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09/19/2023
FRAMU: Attention-based Machine Unlearning using Federated Reinforcement Learning
Machine Unlearning is an emerging field that addresses data privacy issu...
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09/04/2023
Zero-shot information extraction from radiological reports using ChatGPT
Electronic health records contain an enormous amount of valuable informa...
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08/03/2023
Unsupervised Multiplex Graph Learning with Complementary and Consistent Information
Unsupervised multiplex graph learning (UMGL) has been shown to achieve s...
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06/20/2023
A Universal Unbiased Method for Classification from Aggregate Observations
In conventional supervised classification, true labels are required for ...
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05/28/2023
Using Caterpillar to Nibble Small-Scale Images
Recently, MLP-based models have become popular and attained significant ...
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05/26/2023
An Efficient Membership Inference Attack for the Diffusion Model by Proximal Initialization
Recently, diffusion models have achieved remarkable success in generatin...
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05/10/2023
Exploring the Landscape of Machine Unlearning: A Comprehensive Survey and Taxonomy
Machine unlearning (MU) is gaining increasing attention due to the need ...
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04/11/2023
Explicit and Implicit Semantic Ranking Framework
The core challenge in numerous real-world applications is to match an in...
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03/21/2023
Self-Paced Neutral Expression-Disentangled Learning for Facial Expression Recognition
The accuracy of facial expression recognition is typically affected by t...
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01/12/2023
Unbiased estimation and asymptotically valid inference in multivariable Mendelian randomization with many weak instrumental variables
Mendelian randomization (MR) is a popular epidemiological approach that ...
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03/17/2022
GATE: Graph CCA for Temporal SElf-supervised Learning for Label-efficient fMRI Analysis
In this work, we focus on the challenging task, neuro-disease classifica...
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12/19/2021
FedNI: Federated Graph Learning with Network Inpainting for Population-Based Disease Prediction
Graph Convolutional Neural Networks (GCNs) are widely used for graph ana...
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06/25/2021
Self-paced Principal Component Analysis
Principal Component Analysis (PCA) has been widely used for dimensionali...
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06/21/2021
Multi-VAE: Learning Disentangled View-common and View-peculiar Visual Representations for Multi-view Clustering
Multi-view clustering, a long-standing and important research problem, f...
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06/21/2021
Contrastive Multi-Modal Clustering
Multi-modal clustering, which explores complementary information from mu...
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05/07/2021
Self-paced Resistance Learning against Overfitting on Noisy Labels
Noisy labels composed of correct and corrupted ones are pervasive in pra...
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02/16/2021
Structured Graph Learning for Scalable Subspace Clustering: From Single-view to Multi-view
Graph-based subspace clustering methods have exhibited promising perform...
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05/07/2020
Joint Prediction and Time Estimation of COVID-19 Developing Severe Symptoms using Chest CT Scan
With the rapidly worldwide spread of Coronavirus disease (COVID-19), it ...
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04/29/2020
Neural Network Retraining for Model Serving
We propose incremental (re)training of a neural network model to cope wi...
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01/07/2020
Frosting Weights for Better Continual Training
Training a neural network model can be a lifelong learning process and i...
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01/07/2020
Listwise Learning to Rank by Exploring Unique Ratings
In this paper, we propose new listwise learning-to-rank models that miti...
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02/28/2019
High dynamic range image forensics using cnn
High dynamic range (HDR) imaging has recently drawn much attention in mu...
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09/14/2018
Identification of multi-scale hierarchical brain functional networks using deep matrix factorization
We present a deep semi-nonnegative matrix factorization method for ident...
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09/05/2017
Semantic Document Distance Measures and Unsupervised Document Revision Detection
In this paper, we model the document revision detection problem as a min...
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08/29/2017