Year  Title  Author 
2017

Generalization in Deep Learning 
K Kawaguchi, LP Kaelbling, Y Bengio

2017

Deep Domain Generalization with Structured LowRank Constraint 
Z Ding, Y Fu

2017

Computing Nonvacuous Generalization Bounds for Deep (Stochastic) Neural Networks with Many More Parameters than Training Data 
GK Dziugaite, DM Roy

2017

Theory of Deep Learning III: Generalization Properties of SGD 
C Zhang, Q Liao, A Rakhlin, K Sridharan, B Miranda

2017

Understanding Deep Learning Generalization by Maximum Entropy 
G Zheng, J Sang, C Xu

2017

Exploring Generalization in Deep Learning 
B Neyshabur, S Bhojanapalli, D McAllester, N Srebro

2017

Improving the Generalization Ability of Restricted Boltzmann Machines via Theta Pure Dependency 
Q Xu, Y Hou

2017

Generalization of Deep Neural Networks for Chest Pathology Classification in XRays Using Generative Adversarial Networks 
H Salehinejad, S Valaee, T Dowdell, E Colak, J Barfett

2017

Human Activity Recognition Using Radial Basis Function Neural Network Trained via a Minimization of Localized Generalization Error 
S Zhang, WWY Ng, J Zhang, CD Nugent

2017

Improving Output Uncertainty Estimation and Generalization in Deep Learning via Neural Network Gaussian Processes 
T Iwata, Z Ghahramani

2017

On Generalization and Regularization in Deep Learning 
P Lemberger

2016

SelectAdditive Learning: Improving Crossindividual Generalization in Multimodal Sentiment Analysis 
H Wang, A Meghawat, LP Morency, EP Xing

2016

On LargeBatch Training for Deep Learning: Generalization Gap and Sharp Minima 
NS Keskar, D Mudigere, J Nocedal, M Smelyanskiy

2016

Understanding deep learning requires rethinking generalization 
C Zhang, S Bengio, M Hardt, B Recht, O Vinyals

2016

Fuzzy rulebased models with interactive rules and their granular generalization 
X Hu, W Pedrycz, O Castillo, P Melin

2016

OneShot Generalization in Deep Generative Models 
DJ Rezende, S Mohamed, I Danihelka, K Gregor

2016

The Role of Typicality in Object Classification: Improving The Generalization Capacity of Convolutional Neural Networks 
B Saleh, A Elgammal, J Feldman

2016

NFLB dropout: Improve generalization ability by dropping out the bestA biologically inspired adaptive dropout method for unsupervised learning 
P Yin, L Qi, X Xi, B Zhang, H Qiao

2016

Simplified Information Maximization for Improving Generalization Performance in MultiLayered Neural Networks 
R Kamimura

2016

Domain Adaptation and Domain Generalization with Representation Learning 
M Ghifary

2016

A feasibility study of an autoencoder metamodel for improving generalization capabilities on training sets of small sizes 
A Potapov, V Potapova, M Peterson

2016

Assessing generalization ability of Majority Vote Point Classifiers 
RK Sevakula, NK Verma

2015

Rényi Divergence Based Generalization for Learning of Classification Restricted Boltzmann Machines 
Q Yu, Y Hou, X Zhao, G Cheng

2015

Generalization in Native Language Identification: Learners versus Scientists 
S Stehwien, S Pado

2015

On the Generalization Error Bounds of Neural Networks under DiversityInducing Mutual Angular Regularization 
P Xie, Y Deng, E Xing

2014

SimNets: A Generalization of Convolutional Networks 
N Cohen, A Shashua
