49 citations · 241 across the 42 of their papers we have counts for
9 papers · 1 filter
Robust Visual Tracking using Multi-Frame Multi-Feature Joint Modeling
Peng Zhang, Shujian Yu, Jiamiao Xu +4
It remains a huge challenge to design effective and efficient trackers under complex scenarios, including occlusions, illumination changes and pose variations. To cope with this pr…
Simple stopping criteria for information theoretic feature selection
Shujian Yu, Jose C. Principe
Feature selection aims to select the smallest feature subset that yields the minimum generalization error. In the rich literature in feature selection, information theory-based app…
Multivariate Extension of Matrix-based Renyi's α-order Entropy Functional
Shujian Yu, Luis Gonzalo Sanchez Giraldo, Robert Jenssen +1
The matrix-based Renyi's α-order entropy functional was recently introduced using the normalized eigenspectrum of a Hermitian matrix of the projected data in a reproducing kernel H…
Request-and-Reverify: Hierarchical Hypothesis Testing for Concept Drift Detection with Expensive Labels
Shujian Yu, Xiaoyang Wang, Jose C. Principe
One important assumption underlying common classification models is the stationarity of the data. However, in real-world streaming applications, the data concept indicated by the j…
Coarse-to-Fine Salient Object Detection with Low-Rank Matrix Recovery
Qi Zheng, Shujian Yu, Xinge You +1
Low-Rank Matrix Recovery (LRMR) has recently been applied to saliency detection by decomposing image features into a low-rank component associated with background and a sparse comp…
Multi-view Hybrid Embedding: A Divide-and-Conquer Approach
Jiamiao Xu, Shujian Yu, Xinge You +3
We present a novel cross-view classification algorithm where the gallery and probe data come from different views. A popular approach to tackle this problem is the multi-view subsp…
Understanding Convolutional Neural Networks with Information Theory: An Initial Exploration
Shujian Yu, Kristoffer Wickstrøm, Robert Jenssen +1
The matrix-based Renyi's α-entropy functional and its multivariate extension were recently developed in terms of the normalized eigenspectrum of a Hermitian matrix of the projected…
Understanding Autoencoders with Information Theoretic Concepts
Shujian Yu, Jose C. Principe
Despite their great success in practical applications, there is still a lack of theoretical and systematic methods to analyze deep neural networks. In this paper, we illustrate an…
On Kernel Method-Based Connectionist Models and Supervised Deep Learning Without Backpropagation
Shiyu Duan, Shujian Yu, Yunmei Chen +1
We propose a novel family of connectionist models based on kernel machines and consider the problem of learning layer-by-layer a compositional hypothesis class, i.e., a feedforward…