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09/04/2023
In-processing User Constrained Dominant Sets for User-Oriented Fairness in Recommender Systems
Recommender systems are typically biased toward a small group of users, ...
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08/18/2023
Defending Label Inference Attacks in Split Learning under Regression Setting
As a privacy-preserving method for implementing Vertical Federated Learn...
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08/17/2023
Joint Local Relational Augmentation and Global Nash Equilibrium for Federated Learning with Non-IID Data
Federated learning (FL) is a distributed machine learning paradigm that ...
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08/15/2023
Decentralized Graph Neural Network for Privacy-Preserving Recommendation
Building a graph neural network (GNN)-based recommender system without v...
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08/15/2023
Freshness or Accuracy, Why Not Both? Addressing Delayed Feedback via Dynamic Graph Neural Networks
The delayed feedback problem is one of the most pressing challenges in p...
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07/18/2023
Federated Large Language Model: A Position Paper
Large scale language models (LLM) have received significant attention an...
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07/07/2023
Federated Unlearning via Active Forgetting
The increasing concerns regarding the privacy of machine learning models...
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06/26/2023
Federated Learning on Non-iid Data via Local and Global Distillation
Most existing federated learning algorithms are based on the vanilla Fed...
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05/11/2023
PPGenCDR: A Stable and Robust Framework for Privacy-Preserving Cross-Domain Recommendation
Privacy-preserving cross-domain recommendation (PPCDR) refers to preserv...
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04/20/2023
Selective and Collaborative Influence Function for Efficient Recommendation Unlearning
Recent regulations on the Right to be Forgotten have greatly influenced ...
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10/24/2022
Heterogeneous Information Crossing on Graphs for Session-based Recommender Systems
Recommender systems are fundamental information filtering techniques to ...
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10/18/2022
Making Split Learning Resilient to Label Leakage by Potential Energy Loss
As a practical privacy-preserving learning method, split learning has dr...
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09/21/2022
DDGHM: Dual Dynamic Graph with Hybrid Metric Training for Cross-Domain Sequential Recommendation
Sequential Recommendation (SR) characterizes evolving patterns of user b...
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05/24/2022
HCFRec: Hash Collaborative Filtering via Normalized Flow with Structural Consensus for Efficient Recommendation
The ever-increasing data scale of user-item interactions makes it challe...
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05/20/2022
A Survey of Trustworthy Graph Learning: Reliability, Explainability, and Privacy Protection
Deep graph learning has achieved remarkable progresses in both business ...
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05/13/2022
Exploiting Variational Domain-Invariant User Embedding for Partially Overlapped Cross Domain Recommendation
Cross-Domain Recommendation (CDR) has been popularly studied to utilize ...
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04/19/2022
Partial Relaxed Optimal Transport for Denoised Recommendation
The interaction data used by recommender systems (RSs) inevitably includ...
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03/22/2022
Making Recommender Systems Forget: Learning and Unlearning for Erasable Recommendation
Privacy laws and regulations enforce data-driven systems, e.g., recommen...
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02/10/2022
Collaborative Filtering with Attribution Alignment for Review-based Non-overlapped Cross Domain Recommendation
Cross-Domain Recommendation (CDR) has been popularly studied to utilize ...
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02/10/2022
Differential Private Knowledge Transfer for Privacy-Preserving Cross-Domain Recommendation
Cross Domain Recommendation (CDR) has been popularly studied to alleviat...
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09/15/2021
Beyond Glass-Box Features: Uncertainty Quantification Enhanced Quality Estimation for Neural Machine Translation
Quality Estimation (QE) plays an essential role in applications of Machi...
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08/17/2021
Towards Secure and Practical Machine Learning via Secret Sharing and Random Permutation
With the increasing demands for privacy protection, privacy-preserving m...
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03/27/2021
Multi-Facet Recommender Networks with Spherical Optimization
Implicit feedback is widely explored by modern recommender systems. Sinc...
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12/17/2020
Towards Scalable and Privacy-Preserving Deep Neural Network via Algorithmic-Cryptographic Co-design
Deep Neural Networks (DNNs) have achieved remarkable progress in various...
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05/25/2020
Privacy-Preserving Graph Neural Network for Node Classification
Recently, Graph Neural Network (GNN) has achieved remarkable progresses ...
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03/05/2020
Semi-supervised Learning Meets Factorization: Learning to Recommend with Chain Graph Model
Recently latent factor model (LFM) has been drawing much attention in re...
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03/05/2020
Practical Privacy Preserving POI Recommendation
Point-of-Interest (POI) recommendation has been extensively studied and ...
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11/13/2019
Adaptive Portfolio by Solving Multi-armed Bandit via Thompson Sampling
As the cornerstone of modern portfolio theory, Markowitz's mean-variance...
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11/13/2019
Context-aware Dynamic Assets Selection for Online Portfolio Selection based on Contextual Bandit
Online portfolio selection is a sequential decision-making problem in fi...
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08/26/2018
FinBrain: When Finance Meets AI 2.0
Artificial intelligence (AI) is the core technology of technological rev...
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04/28/2018
User-Sensitive Recommendation Ensemble with Clustered Multi-Task Learning
This paper considers recommendation algorithm ensembles in a user-sensit...
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12/25/2017
Collaborative Autoencoder for Recommender Systems
In recent years, deep neural networks have yielded state-of-the-art perf...
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12/25/2017
Deep Collaborative Autoencoder for Recommender Systems: A Unified Framework for Explicit and Implicit Feedback
In recent years, deep neural networks have yielded state-of-the-art perf...
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11/30/2017