Contextual bandit learning is a reinforcement learning problem where the learner repeatedly receives a set of features (context), takes an action and receives a reward based on th...
Unsupervised discovery of latent representations, in addition to being useful for density modeling, visualisation and exploratory data analysis, is also increasingly important for...
Jasper Snoek, Ryan Prescott Adams, Hugo Larochelle
Selecting the optimal kernel is an important and difficult challenge in applying kernel methods to pattern recognition. To address this challenge, multiple kernel learning (MKL) ...
rrent ML, synchronization abstractions can be defined and passed as values, much like functions in ML. This mechanism admits a powerful, modular style of concurrent programming, c...
There are now a number of bidirectional programming languages, where every program can be read both as a forward transformation mapping one data structure to another and as a reve...
J. Nathan Foster, Alexandre Pilkiewicz, Benjamin C...