Matthew Joseph
14 papers · 2016–2026 · 4 venues · across top CS/AI venues
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Achievements
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πΊοΈ Taxonomy Completionist (21) π Conference Polyglot Β· Bronze π£ Hot Topic Early Bird π Interdisciplinary Bridge Β· Silver π Academic Marathon Β· Half
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Keyword Champion
(3)
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Trend Setter
π₯
Unstoppable Β· Silver
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Century Club Β· Bronze
ποΈ
Keyword Collector
(56)
Venues
Top co-authors
Research topics
Machine Learning
(14)
Security & Privacy
(10)
Differential Privacy
(10)
Application Areas
(9)
Optimization & Theory
(7)
Mathematics & Optimization
(4)
Learning Types
(4)
Artificial Intelligence
(3)
Core AI
(3)
Core Methods
(3)
Optimization
(3)
Mathematics
(2)
Reinforcement Learning
(1)
Methods
(1)
Privacy
(1)
Keywords
differential privacy
(10)
exponential mechanism
(3)
fairness constraint
(2)
local differential privacy
(2)
k-norm mechanism
(2)
local privacy
(2)
privacy guarantee
(2)
linear regression
(2)
statistical estimation
(1)
top-k ranking
(1)
sample complexity
(1)
reinforcement learning
(1)
stochastic convex optimization
(1)
quantile estimation
(1)
contextual bandit
(1)
feature selection
(1)
learning algorithm
(1)
regret bound
(1)
optimal policy
(1)
multi-armed bandit
(1)
Papers
Ripple Mechanisms for Discrete and Private Statistics
COLT 2026
Approximate Differential Privacy of the β_2 Mechanism
ICML 2025
Privately Counting Partially Ordered Data
ICLR 2025
Some Constructions of Private, Efficient, and Optimal K-Norm and Elliptic Gaussian Noise
COLT 2024
Better Private Linear Regression Through Better Private Feature Selection
NeurIPS 2023
Easy Differentially Private Linear Regression
ICLR 2023
A Joint Exponential Mechanism For Differentially Private Top-k
ICML 2022
Shuffle Private Stochastic Convex Optimization
ICLR 2022
Differentially Private Quantiles
ICML 2021
Pan-Private Uniformity Testing
COLT 2020
Locally Private Gaussian Estimation
NeurIPS 2019
Local Differential Privacy for Evolving Data
NeurIPS 2018
Fairness in Reinforcement Learning
ICML 2017
Fairness in Learning: Classic and Contextual Bandits
NeurIPS 2016