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06/05/2023
Learning to Substitute Spans towards Improving Compositional Generalization
Despite the rising prevalence of neural sequence models, recent empirica...
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03/27/2023
Blind Image Quality Assessment via Vision-Language Correspondence: A Multitask Learning Perspective
We aim at advancing blind image quality assessment (BIQA), which predict...
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03/21/2023
Detecting the open-world objects with the help of the Brain
Open World Object Detection (OWOD) is a novel computer vision task with ...
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01/08/2023
FGAHOI: Fine-Grained Anchors for Human-Object Interaction Detection
Human-Object Interaction (HOI), as an important problem in computer visi...
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01/05/2023
CAT: LoCalization and IdentificAtion Cascade Detection Transformer for Open-World Object Detection
Open-world object detection (OWOD), as a more general and challenging go...
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12/12/2022
Hybrid Censored Quantile Regression Forest to Assess the Heterogeneous Effects
In many applications, heterogeneous treatment effects on a censored resp...
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11/16/2022
Disentangling Task Relations for Few-shot Text Classification via Self-Supervised Hierarchical Task Clustering
Few-Shot Text Classification (FSTC) imitates humans to learn a new text ...
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09/12/2022
Wasserstein Distributional Learning
Learning conditional densities and identifying factors that influence th...
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07/25/2022
A unified quantile framework reveals nonlinear heterogeneous transcriptome-wide associations
Transcriptome-wide association studies (TWAS) are powerful tools for ide...
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06/09/2022
Learning to generate imaginary tasks for improving generalization in meta-learning
The success of meta-learning on existing benchmarks is predicated on the...
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04/28/2022
Discriminative-Region Attention and Orthogonal-View Generation Model for Vehicle Re-Identification
Vehicle re-identification (Re-ID) is urgently demanded to alleviate thep...
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04/27/2022
Self-Supervised Text Erasing with Controllable Image Synthesis
Recent efforts on scene text erasing have shown promising results. Howev...
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10/26/2021
Meta-learning with an Adaptive Task Scheduler
To benefit the learning of a new task, meta-learning has been proposed t...
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06/17/2021
Frustratingly Easy Transferability Estimation
Transferability estimation has been an essential tool in selecting a pre...
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03/20/2021
Modeling Heterogeneity and Missing Data of Multiple Longitudinal Outcomes in Electronic Health Records
In electronic health records (EHRs), latent subgroups of patients may ex...
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07/26/2020
Don't Overlook the Support Set: Towards Improving Generalization in Meta-learning
Meta-learning has proven to be a powerful paradigm for transferring the ...
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07/09/2020
Parallel energy-stable solver for a coupled Allen-Cahn and Cahn-Hilliard system
In this paper, we study numerical methods for solving the coupled Allen-...
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07/04/2020
Multi-Site Infant Brain Segmentation Algorithms: The iSeg-2019 Challenge
To better understand early brain growth patterns in health and disorder,...
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05/07/2020
Hypergraph Learning for Identification of COVID-19 with CT Imaging
The coronavirus disease, named COVID-19, has become the largest global p...
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05/07/2020
Adaptive Feature Selection Guided Deep Forest for COVID-19 Classification with Chest CT
Chest computed tomography (CT) becomes an effective tool to assist the d...
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05/06/2020
Dual-Sampling Attention Network for Diagnosis of COVID-19 from Community Acquired Pneumonia
The coronavirus disease (COVID-19) is rapidly spreading all over the wor...
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04/30/2020
COVID-DA: Deep Domain Adaptation from Typical Pneumonia to COVID-19
The outbreak of novel coronavirus disease 2019 (COVID-19) has already in...
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03/22/2020
Large-Scale Screening of COVID-19 from Community Acquired Pneumonia using Infection Size-Aware Classification
The worldwide spread of coronavirus disease (COVID-19) has become a thre...
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03/12/2020
Fisher Deep Domain Adaptation
Deep domain adaptation models learn a neural network in an unlabeled tar...
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12/29/2019
Infant brain MRI segmentation with dilated convolution pyramid downsampling and self-attention
In this paper, we propose a dual aggregation network to adaptively aggre...
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11/17/2019
Collaborative Unsupervised Domain Adaptation for Medical Image Diagnosis
Deep learning based medical image diagnosis has shown great potential in...
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10/31/2019
Transferable End-to-End Aspect-based Sentiment Analysis with Selective Adversarial Learning
Joint extraction of aspects and sentiments can be effectively formulated...
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10/22/2019
Integrated Quantile RAnk Test (iQRAT) for gene-level associations in sequencing studies
Testing gene-based associations is the fundamental approach to identify ...
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10/07/2019
Graph Few-shot Learning via Knowledge Transfer
Towards the challenging problem of semi-supervised node classification, ...
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09/07/2019
Transferable Neural Processes for Hyperparameter Optimization
Automated machine learning aims to automate the whole process of machine...
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05/13/2019
Hierarchically Structured Meta-learning
In order to learn quickly with few samples, meta-learning utilizes prior...
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01/24/2019
Learning from Multiple Cities: A Meta-Learning Approach for Spatial-Temporal Prediction
Spatial-temporal prediction is a fundamental problem for constructing sm...
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11/16/2018
Exploiting Coarse-to-Fine Task Transfer for Aspect-level Sentiment Classification
Aspect-level sentiment classification (ASC) aims at identifying sentimen...
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05/19/2018
Learning to Multitask
Multitask learning has shown promising performance in many applications ...
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08/18/2017
Learning to Transfer
Transfer learning borrows knowledge from a source domain to facilitate l...
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03/03/2017