research
∙
05/02/2023
Understanding the Generalization Ability of Deep Learning Algorithms: A Kernelized Renyi's Entropy Perspective
Recently, information theoretic analysis has become a popular framework ...
share
research
∙
02/20/2023
On the Stability and Generalization of Triplet Learning
Triplet learning, i.e. learning from triplet data, has attracted much at...
research
∙
11/30/2022
Robust and Fast Measure of Information via Low-rank Representation
The matrix-based Rényi's entropy allows us to directly quantify informat...
research
∙
05/16/2022
Optimal Randomized Approximations for Matrix based Renyi's Entropy
The Matrix-based Renyi's entropy enables us to directly measure informat...
research
∙
03/09/2022
Error-based Knockoffs Inference for Controlled Feature Selection
Recently, the scheme of model-X knockoffs was proposed as a promising so...
research
∙
12/27/2021
Computationally Efficient Approximations for Matrix-based Renyi's Entropy
The recently developed matrix based Renyi's entropy enables measurement ...
research
∙
12/12/2021
Markov subsampling based Huber Criterion
Subsampling is an important technique to tackle the computational challe...
research
∙
11/24/2021
Meta Mask Correction for Nuclei Segmentation in Histopathological Image
Nuclei segmentation is a fundamental task in digital pathology analysis ...
research
∙
11/09/2021
PIMIP: An Open Source Platform for Pathology Information Management and Integration
Digital pathology plays a crucial role in the development of artificial ...
research
∙
10/26/2021
A Personalized Diagnostic Generation Framework Based on Multi-source Heterogeneous Data
Personalized diagnoses have not been possible due to sear amount of data...
research
∙
10/26/2021
W-Net: A Two-Stage Convolutional Network for Nucleus Detection in Histopathology Image
Pathological diagnosis is the gold standard for cancer diagnosis, but it...
research
∙
10/26/2021