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06/05/2023
Personalized Federated Domain Adaptation for Item-to-Item Recommendation
Item-to-Item (I2I) recommendation is an important function in most recom...
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05/15/2023
GCNSLIM: Graph Convolutional Network with Sparse Linear Methods for E-government Service Recommendation
Graph Convolutional Networks have made significant strides in Collabora-...
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12/07/2022
Few-shot Medical Image Segmentation with Cycle-resemblance Attention
Recently, due to the increasing requirements of medical imaging applicat...
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11/30/2022
Rethinking Causality-driven Robot Tool Segmentation with Temporal Constraints
Purpose: Vision-based robot tool segmentation plays a fundamental role i...
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11/21/2022
Twin-S: A Digital Twin for Skull-base Surgery
Purpose: Digital twins are virtual interactive models of the real world,...
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03/15/2022
CaRTS: Causality-driven Robot Tool Segmentation from Vision and Kinematics Data
Vision-based segmentation of the robotic tool during robot-assisted surg...
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02/01/2022
Context Uncertainty in Contextual Bandits with Applications to Recommender Systems
Recurrent neural networks have proven effective in modeling sequential u...
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09/13/2021
On the Sins of Image Synthesis Loss for Self-supervised Depth Estimation
Scene depth estimation from stereo and monocular imagery is critical for...
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08/20/2021
Influence Selection for Active Learning
The existing active learning methods select the samples by evaluating th...
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05/18/2021
Zero-Shot Recommender Systems
Performance of recommender systems (RS) relies heavily on the amount of ...
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07/20/2020
Cross-View Image Synthesis with Deformable Convolution and Attention Mechanism
Learning to generate natural scenes has always been a daunting task in c...
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06/17/2020
Gender Inequality in Research Productivity During the COVID-19 Pandemic
We study the disproportionate impact of the lockdown as a result of the ...
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11/25/2019
Shape-aware Feature Extraction for Instance Segmentation
Modern instance segmentation approaches mainly adopt a sequential paradi...
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04/01/2019
Unsupervised Inductive Whole-Graph Embedding by Preserving Graph Proximity
We introduce a novel approach to graph-level representation learning, wh...
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10/23/2018
Convolutional Set Matching for Graph Similarity
We introduce GSimCNN (Graph Similarity Computation via Convolutional Neu...
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09/10/2018
Convolutional Neural Networks for Fast Approximation of Graph Edit Distance
Graph Edit Distance (GED) computation is a core operation of many widely...
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08/16/2018
Graph Edit Distance Computation via Graph Neural Networks
Graph similarity search is among the most important graph-based applicat...
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07/08/2014