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Testing the choice of a mixing distribution in discrete choice models

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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

Testing the choice of a mixing distribution in discrete choice models

Graph Chatbot

Chattez avec Graph Search

Learning Robust and Adaptive Representations: from Interactions, for Interactions

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Multiple testing with test statistics following heavy-tailed distributions

Trajectory planning under environmental uncertainty with finite-sample safety guarantees

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

Information content and aerosol property retrieval potential for different types of in situ polar nephelometer data

Capturing trade-offs between daily scheduling choices

Learning Robust and Adaptive Representations: from Interactions, for Interactions

Clustering and Informative Path Planning for 3D Gas Distribution Mapping: Algorithms and Performance Evaluation

Multiple testing with test statistics following heavy-tailed distributions

Trajectory planning under environmental uncertainty with finite-sample safety guarantees

Making Computer Vision Models Robust and Adaptive

Dalton: Learned Partitioning for Distributed Data Streams

Leveraging species distribution models to predict the impact of climate change on glacier-fed stream biofilms