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08/16/2023
STEM: Unleashing the Power of Embeddings for Multi-task Recommendation
Multi-task learning (MTL) has gained significant popularity in recommend...
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07/31/2023
TFE-GNN: A Temporal Fusion Encoder Using Graph Neural Networks for Fine-grained Encrypted Traffic Classification
Encrypted traffic classification is receiving widespread attention from ...
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06/13/2023
Time-aware Graph Structure Learning via Sequence Prediction on Temporal Graphs
Temporal Graph Learning, which aims to model the time-evolving nature of...
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10/30/2022
A Simple Hypergraph Kernel Convolution based on Discounted Markov Diffusion Process
Kernels on discrete structures evaluate pairwise similarities between ob...
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05/31/2022
Cascade Luminance and Chrominance for Image Retouching: More Like Artist
Photo retouching aims to adjust the luminance, contrast, and saturation ...
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03/31/2022
Hypergraph Convolutional Networks via Equivalency between Hypergraphs and Undirected Graphs
As a powerful tool for modeling complex relationships, hypergraphs are g...
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03/23/2022
PEAR: Personalized Re-ranking with Contextualized Transformer for Recommendation
The goal of recommender systems is to provide ordered item lists to user...
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03/20/2022
Fine-Tuning Graph Neural Networks via Graph Topology induced Optimal Transport
Recently, the pretrain-finetuning paradigm has attracted tons of attenti...
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01/24/2022
Neural Architecture Searching for Facial Attributes-based Depression Recognition
Recent studies show that depression can be partially reflected from huma...
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10/28/2021
UltraGCN: Ultra Simplification of Graph Convolutional Networks for Recommendation
With the recent success of graph convolutional networks (GCNs), they hav...
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09/26/2021
SimpleX: A Simple and Strong Baseline for Collaborative Filtering
Collaborative filtering (CF) is a widely studied research topic in recom...
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08/26/2021
Robust Model-based Reinforcement Learning for Autonomous Greenhouse Control
Due to the high efficiency and less weather dependency, autonomous green...
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08/03/2021
MBDP: A Model-based Approach to Achieve both Robustness and Sample Efficiency via Double Dropout Planning
Model-based reinforcement learning is a widely accepted solution for sol...
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06/10/2021
Learnable Hypergraph Laplacian for Hypergraph Learning
HyperGraph Convolutional Neural Networks (HGCNNs) have demonstrated thei...
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03/17/2021
Diversified Multiscale Graph Learning with Graph Self-Correction
Though the multiscale graph learning techniques have enabled advanced fe...
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11/04/2020
On Self-Distilling Graph Neural Network
Recently, the teacher-student knowledge distillation framework has demon...
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08/26/2020
Item Tagging for Information Retrieval: A Tripartite Graph Neural Network based Approach
Tagging has been recognized as a successful practice to boost relevance ...
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07/12/2020
Inverse Graph Identification: Can We Identify Node Labels Given Graph Labels?
Graph Identification (GI) has long been researched in graph learning and...
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01/17/2020
Rumor Detection on Social Media with Bi-Directional Graph Convolutional Networks
Social media has been developing rapidly in public due to its nature of ...
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11/16/2019
Maintaining Discrimination and Fairness in Class Incremental Learning
Deep neural networks (DNNs) have been applied in class incremental learn...
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04/13/2019
