b'Lina Yao'

research

∙ 09/04/2023

Distributional Domain-Invariant Preference Matching for Cross-Domain Recommendation

Learning accurate cross-domain preference mappings in the absence of ove...

0 Jing Du, et al. ∙

research

∙ 08/28/2023

Reinforcement Learning for Generative AI: A Survey

Deep Generative AI has been a long-standing essential topic in the machi...

0 Yuanjiang Cao, et al. ∙

research

∙ 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...

0 Xiaocong Chen, et al. ∙

research

∙ 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...

0 Yao Liu, et al. ∙

research

∙ 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...

0 Jingcheng Li, et al. ∙

research

∙ 04/17/2023

Causal Disentangled Variational Auto-Encoder for Preference Understanding in Recommendation

Recommendation models are typically trained on observational user intera...

0 Siyu Wang, et al. ∙

research

∙ 04/17/2023

Causal Decision Transformer for Recommender Systems via Offline Reinforcement Learning

Reinforcement learning-based recommender systems have recently gained po...

0 Siyu Wang, et al. ∙

research

∙ 03/23/2023

Limits of Predictability in Top-N Recommendation

Top-N recommendation aims to recommend each consumer a small set of N it...

0 En Xu, et al. ∙

research

∙ 03/23/2023

Adversarially Contrastive Estimation of Conditional Neural Processes

Conditional Neural Processes (CNPs) formulate distributions over functio...

0 Zesheng Ye, et al. ∙

research

∙ 03/15/2023

Uncertainty-Aware Pedestrian Trajectory Prediction via Distributional Diffusion

Tremendous efforts have been devoted to pedestrian trajectory prediction...

0 Yao Liu, et al. ∙

research

∙ 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...

0 Yuanjiang Cao, et al. ∙

research

∙ 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 ...

7 Yun Li, et al. ∙

research

∙ 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...

0 Dawen Zhang, et al. ∙

research

∙ 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...

0 Zhe Liu, et al. ∙

research

∙ 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...

0 Can Li, et al. ∙

research

∙ 09/17/2022

Intrinsically Motivated Reinforcement Learning based Recommendation with Counterfactual Data Augmentation

Deep reinforcement learning (DRL) has been proven its efficiency in capt...

0 Xiaocong Chen, et al. ∙

research

∙ 09/01/2022

The Neural Process Family: Survey, Applications and Perspectives

The standard approaches to neural network implementation yield powerful ...

8 Saurav Jha, et al. ∙

research

∙ 08/22/2022

Design Automation for Fast, Lightweight, and Effective Deep Learning Models: A Survey

Deep learning technologies have demonstrated remarkable effectiveness in...

0 Dalin Zhang, et al. ∙

research

∙ 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...

0 Siyu Wang, et al. ∙

research

∙ 08/09/2022

IDNP: Interest Dynamics Modeling using Generative Neural Processes for Sequential Recommendation

Recent sequential recommendation models rely increasingly on consecutive...

0 Jing Du, et al. ∙

research

∙ 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...

0 Zesheng Ye, et al. ∙

research

∙ 07/08/2022

A Survey on Participant Selection for Federated Learning in Mobile Networks

Federated Learning (FL) is an efficient distributed machine learning par...

3 Behnaz Soltani, et al. ∙

research

∙ 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...

5 Hao Wang, et al. ∙

research

∙ 06/08/2022

Unsupervised Knowledge Adaptation for Passenger Demand Forecasting

Considering the multimodal nature of transport systems and potential cro...

0 Can Li, et al. ∙

research

∙ 05/20/2022

Towards Explanation for Unsupervised Graph-Level Representation Learning

Due to the superior performance of Graph Neural Networks (GNNs) in vario...

0 Qinghua Zheng, et al. ∙

research

∙ 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...

0 Zhe Liu, et al. ∙

research

∙ 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...

0 Yun Li, et al. ∙

research

∙ 04/01/2022

Model-agnostic Counterfactual Synthesis Policy for Interactive Recommendation

Interactive recommendation is able to learn from the interactive process...

0 Siyu Wang, et al. ∙

research

∙ 03/26/2022

Contrastive Graph Learning for Population-based fMRI Classification

Contrastive self-supervised learning has recently benefited fMRI classif...

0 Xuesong Wang, et al. ∙

research

∙ 03/08/2022

Contrastive Conditional Neural Processes

Conditional Neural Processes (CNPs) bridge neural networks with probabil...

0 Zesheng Ye, et al. ∙

research

∙ 01/06/2022

Balancing Generalization and Specialization in Zero-shot Learning

Zero-Shot Learning (ZSL) aims to transfer classification capability from...

0 Yun Li, et al. ∙

research

∙ 12/02/2021

Adversarial Robustness of Deep Reinforcement Learning based Dynamic Recommender Systems

Adversarial attacks, e.g., adversarial perturbations of the input and ad...

0 Siyu Wang, et al. ∙

research

∙ 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...

0 Zhe Liu, et al. ∙

research

∙ 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...

0 Yun Li, et al. ∙

research

∙ 10/21/2021

Locality-Sensitive Experience Replay for Online Recommendation

Online recommendation requires handling rapidly changing user preference...

0 Xiaocong Chen, et al. ∙

research

∙ 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...

0 Nuo Li, et al. ∙

research

∙ 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...

0 Xiaocong Chen, et al. ∙

research

∙ 09/02/2021

Global Convolutional Neural Processes

The ability to deal with uncertainty in machine learning models has beco...

42 Xuesong Wang, et al. ∙

research

∙ 05/03/2021

Generative Adversarial Reward Learning for Generalized Behavior Tendency Inference

Recent advances in reinforcement learning have inspired increasing inter...

0 Xiaocong Chen, et al. ∙

research

∙ 04/22/2021

Attribute-Modulated Generative Meta Learning for Zero-Shot Classification

Zero-shot learning (ZSL) aims to transfer knowledge from seen classes to...

0 Yun Li, et al. ∙

research

∙ 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...

0 Qingyang Li, et al. ∙

research

∙ 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...

0 Zhe Liu, et al. ∙

research

∙ 02/01/2021

An Internet of Things Service Roadmap

We propose a roadmap for leveraging the tremendous opportunities the Int...

0 Athman Bouguettaya, et al. ∙

research

∙ 11/04/2020

Generative Inverse Deep Reinforcement Learning for Online Recommendation

Deep reinforcement learning enables an agent to capture user's interest ...

0 Xiaocong Chen, et al. ∙

research

∙ 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...

10 Can Li, et al. ∙

research

∙ 09/11/2020

TRec: Sequential Recommender Based On Latent Item Trend Information

Recommendation system plays an important role in online web applications...

0 Ye Tao, et al. ∙

research

∙ 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...

0 Zhe Liu, et al. ∙

research

∙ 07/14/2020

Spectrum-Guided Adversarial Disparity Learning

It has been a significant challenge to portray intraclass disparity prec...

0 Zhe Liu, et al. ∙

research

∙ 07/14/2020

Recommender Systems for the Internet of Things: A Survey

Recommendation represents a vital stage in developing and promoting the ...

0 May Altulyan, et al. ∙

research

∙ 07/07/2020

MAMO: Memory-Augmented Meta-Optimization for Cold-start Recommendation

A common challenge for most current recommender systems is the cold-star...

0 Manqing Dong, et al. ∙

Lina Yao

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