5.7k citations · 6k across the 3 of their papers we have counts for
3 papers
Domain-Adversarial Neural Networks
Hana Ajakan, Pascal Germain, Hugo Larochelle +2
We introduce a new representation learning algorithm suited to the context of domain adaptation, in which data at training and test time come from similar but different distributio…
Practical Bayesian Optimization of Machine Learning Algorithms
Jasper Snoek, Hugo Larochelle, Ryan P. Adams
Machine learning algorithms frequently require careful tuning of model hyperparameters, regularization terms, and optimization parameters. Unfortunately, this tuning is often a "bl…
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…