research
∙
09/06/2023
Blink: Link Local Differential Privacy in Graph Neural Networks via Bayesian Estimation
Graph neural networks (GNNs) have gained an increasing amount of popular...
share
research
∙
05/25/2023
Efficient Approximation Algorithms for Spanning Centrality
Given a graph 𝒢, the spanning centrality (SC) of an edge e measures the ...
research
∙
04/10/2023
PrivLava: Synthesizing Relational Data with Foreign Keys under Differential Privacy
Answering database queries while preserving privacy is an important prob...
research
∙
12/08/2022
Skellam Mixture Mechanism: a Novel Approach to Federated Learning with Differential Privacy
Deep neural networks have strong capabilities of memorizing the underlyi...
research
∙
10/18/2022
DPIS: An Enhanced Mechanism for Differentially Private SGD with Importance Sampling
Nowadays, differential privacy (DP) has become a well-accepted standard ...
research
∙
10/15/2022
MGNNI: Multiscale Graph Neural Networks with Implicit Layers
Recently, implicit graph neural networks (GNNs) have been proposed to ca...
research
∙
07/03/2022
GlassDB: An Efficient Verifiable Ledger Database System Through Transparency
Verifiable ledger databases protect data history against malicious tampe...
research
∙
06/14/2022
Sense The Physical, Walkthrough The Virtual, Manage The Metaverse: A Data-centric Perspective
In the Metaverse, the physical space and the virtual space co-exist, and...
research
∙
06/07/2022
Finite-Time Regret of Thompson Sampling Algorithms for Exponential Family Multi-Armed Bandits
We study the regret of Thompson sampling (TS) algorithms for exponential...
research
∙
05/05/2022
Dangling-Aware Entity Alignment with Mixed High-Order Proximities
We study dangling-aware entity alignment in knowledge graphs (KGs), whic...
research
∙
05/01/2022
Differentially Private Multivariate Time Series Forecasting of Aggregated Human Mobility With Deep Learning: Input or Gradient Perturbation?
This paper investigates the problem of forecasting multivariate aggregat...
research
∙
02/22/2022
EIGNN: Efficient Infinite-Depth Graph Neural Networks
Graph neural networks (GNNs) are widely used for modelling graph-structu...
research
∙
11/08/2021
Improving the Utility of Locally Differentially Private Protocols for Longitudinal and Multidimensional Frequency Estimates
This paper investigates the problem of collecting multidimensional data ...
research
∙
09/15/2021
Random Sampling Plus Fake Data: Multidimensional Frequency Estimates With Local Differential Privacy
With local differential privacy (LDP), users can privatize their data an...
research
∙
05/17/2021
A Fusion-Denoising Attack on InstaHide with Data Augmentation
InstaHide is a state-of-the-art mechanism for protecting private trainin...
research
∙
04/26/2021
Exploiting Explanations for Model Inversion Attacks
The successful deployment of artificial intelligence (AI) in many domain...
research
∙
02/07/2021
Effective and Scalable Clustering on Massive Attributed Graphs
Given a graph G where each node is associated with a set of attributes, ...
research
∙
12/13/2020
Active Learning for Node Classification: The Additional Learning Ability from Unlabelled Nodes
Node classification on graph data is an important task on many practical...
research
∙
10/20/2020
Feature Inference Attack on Model Predictions in Vertical Federated Learning
Federated learning (FL) is an emerging paradigm for facilitating multipl...
research
∙
08/14/2020
Privacy Preserving Vertical Federated Learning for Tree-based Models
Federated learning (FL) is an emerging paradigm that enables multiple or...
research
∙
03/04/2020
Analysis of Indexing Structures for Immutable Data
In emerging applications such as blockchains and collaborative data anal...
research
∙
03/04/2020
Analysis of Indexing Structures for Immutable Data (Full Version)
In emerging applications such as blockchains and collaborative data anal...
research
∙
03/03/2020
MOTS: Minimax Optimal Thompson Sampling
Thompson sampling is one of the most widely used algorithms for many onl...
research
∙
02/21/2020
Double Explore-then-Commit: Asymptotic Optimality and Beyond
We study the two-armed bandit problem with subGaussian rewards. The expl...
research
∙
02/19/2020
Realtime Index-Free Single Source SimRank Processing on Web-Scale Graphs
Given a graph G and a node u in G, a single source SimRank query evaluat...
research
∙
09/06/2019
The Disruptions of 5G on Data-driven Technologies and Applications
With 5G on the verge of being adopted as the next mobile network, there ...
research
∙
08/28/2019
Efficient Algorithms for Approximate Single-Source Personalized PageRank Queries
Given a graph G, a source node s and a target node t, the personalized P...
research
∙
07/23/2019
Efficient Approximation Algorithms for Adaptive Seed Minimization
As a dual problem of influence maximization, the seed minimization probl...
research
∙
06/28/2019
Collecting and Analyzing Multidimensional Data with Local Differential Privacy
Local differential privacy (LDP) is a recently proposed privacy standard...
research
∙
06/17/2019
Homogeneous Network Embedding for Massive Graphs via Personalized PageRank
Given an input graph G and a node v in G, homogeneous network embedding ...
research
∙
05/07/2019
PRSim: Sublinear Time SimRank Computation on Large Power-Law Graphs
SimRank is a classic measure of the similarities of nodes in a graph. G...
research
∙
04/03/2019
Efficient Estimation of Heat Kernel PageRank for Local Clustering
Given an undirected graph G and a seed node s, the local clustering prob...
research
∙
10/09/2018
GraphMP: I/O-Efficient Big Graph Analytics on a Single Commodity Machine
Recent studies showed that single-machine graph processing systems can b...
research
∙
09/30/2018
Privacy-preserving Stochastic Gradual Learning
It is challenging for stochastic optimizations to handle large-scale sen...
research
∙
02/26/2018
Millionaire: A Hint-guided Approach for Crowdsourcing
Modern machine learning is migrating to the era of complex models, which...
research
∙
11/29/2017
Cost-Effective Seed Selection in Online Social Networks
We study the min-cost seed selection problem in online social networks, ...
research
∙
09/20/2017
ProbeSim: Scalable Single-Source and Top-k SimRank Computations on Dynamic Graphs
Single-source and top-k SimRank queries are two important types of simil...
research
∙
03/22/2016