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The paper introduces PRA, a parameterized framework that uses inequality‑aversion parameters to softly enforce diversity constraints in resource allocation, allowing flexible trade…

Publications (107)

From Randomized Response to Randomized Index: Answering Subset Counting Queries with Local Differential Privacy

Differentially Private Multivariate Time Series Forecasting of Aggregated Human Mobility With Deep Learning: Input or Gradient Perturbation?

Low-Rank Mechanism: Optimizing Batch Queries under Differential Privacy

The Metaverse Data Deluge: What Can We Do About It?

The Hardness and Approximation Algorithms for L-Diversity

Parameterized Fair Resource Allocation under Diversity Constraints

Proof of Quality: A Costless Paradigm for Trustless Generative AI Model Inference on Blockchains

Millionaire: A Hint-guided Approach for Crowdsourcing

DP-S4S: Accurate and Scalable Select-Join-Aggregate Query Processing with User-Level Differential Privacy

Transparent Anonymization: Thwarting Adversaries Who Know the Algorithm

Visual Graph Scaffolds for Structural Reasoning in Large Language Models

Efficient Approximation Algorithms for Adaptive Influence Maximization

Effective and Scalable Clustering on Massive Attributed Graphs

Random Sampling Plus Fake Data: Multidimensional Frequency Estimates With Local Differential Privacy

Keyword-aware Optimal Route Search

ThriftLLM: On Cost-Effective Selection of Large Language Models for Classification Queries

Predicting Cascading Failures with a Hyperparametric Diffusion Model

PrivLava: Synthesizing Relational Data with Foreign Keys under Differential Privacy

MGNNI: Multiscale Graph Neural Networks with Implicit Layers

EIGNN: Efficient Infinite-Depth Graph Neural Networks

Capacity Constrained Influence Maximization in Social Networks

Accurate Table Question Answering with Accessible LLMs

LSCALE: Latent Space Clustering-Based Active Learning for Node Classification

Cost-Effective Seed Selection in Online Social Networks

Benchmarking Text-to-SQL under Role-Based Access Control

Optimizing Batch Linear Queries under Exact and Approximate Differential Privacy

Single-Pass Contrastive Learning Can Work for Both Homophilic and Heterophilic Graph

Efficient and Effective Algorithms for A Family of Influence Maximization Problems with A Matroid Constraint

Functional Mechanism: Regression Analysis under Differential Privacy

Optimal Streaming Algorithms for Multi-Armed Bandits

Low Rank Mechanism for Optimizing Batch Queries under Differential Privacy

Shortest Path and Distance Queries on Road Networks: Towards Bridging Theory and Practice

Efficient Estimation of Heat Kernel PageRank for Local Clustering

NeurDB: An AI-powered Autonomous Data System

Realtime Index-Free Single Source SimRank Processing on Web-Scale Graphs

PrivTree: A Differentially Private Algorithm for Hierarchical Decompositions

SCOPE: Cost-Efficient Model Selection for Compound AI Systems under Quality Constraints

Near-Optimality for Single-Source Personalized PageRank

KET-RAG: A Cost-Efficient Multi-Granular Indexing Framework for Graph-RAG

Homogeneous Network Embedding for Massive Graphs via Reweighted Personalized PageRank

Collecting and Analyzing Data from Smart Device Users with Local Differential Privacy

You Are What You Bought: Generating Customer Personas for E-commerce Applications

Secure and Verifiable Data Collaboration with Low-Cost Zero-Knowledge Proofs

Improving the utility of locally differentially private protocols for longitudinal and multidimensional frequency estimates

MOTS: Minimax Optimal Thompson Sampling

Passive Inference Attacks on Split Learning via Adversarial Regularization

Efficient Algorithms for Approximate Single-Source Personalized PageRank Queries

Weight-Informed Self-Explaining Clustering for Mixed-Type Tabular Data

GegenNet: Spectral Convolutional Neural Networks for Link Sign Prediction in Signed Bipartite Graphs

Efficient Single-Source Shortest Path and Distance Queries on Large Graphs

GraphMP: I/O-Efficient Big Graph Analytics on a Single Commodity Machine

DPIS: An Enhanced Mechanism for Differentially Private SGD with Importance Sampling

Efficient Approximation Algorithms for Adaptive Target Profit Maximization

Effective Edge-wise Representation Learning in Edge-Attributed Bipartite Graphs

GCON: Differentially Private Graph Convolutional Network via Objective Perturbation

Hyperparametric Robust and Dynamic Influence Maximization

Refutations on "Debunking the Myths of Influence Maximization: An In-Depth Benchmarking Study"

A Fusion-Denoising Attack on InstaHide with Data Augmentation

NeurStore: Efficient In-database Deep Learning Model Management System

Privacy Preserving Vertical Federated Learning for Tree-based Models

Skellam Mixture Mechanism: a Novel Approach to Federated Learning with Differential Privacy

Efficient Approximation Algorithms for Spanning Centrality

Influence Maximization: Near-Optimal Time Complexity Meets Practical Efficiency

The Disruptions of 5G on Data-driven Technologies and Applications

Effective and Efficient PageRank-based Positioning for Graph Visualization

Double Explore-then-Commit: Asymptotic Optimality and Beyond

Fast Approximate CoSimRanks via Random Projections

PrivPetal: Relational Data Synthesis via Permutation Relations

Dangling-Aware Entity Alignment with Mixed High-Order Proximities

PRSim: Sublinear Time SimRank Computation on Large Power-Law Graphs

Differentially Private Contrastive Learning via Bounding Group-level Contribution

Node-wise Diffusion for Scalable Graph Learning

SLING: A Near-Optimal Index Structure for SimRank

PANE: scalable and effective attributed network embedding

AutoContext: Instance-Level Context Learning for LLM Agents

Shortest Path and Distance Queries on Road Networks: An Experimental Evaluation

Optimal Batched Best Arm Identification

Blink: Link Local Differential Privacy in Graph Neural Networks via Bayesian Estimation

Exploiting Explanations for Model Inversion Attacks