Publications associées à Inverse Reinforcement Learning of Pedestrian-Robot Coordination

Chattez avec Graph Search

Posez n’importe quelle question sur les cours, conférences, exercices, recherches, actualités, etc. de l’EPFL ou essayez les exemples de questions ci-dessous.

AVERTISSEMENT : Le chatbot Graph n'est pas programmé pour fournir des réponses explicites ou catégoriques à vos questions. Il transforme plutôt vos questions en demandes API qui sont distribuées aux différents services informatiques officiellement administrés par l'EPFL. Son but est uniquement de collecter et de recommander des références pertinentes à des contenus que vous pouvez explorer pour vous aider à répondre à vos questions.

Leveraging Continuous Time to Understand Momentum When Training Diagonal Linear Networks

Nicolas Henri Bernard Flammarion, Hristo Georgiev Papazov, Scott William Pesme

In this work, we investigate the effect of momentum on the optimisation trajectory of gradient descent. We leverage a continuous-time approach in the analysis of momentum gradient descent with step size

\gamma

and momentum parameter

\beta

that allows u ...

2024

Inverse Reinforcement Learning of Pedestrian-Robot Coordination

Graph Chatbot

Chattez avec Graph Search

Efficient Temporally-Aware DeepFake Detection using H.264 Motion Vectors

Efficient local linearity regularization to overcome catastrophic overfitting

Investigating neural resource allocation in the sensorimotor control of extra limbs

Advancing Self-Supervised Deep Learning for 3D Scene Understanding

Predicting the long-term collective behaviour of fish pairs with deep learning

Optimization Algorithms for Decentralized, Distributed and Collaborative Machine Learning

Infusing structured knowledge priors in neural models for sample-efficient symbolic reasoning

Incorporating Projective Geometry into Deep Learning

Robust NAS under adversarial training: benchmark, theory, and beyond

Leveraging Continuous Time to Understand Momentum When Training Diagonal Linear Networks

Efficient Temporally-Aware DeepFake Detection using H.264 Motion Vectors

Efficient local linearity regularization to overcome catastrophic overfitting

Investigating neural resource allocation in the sensorimotor control of extra limbs

Advancing Self-Supervised Deep Learning for 3D Scene Understanding

Predicting the long-term collective behaviour of fish pairs with deep learning

Optimization Algorithms for Decentralized, Distributed and Collaborative Machine Learning

Infusing structured knowledge priors in neural models for sample-efficient symbolic reasoning

Incorporating Projective Geometry into Deep Learning

Robust NAS under adversarial training: benchmark, theory, and beyond

Leveraging Continuous Time to Understand Momentum When Training Diagonal Linear Networks