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20022024
most citedPractical Bayesian Optimization of Machine Learning Algorithms

5.7k citations

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7 papers · 1 filter

cs.LG20191 cited

A Transfer Learning Method for Goal Recognition Exploiting Cross-Domain Spatial Features

Thibault Duhamel, Mariane Maynard, Froduald Kabanza

The ability to infer the intentions of others, predict their goals, and deduce their plans are critical features for intelligent agents. For a long time, several approaches investi…

cs.LG20191 cited

Spectral Metric for Dataset Complexity Assessment

Frederic Branchaud-Charron, Andrew Achkar, Pierre-Marc Jodoin

In this paper, we propose a new measure to gauge the complexity of image classification problems. Given an annotated image dataset, our method computes a complexity measure called…

cs.LG20194 cited

From Visual to Acoustic Question Answering

Jerome Abdelnour, Giampiero Salvi, Jean Rouat

We introduce the new task of Acoustic Question Answering (AQA) to promote research in acoustic reasoning. The AQA task consists of analyzing an acoustic scene composed by a combina…

cs.LG2015334 cited

MADE: Masked Autoencoder for Distribution Estimation

Mathieu Germain, Karol Gregor, Iain Murray +1

There has been a lot of recent interest in designing neural network models to estimate a distribution from a set of examples. We introduce a simple modification for autoencoder neu…

cs.LG2012

Local Water Diffusion Phenomenon Clustering From High Angular Resolution Diffusion Imaging (HARDI)

Romain Giot, Christophe Charrier, Maxime Descoteaux

The understanding of neurodegenerative diseases undoubtedly passes through the study of human brain white matter fiber tracts. To date, diffusion magnetic resonance imaging (dMRI)…

cs.LG201296 cited

Conditional Restricted Boltzmann Machines for Structured Output Prediction

Volodymyr Mnih, Hugo Larochelle, Geoffrey E. Hinton

Conditional Restricted Boltzmann Machines (CRBMs) are rich probabilistic models that have recently been applied to a wide range of problems, including collaborative filtering, clas…