Random orthogonal matrix masking methodology for microdata release. - Daniel Ting; Stephen E. Fienberg; Mario Trottini (Int. J. Inf. Comput. Secur., 2008)

An Analysis of the Convergence of Graph Laplacians. - Daniel Ting; Ling Huang 001; Michael I. Jordan (ICML, 2010)

Online Semi-Supervised Learning on Quantized Graphs. - Michal Valko; Branislav Kveton; Ling Huang; Daniel Ting (UAI, 2010)

Neighbor-Dependent Ramachandran Probability Distributions of Amino Acids Developed from a Hierarchical Dirichlet Process Model. - Daniel Ting; Guoli Wang 005; Maxim V. Shapovalov; Rajib Mitra; Michael I. Jordan; Roland L. Dunbrack Jr. (PLoS Comput. Biol., 2010)

Mixture models of endhost network traffic. - John Mark Agosta; Jaideep Chandrashekar; Mark Crovella; Nina Taft; Daniel Ting (INFOCOM, 2013)

Streamed approximate counting of distinct elements: beating optimal batch methods. - Daniel Ting (KDD, 2014)

Towards Optimal Cardinality Estimation of Unions and Intersections with Sketches. - Daniel Ting (KDD, 2016)

Adaptive Threshold Sampling and Estimation. - Daniel Ting (CoRR, 2017)

Optimal Sub-sampling with Influence Functions. - Daniel Ting; Eric Brochu (CoRR, 2017)

Count-Min: Optimal Estimation and Tight Error Bounds using Empirical Error Distributions. - Daniel Ting (KDD, 2018)

Optimal Subsampling with Influence Functions. - Daniel Ting; Eric Brochu (NeurIPS, 2018)

Data Sketches for Disaggregated Subset Sum and Frequent Item Estimation. - Daniel Ting (SIGMOD Conference, 2018)

Approximate Distinct Counts for Billions of Datasets. - Daniel Ting (SIGMOD Conference, 2019)

Learning to optimize federated queries. - Liqi Xu; Richard L. Cole; Daniel Ting (aiDM@SIGMOD, 2019)

Data Sketching for Real Time Analytics: Theory and Practice. - Daniel Ting; Jonathan Malkin; Lee Rhodes (KDD, 2020)

Manifold Learning via Manifold Deflation. - Daniel Ting; Michael I. Jordan (CoRR, 2020)

HyperLogLog (HLL) Security: Inflating Cardinality Estimates. - Pedro Reviriego; Pablo Adell; Daniel Ting (CoRR, 2020)

Fast Updates for Line-Rate HyperLogLog-Based Cardinality Estimation. - Pedro Reviriego; Valerio Bruschi; Salvatore Pontarelli; Daniel Ting; Giuseppe Bianchi 001 (IEEE Commun. Lett., 2020)

Security of HyperLogLog (HLL) Cardinality Estimation: Vulnerabilities and Protection. - Pedro Reviriego; Daniel Ting (IEEE Commun. Lett., 2020)

Conditional Cuckoo Filters. - Daniel Ting; Rick Cole (SIGMOD Conference, 2021)

Simple, Optimal Algorithms for Random Sampling Without Replacement. - Daniel Ting (CoRR, 2021)

More Accurate Streaming Cardinality Estimation With Vectorized Counters. - Valerio Bruschi; Pedro Reviriego; Salvatore Pontarelli; Daniel Ting; Giuseppe Bianchi 001 (IEEE Netw. Lett., 2021)

Order-Invariant Cardinality Estimators Are Differentially Private. - Charlie Dickens; Justin Thaler; Daniel Ting (NeurIPS, 2022)

Statistical Schema Learning with Occam's Razor. - Justin Talbot; Daniel Ting (SIGMOD Conference, 2022)

Adaptive Threshold Sampling. - Daniel Ting (SIGMOD Conference, 2022)

(Nearly) All Cardinality Estimators Are Differentially Private. - Charlie Dickens; Justin Thaler; Daniel Ting (CoRR, 2022)

Breaking Cuckoo Hash: Black Box Attacks. - Pedro Reviriego; Daniel Ting (IEEE Trans. Dependable Secur. Comput., 2022)

Sketch-Flip-Merge: Mergeable Sketches for Private Distinct Counting. - Jonathan Hehir; Daniel Ting; Graham Cormode (ICML, 2023)

Challenges Faced by Large Language Models in Solving Multi-Agent Flocking. - Peihan Li; Vishnu Menon; Bhavanaraj Gudiguntla; Daniel Ting; Lifeng Zhou (CoRR, 2024)

A Novel Approach to Test-Induced Defect Detection in Semiconductor Wafers, Using Graph-Based Semi-Supervised Learning (GSSL). - Pedram Tabatabaeemoshiri; Narendra Kumar 001; Anis Salwa Mohd Khairuddin; Daniel Ting; Vivek Regeev (IEEE Access, 2025)

Federated Data Shift Distance Estimation. - Graham Cormode; Daniel Ting (Proc. VLDB Endow., 2025)