33 citations · 58 across the 7 of their papers we have counts for
10 papers
A Probabilistic Representation of DNNs: Bridging Mutual Information and Generalization
Xinjie Lan, Kenneth Barner
Recently, Mutual Information (MI) has attracted attention in bounding the generalization error of Deep Neural Networks (DNNs). However, it is intractable to accurately estimate the…
A Probabilistic Representation of Deep Learning for Improving The Information Theoretic Interpretability
Xinjie Lan, Kenneth E. Barner
In this paper, we propose a probabilistic representation of MultiLayer Perceptrons (MLPs) to improve the information-theoretic interpretability. Above all, we demonstrate that the…
PAC-Bayesian Generalization Bounds for MultiLayer Perceptrons
Xinjie Lan, Xin Guo, Kenneth E. Barner
We study PAC-Bayesian generalization bounds for Multilayer Perceptrons (MLPs) with the cross entropy loss. Above all, we introduce probabilistic explanations for MLPs in two aspect…
Audio-video Emotion Recognition in the Wild using Deep Hybrid Networks
Xin Guo, Luisa F. Polanía, Kenneth E. Barner
This paper presents an audiovisual-based emotion recognition hybrid network. While most of the previous work focuses either on using deep models or hand-engineered features extract…
Explicitly Bayesian Regularizations in Deep Learning
Xinjie Lan, Kenneth E. Barner
Generalization is essential for deep learning. In contrast to previous works claiming that Deep Neural Networks (DNNs) have an implicit regularization implemented by the stochastic…
Automatic Group Cohesiveness Detection With Multi-modal Features
Bin Zhu, Xin Guo, Kenneth Barner +1
Group cohesiveness is a compelling and often studied composition in group dynamics and group performance. The enormous number of web images of groups of people can be used to devel…