Mean absolute percentage error

Science formelle
Statistique
Analyse des données
Régression (statistiques)

À propos
Confidentialité
Mentions légales

Graph Chatbot

Publications associées (26)

Relaxed Wyner's Common Information

Michael Christoph Gastpar, Erixhen Sula

In the problem of coded caching for media delivery, two separate coding opportunities have been identified. The first opportunity is a multi-user advantage and crucially hinges on a public broadcast link in the delivery phase. This has been explored in a p ...

IEEE2019

Regularization via Mass Transportation

Daniel Kuhn, Soroosh Shafieezadeh Abadeh, Peyman Mohajerin Esfahani

The goal of regression and classification methods in supervised learning is to minimize the empirical risk, that is, the expectation of some loss function quantifying the prediction error under the empirical distribution. When facing scarce training data, ...

2019

Calibration Aspects of INS Navigation

Philipp Clausen

The use of a Bayesian filter (e.g., Kalman filter) for the fusion of information from satellite positioning and inertial navigation is a common approach in many applications, where the knowledge of position, velocity, and attitude in space are of great int ...

EPFL2019

Data-Driven Inverse Optimization with Incomplete Information

Daniel Kuhn, Soroosh Shafieezadeh Abadeh, Peyman Mohajerin Esfahani, Grani Adiwena Hanasusanto

In data-driven inverse optimization an observer aims to learn the preferences of an agent who solves a parametric optimization problem depending on an exogenous signal. Thus, the observer seeks the agent's objective function that best explains a historical ...

2018

A statistical shape model to predict the premorbid glenoid cavity

Alexandre Terrier, Alain Farron, Steve Michel Berger, Daniel Abler, Philippe Büchler

Background: This study proposes a method for inferring the premorbid glenoid shape and orientation of scapulae affected by glenohumeral osteoarthritis (OA) to inform restorative surgery. ...

MOSBY-ELSEVIER2018

Time course of prediction errors in sequential decision making

Michael Herzog, He Xu

In reinforcement learning, an agent makes sequential decisions to maximize reward. During learning, the actual and expected outcome are compared to tell whether a decision was good or bad. The difference between the actual outcome and expected outcome is t ...

2018

Page 2 sur 2