Publications related to An Adaptive Approach for Online Segmentation of Multi-Dimensional Mobile Data

Scale-Aware Test-Time Click Adaptation for Pulmonary Nodule and Mass Segmentation

Jiancheng Yang, Li Zhang, Zhigang Li, Bo Du

Pulmonary nodules and masses are crucial imaging features in lung cancer screening that require careful management in clinical diagnosis. Despite the success of deep learning-based medical image segmentation, the robust performance on various sizes of lesi ...

Cham2023

Distributional Regression and Autoregression via Optimal Transport

Laya Ghodrati

We present a framework for performing regression when both covariate and response are probability distributions on a compact and convex subset of

\R^d

. Our regression model is based on the theory of optimal transport and links the conditional Fr'echet m ...

EPFL2023

Data-Driven Behaviour Estimation in Parametric Games

Anna Maria Maddux, Nicolò Pagan

A central question in multi-agent strategic games deals with learning the underlying utilities driving the agents' behaviour. Motivated by the increasing availability of large data-sets, we develop an unifying data-driven technique to estimate agents' util ...

Elsevier2023

Neural controlled differential equations for crop classification

Accurate and scalable crop classification is important for food security and sustainable resources management. The temporal development of crops, i.e., their phenology, is a continuous phenomena that if properly captured, can help to discern them. The nove ...

2021

Leveraging insurance customer data to characterize socioeconomic indicators of Swiss municipalities

Claudia Rebeca Binder Signer, Emanuele Massaro

The availability of reliable socioeconomic data is critical for the design of urban policies and the implementation of location-based services; however, often, their temporal and geographical coverage remain scarce. We explore the potential for insurance c ...

2021

Sparsest piecewise-linear regression of one-dimensional data

Michaël Unser, Julien René Pierre Fageot, Thomas Jean Debarre, Quentin Alain Denoyelle

We study the problem of one-dimensional regression of data points with total-variation (TV) regularization (in the sense of measures) on the second derivative, which is known to promote piecewise-linear solutions with few knots. While there are efficient a ...

Elsevier2021

Multi-Dimensional Explanation of Target Variables from Documents

Boi Faltings, Claudiu-Cristian Musat, Diego Matteo Antognini

Automated predictions require explanations to be interpretable by humans. Past work used attention and rationale mechanisms to find words that predict the target variable of a document. Often though, they result in a tradeoff between noisy explanations or ...

ASSOC ADVANCEMENT ARTIFICIAL INTELLIGENCE2021

Quantification in Musculoskeletal Imaging Using Computational Analysis and Machine Learning: Segmentation and Radiomics

Meritxell Bach Cuadra

Although still limited in clinical practice, quantitative analysis is expected to increase the value of musculoskeletal (MSK) imaging. Segmentation aims at isolating the tissues and/or regions of interest in the image and is crucial to the extraction of qu ...

THIEME MEDICAL PUBL INC2020

Correlating Twitter Language with Community-Level Health Outcomes

Martin Jaggi, Arno Schneuwly

We study how language on social media is linked to diseases such as atherosclerotic heart disease (AHD), diabetes and various types of cancer. Our proposed model leverages state-of-the-art sentence embeddings, followed by a regression model and clustering, ...

ASSOC COMPUTATIONAL LINGUISTICS-ACL2019

Automatic L2 Regularization for Multiple Generalized Additive Models

Yousra El Bachir

Multiple generalized additive models are a class of statistical regression models wherein parameters of probability distributions incorporate information through additive smooth functions of predictors. The functions are represented by basis function expan ...

EPFL2019

An Adaptive Approach for Online Segmentation of Multi-Dimensional Mobile Data

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Scale-Aware Test-Time Click Adaptation for Pulmonary Nodule and Mass Segmentation

Distributional Regression and Autoregression via Optimal Transport

Data-Driven Behaviour Estimation in Parametric Games

Neural controlled differential equations for crop classification

Leveraging insurance customer data to characterize socioeconomic indicators of Swiss municipalities

Sparsest piecewise-linear regression of one-dimensional data

Multi-Dimensional Explanation of Target Variables from Documents

Quantification in Musculoskeletal Imaging Using Computational Analysis and Machine Learning: Segmentation and Radiomics

Correlating Twitter Language with Community-Level Health Outcomes

Automatic L2 Regularization for Multiple Generalized Additive Models

Distributional Regression and Autoregression via Optimal Transport

Neural controlled differential equations for crop classification

Correlating Twitter Language with Community-Level Health Outcomes

Leveraging insurance customer data to characterize socioeconomic indicators of Swiss municipalities

Multi-Dimensional Explanation of Target Variables from Documents

Quantification in Musculoskeletal Imaging Using Computational Analysis and Machine Learning: Segmentation and Radiomics

Automatic L2 Regularization for Multiple Generalized Additive Models

Scale-Aware Test-Time Click Adaptation for Pulmonary Nodule and Mass Segmentation

Data-Driven Behaviour Estimation in Parametric Games

Sparsest piecewise-linear regression of one-dimensional data