Matthew Reimherr

40 papers A* 12A 1C 2Journal 25

Year	Rank	Type	Title / Venue / Authors
2026	A*	`conf`	Harnessing Vision-Language Models for Time Series Anomaly Detection. AAAI Zelin He, Sarah Alnegheimish, Matthew Reimherr
2026	J	`jnl`	SenTSR-Bench: Thinking with Injected Knowledge for Time-Series Reasoning. CoRR Zelin He, Boran Han, Xiyuan Zhang, Shuai Zhang, Haotian Lin, Qi Zhu, Haoyang Fang, Danielle C. Maddix, Abdul Fatir Ansari, Akash Chandrayan, Abhinav Pradhan, Yuyang Wang, Matthew Reimherr
2025	J	`jnl`	FAStEN: An Efficient Adaptive Method for Feature Selection and Estimation in High-Dimensional Functional Regressions. J. Comput. Graph. Stat. Tobia Boschi, Lorenzo Testa, Francesca Chiaromonte, Matthew Reimherr
2025	A*	`conf`	Gaussian Differentially Private Human Faces Under a Face Radial Curve Representation. ICLR Carlos J. Soto, Matthew Reimherr, Aleksandra B. Slavkovic, Mark Shriver
2025	J	`jnl`	Harnessing Vision-Language Models for Time Series Anomaly Detection. CoRR Zelin He, Sarah Alnegheimish, Matthew Reimherr
2025	A	`conf`	M AISTATS Sarah Alnegheimish, Zelin He, Matthew Reimherr, Akash Chandrayan, Abhinav Pradhan, Luca D'Angelo
2025	J	`jnl`	M CoRR Sarah Alnegheimish, Zelin He, Matthew Reimherr, Akash Chandrayan, Abhinav Pradhan, Luca D'Angelo
2025	J	`jnl`	Model-Robust and Adaptive-Optimal Transfer Learning for Tackling Concept Shifts in Nonparametric Regression. CoRR Haotian Lin, Matthew Reimherr
2024	C	`conf`	Differentially Private Quantile Regression. PSD Tran Tran, Matthew Reimherr, Aleksandra B. Slavkovic
2024	J	`jnl`	Gaussian Differentially Private Human Faces Under a Face Radial Curve Representation. CoRR Carlos Soto, Matthew Reimherr, Aleksandra B. Slavkovic, Mark Shriver
2024	A*	`conf`	On Hypothesis Transfer Learning of Functional Linear Models. ICML Haotian Lin, Matthew Reimherr
2024	J	`jnl`	Pure Differential Privacy for Functional Summaries with a Laplace-like Process. J. Mach. Learn. Res. Haotian Lin, Matthew Reimherr
2024	A*	`conf`	Smoothness Adaptive Hypothesis Transfer Learning. ICML Haotian Lin, Matthew Reimherr
2024	J	`jnl`	Smoothness Adaptive Hypothesis Transfer Learning. CoRR Haotian Lin, Matthew Reimherr
2023	J	`jnl`	Differentially Private Functional Summaries via the Independent Component Laplace Process. CoRR Haotian Lin, Matthew Reimherr
2023	J	`jnl`	Modern non-linear function-on-function regression. Stat. Comput. Aniruddha Rajendra Rao, Matthew Reimherr
2023	J	`jnl`	Nonlinear Functional Modeling Using Neural Networks. J. Comput. Graph. Stat. Aniruddha Rajendra Rao, Matthew Reimherr
2022	J	`jnl`	A Formal Privacy Framework for Partially Private Data. CoRR Jeremy Seeman, Aleksandra B. Slavkovic, Matthew Reimherr
2022	J	`jnl`	Exact Privacy Guarantees for Markov Chain Implementations of the Exponential Mechanism with Artificial Atoms. CoRR Jeremy Seeman, Matthew Reimherr, Aleksandra B. Slavkovic
2022	J	`jnl`	On Transfer Learning in Functional Linear Regression. CoRR Haotian Lin, Matthew Reimherr
2022	A*	`conf`	Shape And Structure Preserving Differential Privacy. NeurIPS Carlos Soto, Karthik Bharath, Matthew Reimherr, Aleksandra B. Slavkovic
2022	J	`jnl`	Shape And Structure Preserving Differential Privacy. CoRR Carlos Soto, Karthik Bharath, Matthew Reimherr, Aleksandra B. Slavkovic
2021	A*	`conf`	A Highly-Efficient Group Elastic Net Algorithm with an Application to Function-On-Scalar Regression. NeurIPS Tobia Boschi, Matthew Reimherr, Francesca Chiaromonte
2021	J	`jnl`	Adaptive function-on-scalar regression with a smoothing elastic net. J. Multivar. Anal. Ardalan Mirshani, Matthew Reimherr
2021	A*	`conf`	Differential Privacy Over Riemannian Manifolds. NeurIPS Matthew Reimherr, Karthik Bharath, Carlos Soto
2021	A*	`conf`	Exact Privacy Guarantees for Markov Chain Implementations of the Exponential Mechanism with Artificial Atoms. NeurIPS Jeremy Seeman, Matthew Reimherr, Aleksandra B. Slavkovic
2021	J	`jnl`	Modern Non-Linear Function-on-Function Regression. CoRR Aniruddha Rajendra Rao, Matthew Reimherr
2021	J	`jnl`	Non-linear Functional Modeling using Neural Networks. CoRR Aniruddha Rajendra Rao, Matthew Reimherr
2020	J	`jnl`	An Efficient Semi-smooth Newton Augmented Lagrangian Method for Elastic Net. CoRR Tobia Boschi, Matthew Reimherr, Francesca Chiaromonte
2020	J	`jnl`	Modern Multiple Imputation with Functional Data. CoRR Aniruddha Rajendra Rao, Matthew Reimherr
2020	C	`conf`	Private Posterior Inference Consistent with Public Information: A Case Study in Small Area Estimation from Synthetic Census Data. PSD Jeremy Seeman, Aleksandra B. Slavkovic, Matthew Reimherr
2019	A*	`conf`	Benefits and Pitfalls of the Exponential Mechanism with Applications to Hilbert Spaces and Functional PCA. ICML Jordan Awan, Ana Kenney, Matthew Reimherr, Aleksandra B. Slavkovic
2019	J	`jnl`	Benefits and Pitfalls of the Exponential Mechanism with Applications to Hilbert Spaces and Functional PCA. CoRR Jordan Awan, Ana Kenney, Matthew Reimherr, Aleksandra B. Slavkovic
2019	A*	`conf`	Elliptical Perturbations for Differential Privacy. NeurIPS Matthew Reimherr, Jordan Awan
2019	J	`jnl`	Elliptical Perturbations for Differential Privacy. CoRR Matthew Reimherr, Jordan Awan
2019	A*	`conf`	Formal Privacy for Functional Data with Gaussian Perturbations. ICML Ardalan Mirshani, Matthew Reimherr, Aleksandra B. Slavkovic
2019	J	`jnl`	Functional data analysis for computational biology. Bioinform. Marzia A. Cremona, Hongyan Xu, Kateryna D. Makova, Matthew Reimherr, Francesca Chiaromonte, Pedro Madrigal
2019	A*	`conf`	KNG: The K-Norm Gradient Mechanism. NeurIPS Matthew Reimherr, Jordan Awan
2019	J	`jnl`	KNG: The K-Norm Gradient Mechanism. CoRR Matthew Reimherr, Jordan Awan
2016	J	`jnl`	A randomness test for functional panels. J. Multivar. Anal. Piotr Kokoszka, Matthew Reimherr, Nikolas Wölfing