research
∙
09/20/2023
Rethinking Sensors Modeling: Hierarchical Information Enhanced Traffic Forecasting
With the acceleration of urbanization, traffic forecasting has become an...
share
research
∙
09/18/2023
PromptST: Prompt-Enhanced Spatio-Temporal Multi-Attribute Prediction
In the era of information explosion, spatio-temporal data mining serves ...
research
∙
09/12/2023
HAMUR: Hyper Adapter for Multi-Domain Recommendation
Multi-Domain Recommendation (MDR) has gained significant attention in re...
research
∙
09/05/2023
Scenario-Aware Hierarchical Dynamic Network for Multi-Scenario Recommendation
Click-Through Rate (CTR) prediction is a fundamental technique in recomm...
research
∙
09/02/2023
AdLER: Adversarial Training with Label Error Rectification for One-Shot Medical Image Segmentation
Accurate automatic segmentation of medical images typically requires lar...
research
∙
08/23/2023
Will More Expressive Graph Neural Networks do Better on Generative Tasks?
Graph generation poses a significant challenge as it involves predicting...
research
∙
08/14/2023
AutoAssign+: Automatic Shared Embedding Assignment in Streaming Recommendation
In the domain of streaming recommender systems, conventional methods for...
research
∙
07/10/2023
CT-based Subchondral Bone Microstructural Analysis in Knee Osteoarthritis via MR-Guided Distillation Learning
Background: MR-based subchondral bone effectively predicts knee osteoart...
research
∙
07/05/2023
Recommender Systems in the Era of Large Language Models (LLMs)
With the prosperity of e-commerce and web applications, Recommender Syst...
research
∙
06/08/2023
Hybrid Graph: A Unified Graph Representation with Datasets and Benchmarks for Complex Graphs
Graphs are widely used to encapsulate a variety of data formats, but rea...
research
∙
04/23/2023
Diffusion Model for GPS Trajectory Generation
With the deployment of GPS-enabled devices and data acquisition technolo...
research
∙
04/20/2023
Domain Generalization for Mammographic Image Analysis via Contrastive Learning
Mammographic image analysis is a fundamental problem in the computer-aid...
research
∙
04/16/2023
AutoSTL: Automated Spatio-Temporal Multi-Task Learning
Spatio-Temporal prediction plays a critical role in smart city construct...
research
∙
04/07/2023
Continuous Input Embedding Size Search For Recommender Systems
Latent factor models are the most popular backbones for today's recommen...
research
∙
03/20/2023
IMF: Interactive Multimodal Fusion Model for Link Prediction
Link prediction aims to identify potential missing triples in knowledge ...
research
∙
03/12/2023
AutoDenoise: Automatic Data Instance Denoising for Recommendations
Historical user-item interaction datasets are essential in training mode...
research
∙
03/11/2023
User Retention-oriented Recommendation with Decision Transformer
Improving user retention with reinforcement learning (RL) has attracted ...
research
∙
03/11/2023
AutoMLP: Automated MLP for Sequential Recommendations
Sequential recommender systems aim to predict users' next interested ite...
research
∙
02/12/2023
Denoising and Prompt-Tuning for Multi-Behavior Recommendation
In practical recommendation scenarios, users often interact with items u...
research
∙
02/08/2023
Multimodal Recommender Systems: A Survey
The recommender system (RS) has been an integral toolkit of online servi...
research
∙
02/07/2023
Multi-Task Deep Recommender Systems: A Survey
Multi-task learning (MTL) aims at learning related tasks in a unified mo...
research
∙
02/07/2023
Multi-Task Recommendations with Reinforcement Learning
In recent years, Multi-task Learning (MTL) has yielded immense success i...
research
∙
01/13/2023
RCPS: Rectified Contrastive Pseudo Supervision for Semi-Supervised Medical Image Segmentation
Medical image segmentation methods are generally designed as fully-super...
research
∙
12/20/2022
Data Augmentation on Graphs: A Survey
In recent years, graph representation learning has achieved remarkable s...
