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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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07/26/2023
HyperFed: Hyperbolic Prototypes Exploration with Consistent Aggregation for Non-IID Data in Federated Learning
Federated learning (FL) collaboratively models user data in a decentrali...
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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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05/29/2023
Reducing Communication for Split Learning by Randomized Top-k Sparsification
Split learning is a simple solution for Vertical Federated Learning (VFL...
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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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02/13/2023
DCMT: A Direct Entire-Space Causal Multi-Task Framework for Post-Click Conversion Estimation
In recommendation scenarios, there are two long-standing challenges, i.e...
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02/06/2023
INCREASE: Inductive Graph Representation Learning for Spatio-Temporal Kriging
Spatio-temporal kriging is an important problem in web and social applic...
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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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09/04/2022
Cross-Network Social User Embedding with Hybrid Differential Privacy Guarantees
Integrating multiple online social networks (OSNs) has important implica...
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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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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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02/15/2022
Exploiting Data Sparsity in Secure Cross-Platform Social Recommendation
Social recommendation has shown promising improvements over traditional ...
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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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12/28/2021
Adaptive Client Sampling in Federated Learning via Online Learning with Bandit Feedback
In federated learning (FL) problems, client sampling plays a key role in...
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12/14/2021
Generalization Bounds for Stochastic Gradient Langevin Dynamics: A Unified View via Information Leakage Analysis
Recently, generalization bounds of the non-convex empirical risk minimiz...
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08/18/2021
A Unified Framework for Cross-Domain and Cross-System Recommendations
Cross-Domain Recommendation (CDR) and Cross-System Recommendation (CSR) ...
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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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03/02/2021
Cross-Domain Recommendation: Challenges, Progress, and Prospects
To address the long-standing data sparsity problem in recommender system...
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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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11/23/2020
Improving Federated Relational Data Modeling via Basis Alignment and Weight Penalty
Federated learning (FL) has attracted increasing attention in recent yea...
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11/20/2020
Survey and Open Problems in Privacy Preserving Knowledge Graph: Merging, Query, Representation, Completion and Applications
Knowledge Graph (KG) has attracted more and more companies' attention fo...
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11/06/2020
ASFGNN: Automated Separated-Federated Graph Neural Network
Graph Neural Networks (GNNs) have achieved remarkable performance by tak...
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09/14/2020
A Deep Framework for Cross-Domain and Cross-System Recommendations
Cross-Domain Recommendation (CDR) and Cross-System Recommendations (CSR)...
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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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03/12/2020
Privacy Preserving Point-of-interest Recommendation Using Decentralized Matrix Factorization
Points of interest (POI) recommendation has been drawn much attention re...
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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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02/27/2020
Heterogeneous Graph Neural Networks for Malicious Account Detection
We present, GEM, the first heterogeneous graph neural network approach f...
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02/27/2020
Adapted tree boosting for Transfer Learning
Secure online transaction is an essential task for e-commerce platforms....
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02/27/2020
How Much Can A Retailer Sell? Sales Forecasting on Tmall
Time-series forecasting is an important task in both academic and indust...
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02/06/2020
Privacy Preserving PCA for Multiparty Modeling
In this paper, we present a general multiparty model-ing paradigm with P...
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02/06/2020
Secure Social Recommendation based on Secret Sharing
Nowadays, privacy preserving machine learning has been drawing much atte...
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12/26/2019
A Time Attention based Fraud Transaction Detection Framework
With online payment platforms being ubiquitous and important, fraud tran...
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10/12/2019
Quantification of the Leakage in Federated Learning
With the growing emphasis on users' privacy, federated learning has beco...
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10/05/2019
Characterizing Membership Privacy in Stochastic Gradient Langevin Dynamics
Bayesian deep learning is recently regarded as an intrinsic way to chara...
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08/21/2019
Generalization in Generative Adversarial Networks: A Novel Perspective from Privacy Protection
In this paper, we aim to understand the generalization properties of gen...
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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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05/11/2018
