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02/19/2023
Pseudo Contrastive Learning for Graph-based Semi-supervised Learning
Pseudo Labeling is a technique used to improve the performance of semi-s...
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10/19/2022
Self-supervised Heterogeneous Graph Pre-training Based on Structural Clustering
Recent self-supervised pre-training methods on Heterogeneous Information...
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08/13/2022
Entropy Induced Pruning Framework for Convolutional Neural Networks
Structured pruning techniques have achieved great compression performanc...
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02/03/2022
Reliable Community Search in Dynamic Networks
Local community search is an important research topic to support complex...
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12/22/2021
SkipNode: On Alleviating Over-smoothing for Deep Graph Convolutional Networks
Over-smoothing is a challenging problem, which degrades the performance ...
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08/28/2021
AP-10K: A Benchmark for Animal Pose Estimation in the Wild
Accurate animal pose estimation is an essential step towards understandi...
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06/08/2021
Multi-Agent Cooperative Bidding Games for Multi-Objective Optimization in e-Commercial Sponsored Search
Bid optimization for online advertising from single advertiser's perspec...
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05/18/2021
Non-contact Pain Recognition from Video Sequences with Remote Physiological Measurements Prediction
Automatic pain recognition is paramount for medical diagnosis and treatm...
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05/27/2020
Interpretable and Efficient Heterogeneous Graph Convolutional Network
Graph Convolutional Network (GCN) has achieved extraordinary success in ...
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07/24/2019
Personalized Attraction Enhanced Sponsored Search with Multi-task Learning
We study a novel problem of sponsored search (SS) for E-Commerce platfor...
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07/24/2019
IntentGC: a Scalable Graph Convolution Framework Fusing Heterogeneous Information for Recommendation
The remarkable progress of network embedding has led to state-of-the-art...
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06/24/2019
Query-based Interactive Recommendation by Meta-Path and Adapted Attention-GRU
Recently, interactive recommender systems are becoming increasingly popu...
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05/17/2019
Exact-K Recommendation via Maximal Clique Optimization
This paper targets to a novel but practical recommendation problem named...
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05/23/2018
Addressing the Item Cold-start Problem by Attribute-driven Active Learning
In recommender systems, cold-start issues are situations where no previo...
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05/23/2018
A Brand-level Ranking System with the Customized Attention-GRU Model
In e-commerce websites like Taobao, brand is playing a more important ro...
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03/01/2018
Deep Reinforcement Learning for Sponsored Search Real-time Bidding
Bidding optimization is one of the most critical problems in online adve...
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11/08/2017