Concept

AlphaGo

Related publications (4)

Design of an Always-On Deep Neural Network-Based 1-mu W Voice Activity Detector Aided With a Customized Software Model for Analog Feature Extraction

This paper presents an ultra-low-power voice activity detector (VAD). It uses analog signal processing for acoustic feature extraction (AFE) directly on the microphone output, approximate event-driven analog-to-digital conversion (ED-ADC), and digital deep ...

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC2019

Deep learning relies on a very specific kind of neural networks: those superposing several neural layers. In the last few years, deep learning achieved major breakthroughs in many tasks such as image analysis, speech recognition, natural language processin ...

2018

Deep neural network training spends most of the computation on examples that are properly handled, and could be ignored. We propose to mitigate this phenomenon with a principled importance sampling scheme that focuses computation on "informative" examples ...

Idiap2018

Les enjeux de la transition énergétique suisse: comprendre pour choisir : 100 questions-réponses

Daniel Favrat, François Richard Vuille, Suren Erkman

De nombreux pays se trouvent aujourd’hui engagés dans un processus de «transition énergétique. La Suisse affiche des ambitions particulièrement élevées en la matière : renoncer progressivement à l’énergie nucléaire, diminuer sa dépendance aux énergies foss ...

PPUR2015

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