Publications related to Shrinkage (statistics)

MaskCLR: Attention-Guided Contrastive Learning for Robust Action Representation Learning

Alexandre Massoud Alahi, Mohamed Ossama Ahmed Abdelfattah, Mariam Ahmed Mahmoud Hegazy Hassan

Current transformer-based skeletal action recognition models tend to focus on a limited set of joints and low-level motion patterns to predict action classes. This results in significant performance degradation under small skeleton perturbations or changin ...

2024

On double-descent in uncertainty quantification in overparametrized models

Florent Gérard Krzakala, Lenka Zdeborová, Lucas Andry Clarte, Bruno Loureiro, Bruno Loureiro

Uncertainty quantification is a central challenge in reliable and trustworthy machine learning. Naive measures such as last-layer scores are well-known to yield overconfident estimates in the context of overparametrized neural networks. Several methods, ra ...

PMLR Proceedings of Machine Learning Research2023

Causal inference with recurrent and competing events

Mats Julius Stensrud, Pal Christie Ryalen, Matias Janvin

Many research questions concern treatment effects on outcomes that can recur several times in the same individual. For example, medical researchers are interested in treatment effects on hospitalizations in heart failure patients and sports injuries in ath ...

SPRINGER2023

Continual Test-Time Domain Adaptation

Olga Fink, Qin Wang

Test-time domain adaptation aims to adapt a source pretrained model to a target domain without using any source data. Existing works mainly consider the case where the target domain is static. However, real-world machine perception systems are running in n ...

IEEE COMPUTER SOC2022

Deformation-aware Unpaired Image Translation for Pose Estimation on Laboratory Animals

Pascal Fua, Pavan P Ramdya, Helge Jochen Rhodin, Semih Günel, Siyuan Li, Mirela Ostrek

Our goal is to capture the pose of neuroscience model organisms, without using any manual supervision, to be able to study how neural circuits orchestrate behaviour. Human pose estimation attains remarkable accuracy when trained on real or simulated datase ...

2020

Distributionally Robust Inverse Covariance Estimation: The Wasserstein Shrinkage Estimator

Daniel Kuhn, Viet Anh Nguyen, Peyman Mohajerin Esfahani

We introduce a distributionally robust maximum likelihood estimation model with a Wasserstein ambiguity set to infer the inverse covariance matrix of a p-dimensional Gaussian random vector from n independent samples. The proposed model minimizes the worst ...

2020

Forward-Backward Splitting for Optimal Transport Based Problems

Pascal Frossard, Guillermo Ortiz Jimenez, Mireille El Gheche, Hermina Petric Maretic, Effrosyni Simou

Optimal transport aims to estimate a transportation plan that minimizes a displacement cost. This is realized by optimizing the scalar product between the sought plan and the given cost, over the space of doubly stochastic matrices. When the entropy regula ...

2020

Integrating the Finite Element Method with a Data-Driven Approach for Dam Displacement Prediction

Zhenzhu Meng, Yating Hu, Chenfei Shao

Both numerical simulations and data-driven methods have been applied in dam's displacement modeling. For monitored displacement data-driven methods, the physical mechanism and structural correlations were rarely discussed. In order to take the spatial and ...

2020

Hybrid regularisation and the (in)admissibility of ridge regression in infinite dimensional Hilbert spaces

Victor Panaretos, Anirvan Chakraborty

We consider the problem of estimating the slope function in a functional regression with a scalar response and a functional covariate. This central problem of functional data analysis is well known to be ill-posed, thus requiring a regularised estimation p ...

2019

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Shrinkage (statistics)

MaskCLR: Attention-Guided Contrastive Learning for Robust Action Representation Learning

On double-descent in uncertainty quantification in overparametrized models

Causal inference with recurrent and competing events

Unbiased likelihood-based estimation of Wright-Fisher diffusion processes

Continual Test-Time Domain Adaptation

Deformation-aware Unpaired Image Translation for Pose Estimation on Laboratory Animals

Distributionally Robust Inverse Covariance Estimation: The Wasserstein Shrinkage Estimator

Forward-Backward Splitting for Optimal Transport Based Problems

Integrating the Finite Element Method with a Data-Driven Approach for Dam Displacement Prediction

Hybrid regularisation and the (in)admissibility of ridge regression in infinite dimensional Hilbert spaces

Graph Chatbot

Chat with Graph Search

MaskCLR: Attention-Guided Contrastive Learning for Robust Action Representation Learning

On double-descent in uncertainty quantification in overparametrized models

Unbiased likelihood-based estimation of Wright-Fisher diffusion processes

Causal inference with recurrent and competing events

Distributionally Robust Inverse Covariance Estimation: The Wasserstein Shrinkage Estimator

Integrating the Finite Element Method with a Data-Driven Approach for Dam Displacement Prediction

Hybrid regularisation and the (in)admissibility of ridge regression in infinite dimensional Hilbert spaces

Continual Test-Time Domain Adaptation

Forward-Backward Splitting for Optimal Transport Based Problems

Deformation-aware Unpaired Image Translation for Pose Estimation on Laboratory Animals