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Dropout Rademacher Complexity of Deep Neural Networks
v1v2 (latest)

Dropout Rademacher Complexity of Deep Neural Networks

Science China Information Sciences (Sci. China Inf. Sci.), 2014
16 February 2014
Wei Gao
Zhi Zhou
ArXiv (abs)PDFHTML

Papers citing "Dropout Rademacher Complexity of Deep Neural Networks"

22 / 22 papers shown
ESA: Example Sieve Approach for Multi-Positive and Unlabeled Learning
ESA: Example Sieve Approach for Multi-Positive and Unlabeled LearningWeb Search and Data Mining (WSDM), 2024
Zhongnian Li
Meng Wei
Peng Ying
Xinzheng Xu
324
2
0
03 Dec 2024
On the Role of Noise in the Sample Complexity of Learning Recurrent
  Neural Networks: Exponential Gaps for Long Sequences
On the Role of Noise in the Sample Complexity of Learning Recurrent Neural Networks: Exponential Gaps for Long SequencesNeural Information Processing Systems (NeurIPS), 2023
A. F. Pour
H. Ashtiani
249
0
0
28 May 2023
Dropout Drops Double Descent
Dropout Drops Double DescentJapanese Journal of Statistics and Data Science (JSDS), 2023
Tianbao Yang
J. Suzuki
343
1
0
25 May 2023
Generalization and Estimation Error Bounds for Model-based Neural
  Networks
Generalization and Estimation Error Bounds for Model-based Neural NetworksInternational Conference on Learning Representations (ICLR), 2023
Avner Shultzman
Eyar Azar
M. Rodrigues
Yonina C. Eldar
174
13
0
19 Apr 2023
MESAHA-Net: Multi-Encoders based Self-Adaptive Hard Attention Network
  with Maximum Intensity Projections for Lung Nodule Segmentation in CT Scan
MESAHA-Net: Multi-Encoders based Self-Adaptive Hard Attention Network with Maximum Intensity Projections for Lung Nodule Segmentation in CT Scan
Muhammad Usman
Azka Rehman
Abdullah Shahid
S. Latif
Shi-Sub Byon
Sung Hyun Kim
T. M. Khan
Y. Shin
177
4
0
04 Apr 2023
An Anomaly Detection Method for Satellites Using Monte Carlo Dropout
An Anomaly Detection Method for Satellites Using Monte Carlo DropoutIEEE Transactions on Aerospace and Electronic Systems (TAES), 2022
Mohammad Amin Maleki Sadr
Yeying Zhu
Peng Hu
BDL
186
26
0
27 Nov 2022
Complementary Labels Learning with Augmented Classes
Complementary Labels Learning with Augmented ClassesSocial Science Research Network (SSRN), 2022
Zhongnian Li
Jian Zhang
Mengting Xu
Xinzheng Xu
Daoqiang Zhang
172
1
0
19 Nov 2022
Benefits of Additive Noise in Composing Classes with Bounded Capacity
Benefits of Additive Noise in Composing Classes with Bounded CapacityNeural Information Processing Systems (NeurIPS), 2022
A. F. Pour
H. Ashtiani
321
5
0
14 Jun 2022
Controlling Directions Orthogonal to a Classifier
Controlling Directions Orthogonal to a ClassifierInternational Conference on Learning Representations (ICLR), 2022
Yilun Xu
Hao He
T. Shen
Tommi Jaakkola
354
20
0
27 Jan 2022
Reflash Dropout in Image Super-Resolution
Reflash Dropout in Image Super-ResolutionComputer Vision and Pattern Recognition (CVPR), 2021
Xiangtao Kong
Xina Liu
Jinjin Gu
Yu Qiao
Chao Dong
UQCV
289
65
0
22 Dec 2021
What training reveals about neural network complexity
What training reveals about neural network complexityNeural Information Processing Systems (NeurIPS), 2021
Andreas Loukas
Marinos Poiitis
Stefanie Jegelka
319
12
0
08 Jun 2021
LocalDrop: A Hybrid Regularization for Deep Neural Networks
LocalDrop: A Hybrid Regularization for Deep Neural NetworksIEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2021
Ziqing Lu
Chang Xu
Bo Du
Takashi Ishida
Guang Dai
Masashi Sugiyama
238
17
0
01 Mar 2021
On Convergence and Generalization of Dropout Training
On Convergence and Generalization of Dropout TrainingNeural Information Processing Systems (NeurIPS), 2020
Poorya Mianjy
R. Arora
318
33
0
23 Oct 2020
U-Det: A Modified U-Net architecture with bidirectional feature network
  for lung nodule segmentation
U-Det: A Modified U-Net architecture with bidirectional feature network for lung nodule segmentation
Nikhil Varma Keetha
P. SamsonAnoshBabu
Chandra Sekhara Rao Annavarapu
211
48
0
20 Mar 2020
Dropout: Explicit Forms and Capacity Control
Dropout: Explicit Forms and Capacity ControlInternational Conference on Machine Learning (ICML), 2020
R. Arora
Peter L. Bartlett
Poorya Mianjy
Nathan Srebro
304
42
0
06 Mar 2020
A Theory of Usable Information Under Computational Constraints
A Theory of Usable Information Under Computational ConstraintsInternational Conference on Learning Representations (ICLR), 2020
Yilun Xu
Shengjia Zhao
Jiaming Song
Russell Stewart
Stefano Ermon
290
206
0
25 Feb 2020
Data Interpolating Prediction: Alternative Interpretation of Mixup
Data Interpolating Prediction: Alternative Interpretation of Mixup
Takuya Shimada
Shoichiro Yamaguchi
K. Hayashi
Sosuke Kobayashi
168
7
0
20 Jun 2019
On Dropout and Nuclear Norm Regularization
On Dropout and Nuclear Norm RegularizationInternational Conference on Machine Learning (ICML), 2019
Poorya Mianjy
R. Arora
309
24
0
28 May 2019
Dual-branch residual network for lung nodule segmentation
Dual-branch residual network for lung nodule segmentationApplied Soft Computing (Appl Soft Comput), 2019
Haichao Cao
Hong Liu
E. Song
C. Hung
Guangzhi Ma
Xiangyang Xu
Renchao Jin
Jianguo Lu
151
131
0
21 May 2019
Dating Ancient Paintings of Mogao Grottoes Using Deeply Learnt Visual
  Codes
Dating Ancient Paintings of Mogao Grottoes Using Deeply Learnt Visual Codes
Qingquan Li
Qin Zou
De Ma
Qian Wang
Song Wang
160
30
0
22 Oct 2018
Dropout with Expectation-linear Regularization
Dropout with Expectation-linear Regularization
Xuezhe Ma
Yingkai Gao
Zhiting Hu
Yaoliang Yu
Yuntian Deng
Eduard H. Hovy
UQCV
258
53
0
26 Sep 2016
Distribution-dependent concentration inequalities for tighter
  generalization bounds
Distribution-dependent concentration inequalities for tighter generalization bounds
Xinxing Wu
Junping Zhang
233
1
0
19 Jul 2016
1
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