Recursive Implementation of the Distributed Karhunen-Loeve Transform
Graph Chatbot
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.
Recommender systems enable service providers to predict and address the individual needs of their customers so as to deliver personalized experiences. In this paper, we formulate the recommendation problem as an inference problem on a Pairwise Markov Rando ...
Recent research works on distributed adaptive networks have inten- sively studied the case where the nodes estimate a common parame- ter vector collaboratively. However, there are many applications that are multitask-oriented in the sense that there are mu ...
We apply diffusion strategies to propose a cooperative reinforcement learning algorithm, in which agents in a network communicate with their neighbors to improve predictions about their environment. The algorithm is suitable to learn off-policy even in lar ...
We propose two new and enhanced algorithms for greedy sampling of high- dimensional functions. While the techniques have a substantial degree of generality, we frame the discussion in the context of methods for empirical interpolation and the devel- opment ...
The multitask diffusion LMS algorithm is an efficient strategy to address distributed estimation problems that are multitask-oriented in the sense that the optimum parameter vector may not be the same for every cluster of nodes. In this work, we explore th ...
This paper surveys recent advances related to adaptation, learning, and optimization over networks. Various distributed strategies are discussed that enable a collection of networked agents to interact locally in response to streaming data and to continual ...
We examine the performance of stochastic-gradient learners over connected networks for global optimization problems involving risk functions that are not necessarily quadratic. We consider two well-studied classes of distributed schemes including consensus ...
Machine learning algorithms are widely used today for analytical tasks such as data cleaning, data categorization, or data filtering. At the same time, the rise of social media motivates recent uptake in large scale graph processing. Both categories of alg ...
Machine learning algorithms are widely used today for analytical tasks such as data cleaning, data categorization, or data filtering. At the same time, the rise of social media motivates recent uptake in large scale graph processing. Both categories of alg ...
Clinical use of the Stejskal-Tanner diffusion weighted images is hampered by the geometric distortions that result from the large residual 3D eddy current field induced. In this work we aimed to predict, using linear response theory, the residual 3D eddy c ...
Institute of Electrical and Electronics Engineers2013
