neural Networks
Benign Overfitting in Two-layer Convolutional Neural Networks
Yuan Cao
Zixiang Chen
M. Belkin
Quanquan Gu
MLT
93
90
0
14 Feb 2022
The Sample Complexity of One-Hidden-Layer Neural Networks
The Sample Complexity of One-Hidden-Layer Neural Networks
Gal Vardi
Ohad Shamir
Nathan Srebro
62
10
0
13 Feb 2022
Towards Data-Algorithm Dependent Generalization: a Case Study on
  Overparameterized Linear Regression
Towards Data-Algorithm Dependent Generalization: a Case Study on Overparameterized Linear Regression
Jing Xu
Jiaye Teng
Yang Yuan
Andrew Chi-Chih Yao
86
2
0
12 Feb 2022
Failure Prediction with Statistical Guarantees for Vision-Based Robot
  Control
Failure Prediction with Statistical Guarantees for Vision-Based Robot Control
Alec Farid
David Snyder
Allen Z. Ren
Anirudha Majumdar
92
17
0
11 Feb 2022
Support Vectors and Gradient Dynamics of Single-Neuron ReLU Networks
Support Vectors and Gradient Dynamics of Single-Neuron ReLU Networks
Sangmin Lee
Byeongsu Sim
Jong Chul Ye
MLT
39
0
0
11 Feb 2022
Controlling the Complexity and Lipschitz Constant improves polynomial
  nets
Controlling the Complexity and Lipschitz Constant improves polynomial nets
Zhenyu Zhu
Fabian Latorre
Grigorios G. Chrysos
Volkan Cevher
57
10
0
10 Feb 2022
An Exploration of Multicalibration Uniform Convergence Bounds
An Exploration of Multicalibration Uniform Convergence Bounds
Harrison Rosenberg
Robi Bhattacharjee
Kassem Fawaz
S. Jha
48
1
0
09 Feb 2022
The no-free-lunch theorems of supervised learning
The no-free-lunch theorems of supervised learning
T. Sterkenburg
Peter Grünwald
FedML
73
59
0
09 Feb 2022
Evaluating natural language processing models with generalization
  metrics that do not need access to any training or testing data
Evaluating natural language processing models with generalization metrics that do not need access to any training or testing data
Yaoqing Yang
Ryan Theisen
Liam Hodgkinson
Joseph E. Gonzalez
Kannan Ramchandran
Charles H. Martin
Michael W. Mahoney
145
18
0
06 Feb 2022
Non-Vacuous Generalisation Bounds for Shallow Neural Networks
Non-Vacuous Generalisation Bounds for Shallow Neural Networks
Felix Biggs
Benjamin Guedj
BDL
91
26
0
03 Feb 2022
Approximation bounds for norm constrained neural networks with
  applications to regression and GANs
Approximation bounds for norm constrained neural networks with applications to regression and GANs
Yuling Jiao
Yang Wang
Yunfei Yang
78
20
0
24 Jan 2022
Kernel Methods and Multi-layer Perceptrons Learn Linear Models in High
  Dimensions
Kernel Methods and Multi-layer Perceptrons Learn Linear Models in High Dimensions
Mojtaba Sahraee-Ardakan
M. Emami
Parthe Pandit
S. Rangan
A. Fletcher
90
9
0
20 Jan 2022
ExpertNet: A Symbiosis of Classification and Clustering
ExpertNet: A Symbiosis of Classification and Clustering
Shivin Srivastava
Kenji Kawaguchi
Vaibhav Rajan
18
1
0
17 Jan 2022
Neighborhood Region Smoothing Regularization for Finding Flat Minima In
  Deep Neural Networks
Neighborhood Region Smoothing Regularization for Finding Flat Minima In Deep Neural Networks
Yang Zhao
Hao Zhang
55
2
0
16 Jan 2022
On generalization bounds for deep networks based on loss surface
  implicit regularization
On generalization bounds for deep networks based on loss surface implicit regularization
Masaaki Imaizumi
Johannes Schmidt-Hieber
ODL
68
3
0
12 Jan 2022
Leveraging Unlabeled Data to Predict Out-of-Distribution Performance
