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05/31/2023
Representer Point Selection for Explaining Regularized High-dimensional Models
We introduce a novel class of sample-based explanations we term high-dim...
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05/21/2023
PINA: Leveraging Side Information in eXtreme Multi-label Classification via Predicted Instance Neighborhood Aggregation
The eXtreme Multi-label Classification (XMC) problem seeks to find relev...
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08/23/2022
Retinal Structure Detection in OCTA Image via Voting-based Multi-task Learning
Automated detection of retinal structures, such as retinal vessels (RV),...
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07/25/2022
Sparse-based Domain Adaptation Network for OCTA Image Super-Resolution Reconstruction
Retinal Optical Coherence Tomography Angiography (OCTA) with high-resolu...
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10/29/2021
Node Feature Extraction by Self-Supervised Multi-scale Neighborhood Prediction
Learning on graphs has attracted significant attention in the learning c...
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10/01/2021
Fast Multi-Resolution Transformer Fine-tuning for Extreme Multi-label Text Classification
Extreme multi-label text classification (XMC) seeks to find relevant lab...
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06/23/2021
Extreme Multi-label Learning for Semantic Matching in Product Search
We consider the problem of semantic matching in product search: given a ...
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02/26/2021
3D Vessel Reconstruction in OCT-Angiography via Depth Map Estimation
Optical Coherence Tomography Angiography (OCTA) has been increasingly us...
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07/10/2020
ROSE: A Retinal OCT-Angiography Vessel Segmentation Dataset and New Model
Optical Coherence Tomography Angiography (OCT-A) is a non-invasive imagi...
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03/08/2020
Trajectory Grouping with Curvature Regularization for Tubular Structure Tracking
Tubular structure tracking is an important and difficult problem in the ...
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05/08/2019
AutoAssist: A Framework to Accelerate Training of Deep Neural Networks
Deep neural networks have yielded superior performance in many applicati...
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09/21/2018
Minimal Paths for Tubular Structure Segmentation with Coherence Penalty and Adaptive Anisotropy
The minimal path method has proven to be particularly useful and efficie...
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03/25/2018
Stabilizing Gradients for Deep Neural Networks via Efficient SVD Parameterization
Vanishing and exploding gradients are two of the main obstacles in train...
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03/17/2018
Learning Long Term Dependencies via Fourier Recurrent Units
It is a known fact that training recurrent neural networks for tasks tha...
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07/21/2017
Retinal Microaneurysms Detection using Local Convergence Index Features
Retinal microaneurysms are the earliest clinical sign of diabetic retino...
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10/20/2016
Retrieving challenging vessel connections in retinal images by line co-occurrence statistics
Natural images contain often curvilinear structures, which might be disc...
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05/31/2016