Matthew Reimherr
14 papers · 2019–2026 · 6 venues · across top CS/AI venues
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Achievements
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πΊοΈ Taxonomy Completionist (24) π Conference Polyglot Β· Silver π Academic Marathon Β· Sprint π Interdisciplinary Bridge Β· Silver π£ Hot Topic Early Bird
π§¬
Topic Evolution
π
Grand Slam
π
Keyword Champion
(3)
ποΈ
Keyword Collector
(68)
π
Century Club Β· Bronze
π
Renaissance Researcher
(5)
Top co-authors
Research topics
Machine Learning
(12)
Application Areas
(9)
Mathematics & Optimization
(8)
Artificial Intelligence
(6)
Mathematics
(6)
Security & Privacy
(5)
Core AI
(5)
Differential Privacy
(5)
Optimization
(5)
Optimization & Theory
(3)
Core Methods
(2)
Learning Types
(2)
Computer Vision
(1)
Data Science & Analytics
(1)
Deep Learning
(1)
Keywords
differential privacy
(8)
exponential mechanism
(3)
functional data analysis
(3)
shape analysis
(2)
frechet mean
(2)
riemannian manifold
(2)
gradient mechanism
(2)
privacy budget
(2)
feature selection
(1)
hilbert space
(1)
matrix factorization
(1)
reproducing kernel hilbert space
(1)
nonparametric estimation
(1)
manifold learning
(1)
gaussian process
(1)
markov chain monte carlo
(1)
bayesian inference
(1)
stochastic process
(1)
kernel ridge regression
(1)
excess risk
(1)
Papers
Harnessing Vision-Language Models for Time Series Anomaly Detection
AAAI 2026
Gaussian Differentially Private Human Faces Under a Face Radial Curve Representation
ICLR 2025
M$^2$AD: Multi-Sensor Multi-System Anomaly Detection through Global Scoring and Calibrated Thresholding
AISTATS 2025
On Hypothesis Transfer Learning of Functional Linear Models
ICML 2024
Pure Differential Privacy for Functional Summaries with a Laplace-like Process
JMLR 2024
Smoothness Adaptive Hypothesis Transfer Learning
ICML 2024
Shape And Structure Preserving Differential Privacy
NeurIPS 2022
A Highly-Efficient Group Elastic Net Algorithm with an Application to Function-On-Scalar Regression
NeurIPS 2021
Differential Privacy Over Riemannian Manifolds
NeurIPS 2021
Exact Privacy Guarantees for Markov Chain Implementations of the Exponential Mechanism with Artificial Atoms
NeurIPS 2021
Benefits and Pitfalls of the Exponential Mechanism with Applications to Hilbert Spaces and Functional PCA
ICML 2019
Elliptical Perturbations for Differential Privacy
NeurIPS 2019
Formal Privacy for Functional Data with Gaussian Perturbations
ICML 2019
KNG: The K-Norm Gradient Mechanism
NeurIPS 2019