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09/18/2023
CaT: Balanced Continual Graph Learning with Graph Condensation
Continual graph learning (CGL) is purposed to continuously update a grap...
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09/08/2023
UQ at #SMM4H 2023: ALEX for Public Health Analysis with Social Media
As social media becomes increasingly popular, more and more activities r...
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08/06/2023
Cal-SFDA: Source-Free Domain-adaptive Semantic Segmentation with Differentiable Expected Calibration Error
The prevalence of domain adaptive semantic segmentation has prompted con...
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08/05/2023
OrcoDCS: An IoT-Edge Orchestrated Online Deep Compressed Sensing Framework
Compressed data aggregation (CDA) over wireless sensor networks (WSNs) i...
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08/01/2023
Zero-Shot Learning by Harnessing Adversarial Samples
Zero-Shot Learning (ZSL) aims to recognize unseen classes by generalizin...
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07/16/2023
Revisiting Domain-Adaptive 3D Object Detection by Reliable, Diverse and Class-balanced Pseudo-Labeling
Unsupervised domain adaptation (DA) with the aid of pseudo labeling tech...
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07/16/2023
KECOR: Kernel Coding Rate Maximization for Active 3D Object Detection
Achieving a reliable LiDAR-based object detector in autonomous driving i...
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06/18/2023
Focusing on Relevant Responses for Multi-modal Rumor Detection
In the absence of an authoritative statement about a rumor, people may e...
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05/01/2023
Explicit Knowledge Graph Reasoning for Conversational Recommendation
Traditional recommender systems estimate user preference on items purely...
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02/10/2023
Semi-decentralized Federated Ego Graph Learning for Recommendation
Collaborative filtering (CF) based recommender systems are typically tra...
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10/27/2022
Improved Feature Distillation via Projector Ensemble
In knowledge distillation, previous feature distillation methods mainly ...
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09/08/2022
Beyond Double Ascent via Recurrent Neural Tangent Kernel in Sequential Recommendation
Overfitting has long been considered a common issue to large neural netw...
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09/05/2022
Federated Zero-Shot Learning for Visual Recognition
Zero-shot learning is a learning regime that recognizes unseen classes b...
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07/11/2022
Discovering Domain Disentanglement for Generalized Multi-source Domain Adaptation
A typical multi-source domain adaptation (MSDA) approach aims to transfe...
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07/05/2022
GSMFlow: Generation Shifts Mitigating Flow for Generalized Zero-Shot Learning
Generalized Zero-Shot Learning (GZSL) aims to recognize images from both...
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04/12/2022
ADFF: Attention Based Deep Feature Fusion Approach for Music Emotion Recognition
Music emotion recognition (MER), a sub-task of music information retriev...
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03/29/2022
Self-Supervised Learning for Recommender Systems: A Survey
Neural architecture-based recommender systems have achieved tremendous s...
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02/13/2022
Source-Free Progressive Graph Learning for Open-Set Domain Adaptation
Open-set domain adaptation (OSDA) has gained considerable attention in m...
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01/08/2022
DeHIN: A Decentralized Framework for Embedding Large-scale Heterogeneous Information Networks
Modeling heterogeneity by extraction and exploitation of high-order info...
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12/13/2021
N-Cloth: Predicting 3D Cloth Deformation with Mesh-Based Networks
We present a novel mesh-based learning approach (N-Cloth) for plausible ...
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10/21/2021
PipAttack: Poisoning Federated Recommender Systems forManipulating Item Promotion
Due to the growing privacy concerns, decentralization emerges rapidly in...
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10/13/2021
Domain Adaptive Semantic Segmentation without Source Data
Domain adaptive semantic segmentation is recognized as a promising techn...
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10/12/2021
Contrastive Learning for Representation Degeneration Problem in Sequential Recommendation
Recent advancements of sequential deep learning models such as Transform...
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09/01/2021
Memory Augmented Multi-Instance Contrastive Predictive Coding for Sequential Recommendation
The sequential recommendation aims to recommend items, such as products,...
