collaborators

5 papers

cs.CR2026

DP4SQL: Differentially Private SQL with Flexible Privacy Policies

Andrew Cascio, KinChin Tong, Daniel Kifer +2

The plausible deniability model of differential privacy for single-table datasets is well-understood. However, applying differential privacy to relational databases is much trickie…

cs.DB2026

ResidualPlanner+: a scalable matrix mechanism for marginals and beyond

Guanlin He, Yingtai Xiao, Levent Toksoz +3

Noisy marginals are a common form of confidentiality protecting data release and are useful for many downstream tasks such as contingency table analysis, construction of Bayesian n…

cs.LG2026

The Trap of Trajectory: Towards Understanding and Mitigating Spurious Correlations in Agentic Memory

Luoxi Tang, Rupali Rajendra Vaje, Yuqiao Meng +5

Agentic memory enables LLMs to persist information beyond a single context window and reuse it in later decisions, but it also introduces a new vulnerability: spurious correlations…

cs.DB2026

Accurate and Scalable Matrix Mechanisms via Divide and Conquer

Guanlin He, Yingtai Xiao, Jiamu Bai +4

Matrix mechanisms are often used to provide unbiased differentially private query answers when publishing statistics or creating synthetic data. Recent work has developed matrix me…

cs.LG2026

Scalable Learning of Multivariate Distributions via Coresets

Zeyu Ding, Katja Ickstadt, Nadja Klein +2

Efficient and scalable non-parametric or semi-parametric regression analysis and density estimation are of crucial importance to the fields of statistics and machine learning. Howe…