Publications related to On Optimal Two Sample Homogeneity Tests for Finite Alphabets

Transportation-based functional ANOVA and PCA for covariance operators

Victor Panaretos, Yoav Zemel, Valentina Masarotto

We consider the problem of comparing several samples of stochastic processes with respect to their second-order structure, and describing the main modes of variation in this second order structure, if present. These tasks can be seen as an Analysis of Vari ...

Inst Mathematical Statistics-Ims2024

Higher Order Asymptotics: Applications to Satellite Conjunction and Boundary Problems

Soumaya Elkantassi

Higher-order asymptotics provide accurate approximations for use in parametric statistical modelling. In this thesis, we investigate using higher-order approximations in two-specific settings, with a particular emphasis on the tangent exponential model. Th ...

EPFL2023

Near Collision Attack Against Grain V1

Daniel Patrick Collins, Subhadeep Banik, Willi Meier

A near collision attack against the Grain v1 stream cipher was proposed by Zhang et al. in Eurocrypt 18. The attack uses the fact that two internal states of the stream cipher with very low hamming distance between them, produce similar keystream sequences ...

2023

Memory of Motion for Initializing Optimization in Robotics

Teguh Santoso Lembono

Many robotics problems are formulated as optimization problems. However, most optimization solvers in robotics are locally optimal and the performance depends a lot on the initial guess. For challenging problems, the solver will often get stuck at poor loc ...

EPFL2022

Feature distribution learning by passive exposure

David Pascucci, Gizay Ceylan

Humans can rapidly estimate the statistical properties of groups of stimuli, including their average and variability. But recent studies of so-called Feature Distribution Learning (FDL) have shown that observers can quickly learn even more complex aspects ...

ELSEVIER2022

OptTTA: Learnable Test-Time Augmentation for Source-Free Medical Image Segmentation Under Domain Shift

Jean-Philippe Thiran, Guillaume Marc Georges Vray, Devavrat Tomar

As distribution shifts are inescapable in realistic clinical scenarios due to inconsistencies in imaging protocols, scanner vendors, and across different centers, well-trained deep models incur a domain generalization problem in unseen environments. Despit ...

PMLR2022

Multiple testing with test statistics following heavy-tailed distributions

Zhiwen Jiang

In multiple testing problems where the components come from a mixture model of noise and true effect, we seek to first test for the existence of the non-zero components, and then identify the true alternatives under a fixed significance level

\alpha

. Two ...

EPFL2021

A Statistical Test for Probabilistic Fairness

Daniel Kuhn, Viet Anh Nguyen, Bahar Taskesen

Algorithms are now routinely used to make consequential decisions that affect human lives. Examples include college admissions, medical interventions or law enforcement. While algorithms empower us to harness all information hidden in vast amounts of data, ...

2021

Interpreting null models of resting-state functional MRI dynamics: not throwing the model out with the hypothesis

Dimitri Nestor Alice Van De Ville, Raphaël Pierre Liégeois

Null models are useful for assessing whether a dataset exhibits a non-trivial property of interest. These models have recently gained interest in the neuroimaging community as means to explore dynamic properties of functional Magnetic Resonance Imaging (fM ...

ACADEMIC PRESS INC ELSEVIER SCIENCE2021

NovelT2Mapping for Evaluating Cervical Cancer Features by Providing QuantitativeT2Maps and Synthetic Morphologic Images: A Preliminary Study

Tobias Kober, Tom Hilbert, Yong Zhang, Meng Yang, Jie Liu

Background The application value of T(2)mapping in evaluating cervical cancer (CC) features remains unclear. Purpose To investigate the role of T(2)values in evaluating CC classification, grade, and lymphovascular space invasion (LVSI) in comparison to app ...

WILEY2020

On Optimal Two Sample Homogeneity Tests for Finite Alphabets

Graph Chatbot

Chat with Graph Search

Transportation-based functional ANOVA and PCA for covariance operators

Higher Order Asymptotics: Applications to Satellite Conjunction and Boundary Problems

Near Collision Attack Against Grain V1

Memory of Motion for Initializing Optimization in Robotics

Feature distribution learning by passive exposure

OptTTA: Learnable Test-Time Augmentation for Source-Free Medical Image Segmentation Under Domain Shift

Multiple testing with test statistics following heavy-tailed distributions

A Statistical Test for Probabilistic Fairness

Interpreting null models of resting-state functional MRI dynamics: not throwing the model out with the hypothesis

NovelT2Mapping for Evaluating Cervical Cancer Features by Providing QuantitativeT2Maps and Synthetic Morphologic Images: A Preliminary Study

Transportation-based functional ANOVA and PCA for covariance operators

Higher Order Asymptotics: Applications to Satellite Conjunction and Boundary Problems

Near Collision Attack Against Grain V1

Memory of Motion for Initializing Optimization in Robotics

OptTTA: Learnable Test-Time Augmentation for Source-Free Medical Image Segmentation Under Domain Shift

Multiple testing with test statistics following heavy-tailed distributions

Feature distribution learning by passive exposure

Interpreting null models of resting-state functional MRI dynamics: not throwing the model out with the hypothesis

A Statistical Test for Probabilistic Fairness

NovelT2Mapping for Evaluating Cervical Cancer Features by Providing QuantitativeT2Maps and Synthetic Morphologic Images: A Preliminary Study