Travis Dick
18 papers · 2013–2025 · 7 venues · across top CS/AI venues
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Achievements
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🐣 Hot Topic Early Bird 🌍 Conference Polyglot · Silver 🏃 Academic Marathon · Half 🌉 Interdisciplinary Bridge · Silver 🗺️ Taxonomy Completionist (29)
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Century Club · Bronze
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Renaissance Researcher
(7)
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Research topics
Machine Learning
(17)
Optimization & Theory
(10)
Core Methods
(9)
Application Areas
(7)
Mathematics & Optimization
(6)
Learning Types
(5)
Optimization
(5)
Artificial Intelligence
(2)
Security & Privacy
(2)
Core AI
(2)
Differential Privacy
(2)
Computer Science
(1)
Computer Vision
(1)
Data Science & Analytics
(1)
Reinforcement Learning
(1)
Keywords
differential privacy
(6)
algorithm selection
(3)
regret bound
(2)
empirical risk minimization
(2)
k-means clustering
(2)
statistical estimation
(2)
online learning
(2)
algorithmic fairness
(1)
adversarial robustness
(1)
learning theory
(1)
feature selection
(1)
weakly supervised learning
(1)
sample complexity
(1)
distributed learning
(1)
online clustering
(1)
metric learning
(1)
markov decision process
(1)
theoretical analysis
(1)
branch and bound
(1)
mean estimation
(1)
Papers
Nearly Optimal Sample Complexity for Learning with Label Proportions
ICML 2025
Auditing Privacy Mechanisms via Label Inference Attacks
NeurIPS 2024
Better Private Linear Regression Through Better Private Feature Selection
NeurIPS 2023
Easy Learning from Label Proportions
NeurIPS 2023
Learning-augmented private algorithms for multiple quantile release
ICML 2023
Subset-Based Instance Optimality in Private Estimation
ICML 2023
Learning piecewise Lipschitz functions in changing environments
AISTATS 2020
Learning to Link
ICLR 2020
Random Smoothing Might be Unable to Certify ℓ_∞ Robustness for High-Dimensional Images
JMLR 2020
Semi-bandit Optimization in the Dispersed Setting
UAI 2020
Differentially Private Covariance Estimation
NeurIPS 2019
Envy-Free Classification
NeurIPS 2019
Data-Driven Clustering via Parameterized Lloyd's Families
NeurIPS 2018
Learning to Branch
ICML 2018
Data Driven Resource Allocation for Distributed Learning
AISTATS 2017
Differentially Private Clustering in High-Dimensional Euclidean Spaces
ICML 2017
Online Learning in Markov Decision Processes with Changing Cost Sequences
ICML 2014
Realtime Registration-Based Tracking via Approximate Nearest Neighbour Search
RSS 2013