Leveraging Unlabeled Data to Predict Out-of-Distribution Performance
Saurabh Garg
Sivaraman Balakrishnan
Zachary Chase Lipton
Behnam Neyshabur
Hanie Sedghi
OODDOOD
97
131
0
11 Jan 2022
Complexity from Adaptive-Symmetries Breaking: Global Minima in the
  Statistical Mechanics of Deep Neural Networks
Complexity from Adaptive-Symmetries Breaking: Global Minima in the Statistical Mechanics of Deep Neural Networks
Shaun Li
AI4CE
71
0
0
03 Jan 2022
On the Role of Neural Collapse in Transfer Learning
On the Role of Neural Collapse in Transfer Learning
Tomer Galanti
András Gyorgy
Marcus Hutter
SSL
88
93
0
30 Dec 2021
Depth and Feature Learning are Provably Beneficial for Neural Network
  Discriminators
Depth and Feature Learning are Provably Beneficial for Neural Network Discriminators
Carles Domingo-Enrich
MLTMDE
105
0
0
27 Dec 2021
Self-Ensembling GAN for Cross-Domain Semantic Segmentation
Self-Ensembling GAN for Cross-Domain Semantic Segmentation
Yonghao Xu
Fengxiang He
Bo Du
Dacheng Tao
Liangpei Zhang
GAN
66
17
0
15 Dec 2021
A New Measure of Model Redundancy for Compressed Convolutional Neural
  Networks
A New Measure of Model Redundancy for Compressed Convolutional Neural Networks
Feiqing Huang
Yuefeng Si
Yao Zheng
Guodong Li
67
1
0
09 Dec 2021
Effective dimension of machine learning models
Effective dimension of machine learning models
Amira Abbas
David Sutter
Alessio Figalli
Stefan Woerner
121
18
0
09 Dec 2021
Generalization Error Bounds for Iterative Recovery Algorithms Unfolded
  as Neural Networks
Generalization Error Bounds for Iterative Recovery Algorithms Unfolded as Neural Networks
Ekkehard Schnoor
Arash Behboodi
Holger Rauhut
53
14
0
08 Dec 2021
Spectral Complexity-scaled Generalization Bound of Complex-valued Neural
  Networks
Spectral Complexity-scaled Generalization Bound of Complex-valued Neural Networks
Haowen Chen
Fengxiang He
Shiye Lei
Dacheng Tao
25
0
0
07 Dec 2021
On the Convergence of Shallow Neural Network Training with Randomly
  Masked Neurons
On the Convergence of Shallow Neural Network Training with Randomly Masked Neurons
Fangshuo Liao
Anastasios Kyrillidis
118
16
0
05 Dec 2021
Learning with Noisy Labels by Efficient Transition Matrix Estimation to
  Combat Label Miscorrection
Learning with Noisy Labels by Efficient Transition Matrix Estimation to Combat Label Miscorrection
Seong Min Kye
Kwanghee Choi
Joonyoung Yi
Buru Chang
NoLa
96
17
0
29 Nov 2021
On the Robustness and Generalization of Deep Learning Driven Full
  Waveform Inversion
On the Robustness and Generalization of Deep Learning Driven Full Waveform Inversion
Chengyuan Deng
Youzuo Lin
OOD
56
2
0
28 Nov 2021
Generalization Performance of Empirical Risk Minimization on
  Over-parameterized Deep ReLU Nets
Generalization Performance of Empirical Risk Minimization on Over-parameterized Deep ReLU Nets
Shao-Bo Lin
Yao Wang
Ding-Xuan Zhou
ODL
80
6
0
28 Nov 2021
Stronger Generalization Guarantees for Robot Learning by Combining
  Generative Models and Real-World Data
Stronger Generalization Guarantees for Robot Learning by Combining Generative Models and Real-World Data
Abhinav Agarwal
Sushant Veer
Allen Z. Ren
Anirudha Majumdar
60
1
0
16 Nov 2021
Understanding the Generalization Benefit of Model Invariance from a Data
  Perspective
Understanding the Generalization Benefit of Model Invariance from a Data Perspective
Sicheng Zhu
Bang An
Furong Huang
51
26
0
10 Nov 2021
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