← Authors

Travis Dick

18 papers · 2013–2025 · 7 conferences · across top CS/AI conferences

Achievements

πŸŒ‰ Interdisciplinary Bridge 🧭 Keyword Pioneer 🐣 Hot Topic Early Bird 🐝 Cross-Pollinator (8) 🌈 Renaissance Researcher (8) πŸ—ΊοΈ Taxonomy Completionist (31) 🌍 Conference Polyglot (7) πŸƒ Academic Marathon (12) πŸ’Ž Century Club (18) πŸ“ˆ Trend Setter πŸ—ƒοΈ Keyword Collector (85)

Conferences

ICML (6) NIPS (6) AISTATS (2) ICLR (1) JMLR (1) RSS (1) UAI (1)

Top co-authors

Maria-Florina Balcan (5) Claudio Gentile (3) Kareem Amin (2) Hongyang Zhang (2) Maria-Florina F Balcan (2) RΓ³bert IstvΓ‘n Busa-Fekete (2) Andres Munoz Medina (2) Sergei Vassilvitskii (2) Alex Kulesza (2) Colin White (2)

Research topics

Differential Privacy (2) Privacy (1) Statistics (1)

Keywords

differential privacy (6) algorithm selection (2) regret bound (2) online learning (2) k-means clustering (2) statistical estimation (2) game theory (1) distributed learning (1) learning theory (1) weakly supervised learning (1) feature selection (1) mean estimation (1) theoretical analysis (1) empirical risk minimization (1) algorithmic fairness (1) online optimization (1) covariance matrix (1) branch and bound (1) markov decision process (1) online clustering (1)

Papers

Nearly Optimal Sample Complexity for Learning with Label Proportions ICML 2025
Auditing Privacy Mechanisms via Label Inference Attacks NIPS 2024
Subset-Based Instance Optimality in Private Estimation ICML 2023
Learning-augmented private algorithms for multiple quantile release ICML 2023
Easy Learning from Label Proportions NIPS 2023
Better Private Linear Regression Through Better Private Feature Selection NIPS 2023
Semi-bandit Optimization in the Dispersed Setting UAI 2020
Learning piecewise Lipschitz functions in changing environments AISTATS 2020
Learning to Link ICLR 2020
Random Smoothing Might be Unable to Certify $\ell_\infty$ Robustness for High-Dimensional Images JMLR 2020
Envy-Free Classification NIPS 2019
Differentially Private Covariance Estimation NIPS 2019
Data-Driven Clustering via Parameterized Lloyd's Families NIPS 2018
Learning to Branch ICML 2018
Differentially Private Clustering in High-Dimensional Euclidean Spaces ICML 2017
Data Driven Resource Allocation for Distributed Learning AISTATS 2017
Online Learning in Markov Decision Processes with Changing Cost Sequences ICML 2014
Realtime Registration-Based Tracking via Approximate Nearest Neighbour Search RSS 2013