The field of machine learning (ML) is concerned with the question of how to construct algorithms that automatically improve with experience. In recent years many successful ML app...
Evaluation measures play an important role in machine learning because they are used not only to compare different learning algorithms, but also often as goals to optimize in cons...
Research in bioinformatics is driven by the experimental data. Current biological databases are populated by vast amounts of experimental data. Machine learning has been widely ap...
We present a new approximate inference algorithm for Deep Boltzmann Machines (DBM's), a generative model with many layers of hidden variables. The algorithm learns a separate...
We explore how to improve machine translation systems by adding more translation data in situations where we already have substantial resources. The main challenge is how to buck ...