Concept

Training, validation, and test data sets

Related publications (455)

About
Privacy
Disclaimer

Graph Chatbot

Chat with Graph Search

Ask any question about EPFL courses, lectures, exercises, research, news, etc. or try the example questions below.

DISCLAIMER: The Graph Chatbot is not programmed to provide explicit or categorical answers to your questions. Rather, it transforms your questions into API requests that are distributed across the various IT services officially administered by EPFL. Its purpose is solely to collect and recommend relevant references to content that you can explore to help you answer your questions.

Training, validation, and test data sets

Graph Chatbot

Chat with Graph Search

Strategy to validate sensor-placement methodologies in the context of sparse measurement in complex urban systems

Noninvasive estimation of aortic hemodynamics and cardiac contractility using machine learning

Privacy-preserving and Personalized Federated Machine Learning for Medical Data

Seek and learn: Automated identification of microevents in animal behaviour using envelopes of acceleration data and machine learning

Gait in real world: validated algorithms for gait periods and speed estimation using a single wearable sensor

Big-Data Science in Porous Materials: Materials Genomics and Machine Learning

IMPROVING CROSS-DATASET PERFORMANCE OF FACE PRESENTATION ATTACK DETECTION SYSTEMS USING FACE RECOGNITION DATASETS

Redundant features can hurt robustness to distributions shift

Seismic Vulnerability Assessment at Large Scale – City of Geneva

From human action understanding to robot action execution: how the physical properties of handled objects modulate non-verbal cues