research
∙
09/21/2022
A Comprehensive Survey on Trustworthy Recommender Systems
As one of the most successful AI-powered applications, recommender syste...
research
∙
08/16/2022
"Are you okay, honey?": Recognizing Emotions among Couples Managing Diabetes in Daily Life using Multimodal Real-World Smartwatch Data
Couples generally manage chronic diseases together and the management ta...
research
∙
08/12/2022
TBI-GAN: An Adversarial Learning Approach for Data Synthesis on Traumatic Brain Segmentation
Brain network analysis for traumatic brain injury (TBI) patients is crit...
research
∙
07/24/2022
Federated Graph Contrastive Learning
Graph learning models are critical tools for researchers to explore grap...
research
∙
07/21/2022
Knowledge-enhanced Black-box Attacks for Recommendations
Recent studies have shown that deep neural networks-based recommender sy...
research
∙
04/25/2022
MLP4Rec: A Pure MLP Architecture for Sequential Recommendations
Self-attention models have achieved state-of-the-art performance in sequ...
research
∙
04/19/2022
AutoField: Automating Feature Selection in Deep Recommender Systems
Feature quality has an impactful effect on recommendation performance. T...
research
∙
04/04/2022
Automated Machine Learning for Deep Recommender Systems: A Survey
Deep recommender systems (DRS) are critical for current commercial onlin...
research
∙
02/25/2022
Building a 3-Player Mahjong AI using Deep Reinforcement Learning
Mahjong is a popular multi-player imperfect-information game developed i...
research
∙
08/12/2021
Graph Trend Networks for Recommendations
Recommender systems aim to provide personalized services to users and ar...
research
∙
07/19/2021
Structural Watermarking to Deep Neural Networks via Network Channel Pruning
In order to protect the intellectual property (IP) of deep neural networ...
research
∙
06/12/2021
AutoLoss: Automated Loss Function Search in Recommendations
Designing an effective loss function plays a crucial role in training de...
research
∙
06/10/2021
Automated Self-Supervised Learning for Graphs
Graph self-supervised learning has gained increasing attention due to it...
research
∙
05/04/2021
Data-Efficient Reinforcement Learning for Malaria Control
Sequential decision-making under cost-sensitive tasks is prohibitively d...
research
∙
02/10/2021
D2A U-Net: Automatic Segmentation of COVID-19 Lesions from CT Slices with Dilated Convolution and Dual Attention Mechanism
Coronavirus Disease 2019 (COVID-19) has caused great casualties and beco...
research
∙
11/01/2020
Watermarking Graph Neural Networks by Random Graphs
Many learning tasks require us to deal with graph data which contains ri...
research
∙
07/04/2020
Neural Interactive Collaborative Filtering
In this paper, we study collaborative filtering in an interactive settin...
research
∙
06/26/2020
Memory-efficient Embedding for Recommendations
Practical large-scale recommender systems usually contain thousands of f...
research
∙
05/17/2020
Attacking Black-box Recommendations via Copying Cross-domain User Profiles
Recently, recommender systems that aim to suggest personalized lists of ...
research
∙
02/28/2020
Jointly Learning to Recommend and Advertise
Online recommendation and advertising are two major income channels for ...
research
∙
02/26/2020
AutoEmb: Automated Embedding Dimensionality Search in Streaming Recommendations
Deep learning based recommender systems (DLRSs) often have embedding lay...
research
∙
01/20/2020
Exploring Spatio-Temporal and Cross-Type Correlations for Crime Prediction
Crime prediction plays an impactful role in enhancing public security an...
research
∙
09/09/2019
Deep Reinforcement Learning for Online Advertising in Recommender Systems
With the recent prevalence of Reinforcement Learning (RL), there have be...
research
∙
06/27/2019
Toward Simulating Environments in Reinforcement Learning Based Recommendations
With the recent advances in Reinforcement Learning (RL), there have been...
research
∙
02/11/2019
Model-Based Reinforcement Learning for Whole-Chain Recommendations
With the recent prevalence of Reinforcement Learning (RL), there have be...
research
∙
12/18/2018