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09/04/2023
Distributional Domain-Invariant Preference Matching for Cross-Domain Recommendation
Learning accurate cross-domain preference mappings in the absence of ove...
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08/28/2023
Reinforcement Learning for Generative AI: A Survey
Deep Generative AI has been a long-standing essential topic in the machi...
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08/22/2023
On the Opportunities and Challenges of Offline Reinforcement Learning for Recommender Systems
Reinforcement learning serves as a potent tool for modeling dynamic user...
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07/22/2023
Two-stream Multi-level Dynamic Point Transformer for Two-person Interaction Recognition
As a fundamental aspect of human life, two-person interactions contain m...
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05/05/2023
Distilled Mid-Fusion Transformer Networks for Multi-Modal Human Activity Recognition
Human Activity Recognition is an important task in many human-computer c...
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04/17/2023
Causal Disentangled Variational Auto-Encoder for Preference Understanding in Recommendation
Recommendation models are typically trained on observational user intera...
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04/17/2023
Causal Decision Transformer for Recommender Systems via Offline Reinforcement Learning
Reinforcement learning-based recommender systems have recently gained po...
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03/23/2023
Limits of Predictability in Top-N Recommendation
Top-N recommendation aims to recommend each consumer a small set of N it...
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03/23/2023
Adversarially Contrastive Estimation of Conditional Neural Processes
Conditional Neural Processes (CNPs) formulate distributions over functio...
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03/15/2023
Uncertainty-Aware Pedestrian Trajectory Prediction via Distributional Diffusion
Tremendous efforts have been devoted to pedestrian trajectory prediction...
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03/07/2023
Guided Image-to-Image Translation by Discriminator-Generator Communication
The goal of Image-to-image (I2I) translation is to transfer an image fro...
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03/01/2023
Distilled Reverse Attention Network for Open-world Compositional Zero-Shot Learning
Open-World Compositional Zero-Shot Learning (OW-CZSL) aims to recognize ...
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02/07/2023
To Be Forgotten or To Be Fair: Unveiling Fairness Implications of Machine Unlearning Methods
The right to be forgotten (RTBF) is motivated by the desire of people no...
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11/05/2022
Simple Primitives with Feasibility- and Contextuality-Dependence for Open-World Compositional Zero-shot Learning
The task of Compositional Zero-Shot Learning (CZSL) is to recognize imag...
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10/26/2022
A Bibliometric Analysis and Review on Reinforcement Learning for Transportation Applications
Transportation is the backbone of the economy and urban development. Imp...
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09/17/2022
Intrinsically Motivated Reinforcement Learning based Recommendation with Counterfactual Data Augmentation
Deep reinforcement learning (DRL) has been proven its efficiency in capt...
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09/01/2022
The Neural Process Family: Survey, Applications and Perspectives
The standard approaches to neural network implementation yield powerful ...
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08/22/2022
Design Automation for Fast, Lightweight, and Effective Deep Learning Models: A Survey
Deep learning technologies have demonstrated remarkable effectiveness in...
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08/10/2022
Deep Reinforcement Learning for Dynamic Recommendation with Model-agnostic Counterfactual Policy Synthesis
Recent advances in recommender systems have proved the potential of Rein...
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08/09/2022
IDNP: Interest Dynamics Modeling using Generative Neural Processes for Sequential Recommendation
Recent sequential recommendation models rely increasingly on consecutive...
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08/07/2022
See What You See: Self-supervised Cross-modal Retrieval of Visual Stimuli from Brain Activity
Recent studies demonstrate the use of a two-stage supervised framework t...
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07/08/2022
A Survey on Participant Selection for Federated Learning in Mobile Networks
Federated Learning (FL) is an efficient distributed machine learning par...
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07/02/2022
Enabling Harmonious Human-Machine Interaction with Visual-Context Augmented Dialogue System: A Review
The intelligent dialogue system, aiming at communicating with humans har...
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06/08/2022
Unsupervised Knowledge Adaptation for Passenger Demand Forecasting
Considering the multimodal nature of transport systems and potential cro...
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05/20/2022
Towards Explanation for Unsupervised Graph-Level Representation Learning
Due to the superior performance of Graph Neural Networks (GNNs) in vario...
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05/03/2022
Disentangled and Side-aware Unsupervised Domain Adaptation for Cross-dataset Subjective Tinnitus Diagnosis
EEG-based tinnitus classification is a valuable tool for tinnitus diagno...
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05/03/2022
Side-aware Meta-Learning for Cross-Dataset Listener Diagnosis with Subjective Tinnitus
With the development of digital technology, machine learning has paved t...
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04/01/2022
Model-agnostic Counterfactual Synthesis Policy for Interactive Recommendation
Interactive recommendation is able to learn from the interactive process...
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03/26/2022
Contrastive Graph Learning for Population-based fMRI Classification
Contrastive self-supervised learning has recently benefited fMRI classif...
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03/08/2022
Contrastive Conditional Neural Processes
Conditional Neural Processes (CNPs) bridge neural networks with probabil...
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01/06/2022
Balancing Generalization and Specialization in Zero-shot Learning
Zero-Shot Learning (ZSL) aims to transfer classification capability from...
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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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12/01/2021
Rethink, Revisit, Revise: A Spiral Reinforced Self-Revised Network for Zero-Shot Learning
Current approaches to Zero-Shot Learning (ZSL) struggle to learn general...
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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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10/11/2021
AskMe: Joint Individual-level and Community-level Behavior Interaction for Question Recommendation
Questions in Community Question Answering (CQA) sites are recommended to...
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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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03/20/2021
RLTIR: Activity-based Interactive Person Identification based on Reinforcement Learning Tree
Identity recognition plays an important role in ensuring security in our...
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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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02/01/2021
An Internet of Things Service Roadmap
We propose a roadmap for leveraging the tremendous opportunities the Int...
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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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09/12/2020
Knowledge Adaption for Demand Prediction based on Multi-task Memory Neural Network
Accurate demand forecasting of different public transport modes(e.g., bu...
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09/11/2020
TRec: Sequential Recommender Based On Latent Item Trend Information
Recommendation system plays an important role in online web applications...
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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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07/07/2020