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12/02/2021
Adversarial Robustness of Deep Reinforcement Learning based Dynamic Recommender Systems
Adversarial attacks, e.g., adversarial perturbations of the input and ad...
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11/03/2021
An Entropy-guided Reinforced Partial Convolutional Network for Zero-Shot Learning
Zero-Shot Learning (ZSL) aims to transfer learned knowledge from observe...
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10/21/2021
Locality-Sensitive Experience Replay for Online Recommendation
Online recommendation requires handling rapidly changing user preference...
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09/08/2021
A Survey of Deep Reinforcement Learning in Recommender Systems: A Systematic Review and Future Directions
In light of the emergence of deep reinforcement learning (DRL) in recomm...
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09/02/2021
Global Convolutional Neural Processes
The ability to deal with uncertainty in machine learning models has beco...
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05/03/2021
Generative Adversarial Reward Learning for Generalized Behavior Tendency Inference
Recent advances in reinforcement learning have inspired increasing inter...
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04/22/2021
Attribute-Modulated Generative Meta Learning for Zero-Shot Classification
Zero-shot learning (ZSL) aims to transfer knowledge from seen classes to...
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03/03/2021
Task Aligned Generative Meta-learning for Zero-shot Learning
Zero-shot learning (ZSL) refers to the problem of learning to classify i...
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11/04/2020
Generative Inverse Deep Reinforcement Learning for Online Recommendation
Deep reinforcement learning enables an agent to capture user's interest ...
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07/14/2020
Face to Purchase: Predicting Consumer Choices with Structured Facial and Behavioral Traits Embedding
Predicting consumers' purchasing behaviors is critical for targeted adve...
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07/14/2020
Spectrum-Guided Adversarial Disparity Learning
It has been a significant challenge to portray intraclass disparity prec...
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07/14/2020
Recommender Systems for the Internet of Things: A Survey
Recommendation represents a vital stage in developing and promoting the ...
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07/06/2020
Adaptive Graph Convolutional Recurrent Network for Traffic Forecasting
Modeling complex spatial and temporal correlations in the correlated tim...
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07/03/2020
Depression Detection with Multi-Modalities Using a Hybrid Deep Learning Model on Social Media
Social networks enable people to interact with one another by sharing in...
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06/27/2020
Causality Learning: A New Perspective for Interpretable Machine Learning
Recent years have witnessed the rapid growth of machine learning in a wi...
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06/14/2020
Adversarial Attacks and Detection on Reinforcement Learning-Based Interactive Recommender Systems
Adversarial attacks pose significant challenges for detecting adversaria...
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05/12/2020
Agglomerative Neural Networks for Multi-view Clustering
Conventional multi-view clustering methods seek for a view consensus thr...
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05/03/2020
Multi-Center Federated Learning
Federated learning has received great attention for its capability to tr...
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04/18/2020
Are You A Risk Taker? Adversarial Learning of Asymmetric Cross-Domain Alignment for Risk Tolerance Prediction
Most current studies on survey analysis and risk tolerance modelling lac...
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04/17/2020
Knowledge-guided Deep Reinforcement Learning for Interactive Recommendation
Interactive recommendation aims to learn from dynamic interactions betwe...
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04/08/2020
Trust in Recommender Systems: A Deep Learning Perspective
A significant remaining challenge for existing recommender systems is th...
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05/24/2019
STG2Seq: Spatial-temporal Graph to Sequence Model for Multi-step Passenger Demand Forecasting
Multi-step passenger demand forecasting is a crucial task in on-demand v...
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05/10/2019
A Survey on Deep Learning based Brain Computer Interface: Recent Advances and New Frontiers
Brain-Computer Interface (BCI) bridges the human's neural world and the ...
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12/24/2018
Automatic Device Classification from Network Traffic Streams of Internet of Things
With the widespread adoption of Internet of Things (IoT), billions of ev...
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10/26/2018
Software Expert Discovery via Knowledge Domain Embeddings in a Collaborative Network
Community Question Answering (CQA) websites can be claimed as the most m...
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08/03/2018
Expert Recommendation via Tensor Factorization with Regularizing Hierarchical Topical Relationships
Knowledge acquisition and exchange are generally crucial yet costly for ...
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07/15/2018
A Survey on Expert Recommendation in Community Question Answering
Community question answering (CQA) represents the type of Web applicatio...
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06/21/2018
GrCAN: Gradient Boost Convolutional Autoencoder with Neural Decision Forest
Random forest and deep neural network are two schools of effective class...
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05/17/2018
Interpretable Parallel Recurrent Neural Networks with Convolutional Attentions for Multi-Modality Activity Modeling
Multimodal features play a key role in wearable sensor-based human activ...
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05/09/2018
Opinion Fraud Detection via Neural Autoencoder Decision Forest
Online reviews play an important role in influencing buyers' daily purch...
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02/12/2018
Know Your Mind: Adaptive Brain Signal Classification with Reinforced Attentive Convolutional Neural Networks
Electroencephalography (EEG) signals reflect activities on certain brain...
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11/21/2017
Fullie and Wiselie: A Dual-Stream Recurrent Convolutional Attention Model for Activity Recognition
Multimodal features play a key role in wearable sensor based Human Activ...
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09/26/2017
Multi-Person Brain Activity Recognition via Comprehensive EEG Signal Analysis
An electroencephalography (EEG) based brain activity recognition is a fu...
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08/07/2017
From Appearance to Essence: Comparing Truth Discovery Methods without Using Ground Truth
Truth discovery has been widely studied in recent years as a fundamental...
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08/07/2017