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Concept

Arbre de décision

Publications associées (30)

Decision Learning and Adaptation Over Multi-Task Networks

Ali H. Sayed

This paper studies the operation of multi-agent networks engaged in multi-task decision problems under the paradigm of simultaneous learning and adaptation. Two scenarios are considered:one in which a decision must be taken among multiple states of nature ...

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC2021

Rationalization through Concepts

Boi Faltings, Diego Matteo Antognini

Automated predictions require explanations to be interpretable by humans. One type of ex- planation is a rationale, i.e., a selection of in- put features such as relevant text snippets from which the model computes the outcome. How- ever, a single overall ...

2021

Tree in Tree: from Decision trees to Decision Graphs

Mahsa Shoaran, Bingzhao Zhu

Decision trees have been widely used as classifiers in many machine learning applications thanks to their lightweight and interpretable decision process. This paper introduces Tree in Tree decision graph (TnT), a framework that extends the conventional dec ...

Curran Associates, Inc, (NIPS '21: Proceedings of the 35th International Conference on Neural Information Processing Systems)2021

Prospects for B-c(+) -> tau(+)nu(tau) at FCC-ee

Donal Patrick Hill, Clement Helsens

This paper presents the prospects for a precise measurement of the branching fraction of the leptonic B-c(+) -> tau(+)nu(tau) decay at the Future Circular Collider (FCC-ee) running at the Z-pole. A detailed description of the simulation and analysis framew ...

Springer Nature2021

A scenario modeling pipeline for COVID-19 emergency planning

Francisco Javier Perez Saez, Joseph Chadi Benoit Lemaitre

Coronavirus disease 2019 (COVID-19) has caused strain on health systems worldwide due to its high mortality rate and the large portion of cases requiring critical care and mechanical ventilation. During these uncertain times, public health decision makers, ...

Nature Portfolio2021

Monte Carlo Estimators for Differential Light Transport

Wenzel Alban Jakob, Tizian Lucien Zeltner, Sébastien Nicolas Speierer

Physically based differentiable rendering algorithms propagate derivatives through realistic light transport simulations and have applications in diverse areas including inverse reconstruction and machine learning. Recent progress has led to unbiased metho ...

ASSOC COMPUTING MACHINERY2021

Predicting involuntary hospitalization in psychiatry: A machine learning investigation

Mehdi Gholam

Background Coercion in psychiatry is a controversial issue. Identifying its predictors and their interaction using traditional statistical methods is difficult, given the large number of variables involved. The purpose of this study was to use machine-lear ...

CAMBRIDGE UNIV PRESS2021

Industry 4.0 Technologies and Customer-centricity for Digital Supply Chains

Rachel Agnès Laetitia Rosemonde Marie Lacroix

The last few years have experienced the emergence of Industry 4.0 (I4.0), ultra-customization, and the explosion of demand for ethical, fair trade, and sustainable consumption. Organizations have therefore started a digital transformation of their SCs and ...

EPFL2021

Nearly-Tight and Oblivious Algorithms for Explainable Clustering

Ola Nils Anders Svensson, Adam Teodor Polak, Buddhima Ruwanmini Gamlath Gamlath Ralalage, Xinrui Jia

We study the problem of explainable clustering in the setting first formalized by Dasgupta, Frost, Moshkovitz, and Rashtchian (ICML 2020). A k-clustering is said to be explainable if it is given by a decision tree where each internal node splits data point ...

2021

Combined use of airborne laser scanning and hyperspectral imaging for forest inventories

Matthew Josef Parkan

The thesis presented hereby proposes as a general objective the estimation of forest inventory parameters (e.g. trunk location, height, basal area, crown area, species, etc..) from the combination of Airborne Laser Scanning (ALS) and Hyperspectal Imaging ( ...

EPFL2019