29 citations · 220 across the 30 of their papers we have counts for
30 papers
Feature Inference Attack on Shapley Values
Xinjian Luo, Yangfan Jiang, Xiaokui Xiao
As a solution concept in cooperative game theory, Shapley value is highly recognized in model interpretability studies and widely adopted by the leading Machine Learning as a Servi…
Comparisons among the Performances of Randomized-framed Benchmarking Protocols under T1, T2 and Coherent Error Models
Xudan Chai, Yanwu Gu, Weifeng Zhuang +3
While fundamental scientific researchers are eagerly anticipating the breakthroughs of quantum computing both in theory and technology, the current quantum computer, i.e. noisy int…
Controllable Weyl nodes and Fermi arcs in a light-irradiated carbon allotrope
Ruoning Ji, Xianyong Ding, Fangyang Zhan +4
The precise control of Weyl physics in realistic materials oers a promising avenue to construct accessible topological quantum systems, and thus draw widespread attention in conden…
Physics-Constrained Hardware-Efficient Ansatz on Quantum Computers that is Universal, Systematically Improvable, and Size-consistent
Xiaoxiao Xiao, Hewang Zhao, Jiajun Ren +2
Variational wavefunction ansätze are at the heart of solving quantum many-body problems in physics and chemistry. Previous designs of hardware-efficient ansatz (HEA) on quantum com…
Node-wise Diffusion for Scalable Graph Learning
Keke Huang, Jing Tang, Juncheng Liu +2
Graph Neural Networks (GNNs) have shown superior performance for semi-supervised learning of numerous web applications, such as classification on web services and pages, analysis o…
Skellam Mixture Mechanism: a Novel Approach to Federated Learning with Differential Privacy
Ergute Bao, Yizheng Zhu, Xiaokui Xiao +4
Deep neural networks have strong capabilities of memorizing the underlying training data, which can be a serious privacy concern. An effective solution to this problem is to train…
Single-Pass Contrastive Learning Can Work for Both Homophilic and Heterophilic Graph
Haonan Wang, Jieyu Zhang, Qi Zhu +3
Existing graph contrastive learning (GCL) techniques typically require two forward passes for a single instance to construct the contrastive loss, which is effective for capturing…
MGNNI: Multiscale Graph Neural Networks with Implicit Layers
Juncheng Liu, Bryan Hooi, Kenji Kawaguchi +1
Recently, implicit graph neural networks (GNNs) have been proposed to capture long-range dependencies in underlying graphs. In this paper, we introduce and justify two weaknesses o…
DPIS: An Enhanced Mechanism for Differentially Private SGD with Importance Sampling
Jianxin Wei, Ergute Bao, Xiaokui Xiao +1
Nowadays, differential privacy (DP) has become a well-accepted standard for privacy protection, and deep neural networks (DNN) have been immensely successful in machine learning. T…
An Embedding-Based Grocery Search Model at Instacart
Yuqing Xie, Taesik Na, Xiao Xiao +7
The key to e-commerce search is how to best utilize the large yet noisy log data. In this paper, we present our embedding-based model for grocery search at Instacart. The system le…
Measuring Friendship Closeness: A Perspective of Social Identity Theory
Shiqi Zhang, Jiachen Sun, Wenqing Lin +2
Measuring the closeness of friendships is an important problem that finds numerous applications in practice. For example, online gaming platforms often host friendship-enhancing ev…
GlassDB: An Efficient Verifiable Ledger Database System Through Transparency
Cong Yue, Tien Tuan Anh Dinh, Zhongle Xie +4
Verifiable ledger databases protect data history against malicious tampering. Existing systems, such as blockchains and certificate transparency, are based on transparency logs --…
Finite-Time Regret of Thompson Sampling Algorithms for Exponential Family Multi-Armed Bandits
Tianyuan Jin, Pan Xu, Xiaokui Xiao +1
We study the regret of Thompson sampling (TS) algorithms for exponential family bandits, where the reward distribution is from a one-dimensional exponential family, which covers ma…
Differentially Private Multivariate Time Series Forecasting of Aggregated Human Mobility With Deep Learning: Input or Gradient Perturbation?
Héber H. Arcolezi, Jean-François Couchot, Denis Renaud +2
This paper investigates the problem of forecasting multivariate aggregated human mobility while preserving the privacy of the individuals concerned. Differential privacy, a state-o…
The Metaverse Data Deluge: What Can We Do About It?
Beng Chin Ooi, Gang Chen, Mike Zheng Shou +5
In the Metaverse, the physical space and the virtual space co-exist, and interact simultaneously. While the physical space is virtually enhanced with information, the virtual space…
Fast Quantum Calibration using Bayesian Optimization with State Parameter Estimator for Non-Markovian Environment
Peng Qian, Shahid Qamar, Xiao Xiao +5
As quantum systems expand in size and complexity, manual qubit characterization and gate optimization will be a non-scalable and time-consuming venture. Physical qubits have to be…
Dangling-Aware Entity Alignment with Mixed High-Order Proximities
Juncheng Liu, Zequn Sun, Bryan Hooi +5
We study dangling-aware entity alignment in knowledge graphs (KGs), which is an underexplored but important problem. As different KGs are naturally constructed by different sets of…
EIGNN: Efficient Infinite-Depth Graph Neural Networks
Juncheng Liu, Kenji Kawaguchi, Bryan Hooi +2
Graph neural networks (GNNs) are widely used for modelling graph-structured data in numerous applications. However, with their inherently finite aggregation layers, existing GNN mo…
Efficient Classical Computation of Quantum Mean Values for Shallow QAOA Circuits
Wei-Feng Zhuang, Ya-Nan Pu, Hong-Ze Xu +9
The Quantum Approximate Optimization Algorithm (QAOA), which is a variational quantum algorithm, aims to give sub-optimal solutions of combinatorial optimization problems. It is wi…
Improving the utility of locally differentially private protocols for longitudinal and multidimensional frequency estimates
Héber H. Arcolezi, Jean-François Couchot, Bechara Al Bouna +1
This paper investigates the problem of collecting multidimensional data throughout time (i.e., longitudinal studies) for the fundamental task of frequency estimation under Local Di…
Efficient Path-Sensitive Data-Dependence Analysis
Peisen Yao, Jinguo Zhou, Xiao Xiao +3
This paper presents a scalable path- and context-sensitive data-dependence analysis. The key is to address the aliasing-path-explosion problem via a sparse, demand-driven, and fuse…
Computational modelling and data-driven homogenisation of knitted membranes
Sumudu Herath, Xiao Xiao, Fehmi Cirak
Knitting is an effective technique for producing complex three-dimensional surfaces owing to the inherent flexibility of interlooped yarns and recent advances in manufacturing prov…
Unknown-box Approximation to Improve Optical Character Recognition Performance
Ayantha Randika, Nilanjan Ray, Xiao Xiao +1
Optical character recognition (OCR) is a widely used pattern recognition application in numerous domains. There are several feature-rich, general-purpose OCR solutions available fo…
A Fusion-Denoising Attack on InstaHide with Data Augmentation
Xinjian Luo, Xiaokui Xiao, Yuncheng Wu +2
InstaHide is a state-of-the-art mechanism for protecting private training images, by mixing multiple private images and modifying them such that their visual features are indisting…