5.7k citations · 17.6k across the 75 of their papers we have counts for
5 papers · 1 filter
Learning where to Attend with Deep Architectures for Image Tracking
Misha Denil, Loris Bazzani, Hugo Larochelle +1
We discuss an attentional model for simultaneous object tracking and recognition that is driven by gaze data. Motivated by theories of perception, the model consists of two interac…
Loss-sensitive Training of Probabilistic Conditional Random Fields
Maksims N. Volkovs, Hugo Larochelle, Richard S. Zemel
We consider the problem of training probabilistic conditional random fields (CRFs) in the context of a task where performance is measured using a specific loss function. While maxi…
Classification of Sets using Restricted Boltzmann Machines
Jérôme Louradour, Hugo Larochelle
We consider the problem of classification when inputs correspond to sets of vectors. This setting occurs in many problems such as the classification of pieces of mail containing se…
Autotagging music with conditional restricted Boltzmann machines
Michael Mandel, Razvan Pascanu, Hugo Larochelle +1
This paper describes two applications of conditional restricted Boltzmann machines (CRBMs) to the task of autotagging music. The first consists of training a CRBM to predict tags t…
On Nonparametric Guidance for Learning Autoencoder Representations
Jasper Snoek, Ryan Prescott Adams, Hugo Larochelle
Unsupervised discovery of latent representations, in addition to being useful for density modeling, visualisation and exploratory data analysis, is also increasingly important for…