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06/20/2023
LVM-Med: Learning Large-Scale Self-Supervised Vision Models for Medical Imaging via Second-order Graph Matching
Obtaining large pre-trained models that can be fine-tuned to new tasks w...
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04/02/2023
Learning by Grouping: A Multilevel Optimization Framework for Improving Fairness in Classification without Losing Accuracy
The integration of machine learning models in various real-world applica...
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02/18/2023
A Comprehensive Survey on Pretrained Foundation Models: A History from BERT to ChatGPT
The Pretrained Foundation Models (PFMs) are regarded as the foundation f...
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01/09/2023
Learning to compile smartly for program size reduction
Compiler optimization passes are an important tool for improving program...
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12/30/2022
DRG-Net: Interactive Joint Learning of Multi-lesion Segmentation and Classification for Diabetic Retinopathy Grading
Diabetic Retinopathy (DR) is a leading cause of vision loss in the world...
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12/04/2022
Joint Self-Supervised Image-Volume Representation Learning with Intra-Inter Contrastive Clustering
Collecting large-scale medical datasets with fully annotated samples for...
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11/15/2022
Type Information Utilized Event Detection via Multi-Channel GNNs in Electrical Power Systems
Event detection in power systems aims to identify triggers and event typ...
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02/16/2022
Not All Patches are What You Need: Expediting Vision Transformers via Token Reorganizations
Vision Transformers (ViTs) take all the image patches as tokens and cons...
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01/04/2022
Self-directed Machine Learning
Conventional machine learning (ML) relies heavily on manual design from ...
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12/01/2021
Learning from Mistakes based on Class Weighting with Application to Neural Architecture Search
Learning from mistakes is an effective learning approach widely used in ...
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11/30/2021
Improving Differentiable Architecture Search with a Generative Model
In differentiable neural architecture search (NAS) algorithms like DARTS...
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11/11/2021
Learning from Mistakes – A Framework for Neural Architecture Search
Learning from one's mistakes is an effective human learning technique wh...
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09/22/2021
Learning by Examples Based on Multi-level Optimization
Learning by examples, which learns to solve a new problem by looking int...
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03/12/2021
Interleaving Learning, with Application to Neural Architecture Search
Interleaving learning is a human learning technique where a learner inte...
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03/11/2021
Learning by Teaching, with Application to Neural Architecture Search
In human learning, an effective skill in improving learning outcomes is ...
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03/09/2021
Self-supervised Regularization for Text Classification
Text classification is a widely studied problem and has broad applicatio...
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12/28/2020
Learning by Ignoring
Learning by ignoring, which identifies less important things and exclude...
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12/23/2020
Learning by Self-Explanation, with Application to Neural Architecture Search
Learning by self-explanation, where students explain a learned topic to ...
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12/23/2020
Small-Group Learning, with Application to Neural Architecture Search
Small-group learning is a broadly used methodology in human learning and...
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12/11/2020
DSRNA: Differentiable Search of Robust Neural Architectures
In deep learning applications, the architectures of deep neural networks...
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12/09/2020
Skillearn: Machine Learning Inspired by Humans' Learning Skills
Humans, as the most powerful learners on the planet, have accumulated a ...
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11/30/2020
Learning by Passing Tests, with Application to Neural Architecture Search
Learning through tests is a broadly used methodology in human learning a...
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10/07/2020
Discriminative Cross-Modal Data Augmentation for Medical Imaging Applications
While deep learning methods have shown great success in medical image an...
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09/16/2020
TreeGAN: Incorporating Class Hierarchy into Image Generation
Conditional image generation (CIG) is a widely studied problem in comput...
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09/13/2020
Contrastive Self-supervised Learning for Graph Classification
Graph classification is a widely studied problem and has broad applicati...
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06/17/2020
XRayGAN: Consistency-preserving Generation of X-ray Images from Radiology Reports
To effectively train medical students to become qualified radiologists, ...
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06/16/2020
Differentially-private Federated Neural Architecture Search
Neural architecture search, which aims to automatically search for archi...
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05/16/2020
CERT: Contrastive Self-supervised Learning for Language Understanding
Pretrained language models such as BERT, GPT have shown great effectiven...
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05/11/2020
On the Generation of Medical Dialogues for COVID-19
Under the pandemic of COVID-19, people experiencing COVID19-related symp...
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04/07/2020
MedDialog: A Large-scale Medical Dialogue Dataset
Medical dialogue systems are promising in assisting in telemedicine to i...
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04/04/2020
Identifying Radiological Findings Related to COVID-19 from Medical Literature
Coronavirus disease 2019 (COVID-19) has infected more than one million i...
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03/30/2020
COVID-CT-Dataset: A CT Scan Dataset about COVID-19
CT scans are promising in providing accurate, fast, and cheap screening ...
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03/07/2020
PathVQA: 30000+ Questions for Medical Visual Question Answering
Is it possible to develop an "AI Pathologist" to pass the board-certifie...
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09/28/2019
Generalized Zero-shot ICD Coding
The International Classification of Diseases (ICD) is a list of classifi...
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05/28/2019
Adversarial Domain Adaptation Being Aware of Class Relationships
Adversarial training is a useful approach to promote the learning of tra...
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02/19/2019
Explaining a black-box using Deep Variational Information Bottleneck Approach
Briefness and comprehensiveness are necessary in order to give a lot of ...
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11/20/2018
Unsupervised Pseudo-Labeling for Extractive Summarization on Electronic Health Records
Extractive summarization is very useful for physicians to better manage ...
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11/19/2018
Stackelberg GAN: Towards Provable Minimax Equilibrium via Multi-Generator Architectures
We study the problem of alleviating the instability issue in the GAN tra...
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10/31/2018
Multimodal Machine Learning for Automated ICD Coding
This study presents a multimodal machine learning model to predict ICD-1...
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08/05/2018
Missing Value Imputation Based on Deep Generative Models
Missing values widely exist in many real-world datasets, which hinders t...
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02/16/2018
Orthogonality-Promoting Distance Metric Learning: Convex Relaxation and Theoretical Analysis
Distance metric learning (DML), which learns a distance metric from labe...
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12/06/2017
Convolutional Neural Networks for Medical Diagnosis from Admission Notes
Objective Develop an automatic diagnostic system which only uses textual...
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11/25/2017
Learning Less-Overlapping Representations
In representation learning (RL), how to make the learned representations...
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11/25/2017
Stacked Kernel Network
Kernel methods are powerful tools to capture nonlinear patterns behind d...
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11/23/2017
Diversity-Promoting Bayesian Learning of Latent Variable Models
To address three important issues involved in latent variable models (LV...
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11/22/2017
On the Automatic Generation of Medical Imaging Reports
Medical imaging is widely used in clinical practice for diagnosis and tr...
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11/21/2017
Effective Use of Bidirectional Language Modeling for Medical Named Entity Recognition
Biomedical named entity recognition (NER) is a fundamental task in text ...
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11/12/2017
Medical Diagnosis From Laboratory Tests by Combining Generative and Discriminative Learning
A primary goal of computational phenotype research is to conduct medical...
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11/11/2017
Towards Automated ICD Coding Using Deep Learning
International Classification of Diseases(ICD) is an authoritative health...
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11/04/2017