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08/26/2021
Learning to Diversify for Single Domain Generalization
Domain generalization (DG) aims to generalize a model trained on multipl...
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07/07/2021
Mitigating Generation Shifts for Generalized Zero-Shot Learning
Generalized Zero-Shot Learning (GZSL) is the task of leveraging semantic...
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07/06/2021
CausalRec: Causal Inference for Visual Debiasing in Visually-Aware Recommendation
Visually-aware recommendation on E-commerce platforms aims to leverage v...
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07/02/2021
Exploiting Cross-Session Information for Session-based Recommendation with Graph Neural Networks
Different from the traditional recommender system, the session-based rec...
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07/02/2021
Exploiting Positional Information for Session-based Recommendation
For present e-commerce platforms, session-based recommender systems are ...
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06/04/2021
Learning Elastic Embeddings for Customizing On-Device Recommenders
In today's context, deploying data-driven services like recommendation o...
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05/11/2021
Learning to Ask Appropriate Questions in Conversational Recommendation
Conversational recommender systems (CRSs) have revolutionized the conven...
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04/05/2021
Quaternion Factorization Machines: A Lightweight Solution to Intricate Feature Interaction Modelling
As a well-established approach, factorization machine (FM) is capable of...
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04/04/2021
Uniting Heterogeneity, Inductiveness, and Efficiency for Graph Representation Learning
With the ubiquitous graph-structured data in various applications, model...
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02/23/2021
Enhanced Modality Transition for Image Captioning
Image captioning model is a cross-modality knowledge discovery task, whi...
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01/29/2021
Graph Embedding for Recommendation against Attribute Inference Attacks
In recent years, recommender systems play a pivotal role in helping user...
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01/20/2021
Semantic Disentangling Generalized Zero-Shot Learning
Generalized Zero-Shot Learning (GZSL) aims to recognize images from both...
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01/09/2021
Entropy-Based Uncertainty Calibration for Generalized Zero-Shot Learning
Compared to conventional zero-shot learning (ZSL) where recognising unse...
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11/25/2020
Interpretable Signed Link Prediction with Signed Infomax Hyperbolic Graph
Signed link prediction in social networks aims to reveal the underlying ...
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07/31/2020
Adversarial Bipartite Graph Learning for Video Domain Adaptation
Domain adaptation techniques, which focus on adapting models between dis...
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07/27/2020
Rethinking Generative Zero-Shot Learning: An Ensemble Learning Perspective for Recognising Visual Patches
Zero-shot learning (ZSL) is commonly used to address the very pervasive ...
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06/22/2020
Progressive Graph Learning for Open-Set Domain Adaptation
Domain shift is a fundamental problem in visual recognition which typica...
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06/15/2020
ORD: Object Relationship Discovery for Visual Dialogue Generation
With the rapid advancement of image captioning and visual question answe...
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05/20/2020
GCN-Based User Representation Learning for Unifying Robust Recommendation and Fraudster Detection
In recent years, recommender system has become an indispensable function...
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05/19/2020
Try This Instead: Personalized and Interpretable Substitute Recommendation
As a fundamental yet significant process in personalized recommendation,...
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04/16/2020
Suicidal Ideation and Mental Disorder Detection with Attentive Relation Networks
Mental health is a critical issue in the modern society, mental disorder...
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04/05/2020
Enhance Social Recommendation with Adversarial Graph Convolutional Networks
Recent reports from industry show that social recommender systems consis...
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11/12/2019
Learning from the Past: Continual Meta-Learning via Bayesian Graph Modeling
Meta-learning for few-shot learning allows a machine to leverage previou...
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11/05/2019
Deep Collaborative Discrete Hashing with Semantic-Invariant Structure
Existing deep hashing approaches fail to fully explore semantic correlat...
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10/23/2019
Suicidal Ideation Detection: A Review of Machine Learning Methods and Applications
Suicide is a critical issue in the modern society. Early detection and p...
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09/21/2019