5 citations · 9 across the 13 of their papers we have counts for
13 papers
Robust Multimodal Sentiment Analysis via Double Information Bottleneck
Huiting Huang, Tieliang Gong, Kai He +3
Multimodal sentiment analysis has received significant attention across diverse research domains. Despite advancements in algorithm design, existing approaches suffer from two crit…
ViLa-MIL: Dual-scale Vision-Language Multiple Instance Learning for Whole Slide Image Classification
Jiangbo Shi, Chen Li, Tieliang Gong +2
Multiple instance learning (MIL)-based framework has become the mainstream for processing the whole slide image (WSI) with giga-pixel size and hierarchical image context in digital…
How Does Distribution Matching Help Domain Generalization: An Information-theoretic Analysis
Yuxin Dong, Tieliang Gong, Hong Chen +3
Domain generalization aims to learn invariance across multiple training domains, thereby enhancing generalization against out-of-distribution data. While gradient or representation…
Understanding the Generalization Ability of Deep Learning Algorithms: A Kernelized Renyi's Entropy Perspective
Yuxin Dong, Tieliang Gong, Hong Chen +1
Recently, information theoretic analysis has become a popular framework for understanding the generalization behavior of deep neural networks. It allows a direct analysis for stoch…
Robust and Fast Measure of Information via Low-rank Representation
Yuxin Dong, Tieliang Gong, Shujian Yu +2
The matrix-based Rényi's entropy allows us to directly quantify information measures from given data, without explicit estimation of the underlying probability distribution. This i…
Optimal Randomized Approximations for Matrix based Renyi's Entropy
Yuxin Dong, Tieliang Gong, Shujian Yu +1
The Matrix-based Renyi's entropy enables us to directly measure information quantities from given data without the costly probability density estimation of underlying distributions…
Computationally Efficient Approximations for Matrix-based Renyi's Entropy
Tieliang Gong, Yuxin Dong, Shujian Yu +1
The recently developed matrix based Renyi's entropy enables measurement of information in data simply using the eigenspectrum of symmetric positive semi definite (PSD) matrices in…
Markov subsampling based Huber Criterion
Tieliang Gong, Yuxin Dong, Hong Chen +2
Subsampling is an important technique to tackle the computational challenges brought by big data. Many subsampling procedures fall within the framework of importance sampling, whic…
Regularized Modal Regression on Markov-dependent Observations: A Theoretical Assessment
Tielang Gong, Yuxin Dong, Hong Chen +3
Modal regression, a widely used regression protocol, has been extensively investigated in statistical and machine learning communities due to its robustness to outliers and heavy-t…
Meta Mask Correction for Nuclei Segmentation in Histopathological Image
Jiangbo Shi, Chang Jia, Zeyu Gao +3
Nuclei segmentation is a fundamental task in digital pathology analysis and can be automated by deep learning-based methods. However, the development of such an automated method re…
PIMIP: An Open Source Platform for Pathology Information Management and Integration
Jialun Wu, Anyu Mao, Xinrui Bao +5
Digital pathology plays a crucial role in the development of artificial intelligence in the medical field. The digital pathology platform can make the pathological resources digita…
BioIE: Biomedical Information Extraction with Multi-head Attention Enhanced Graph Convolutional Network
Jialun Wu, Yang Liu, Zeyu Gao +3
Constructing large-scaled medical knowledge graphs can significantly boost healthcare applications for medical surveillance, bring much attention from recent research. An essential…
A Precision Diagnostic Framework of Renal Cell Carcinoma on Whole-Slide Images using Deep Learning
Jialun Wu, Haichuan Zhang, Zeyu Gao +4
Diagnostic pathology, which is the basis and gold standard of cancer diagnosis, provides essential information on the prognosis of the disease and vital evidence for clinical treat…