Ensemble learning is a variational Bayesian method in which an intractable distribution is approximated by a lower-bound. Ensemble learning results in models with better generaliz...
Abstract— Although the human hand is a complex biomechanical system, only a small set of features may be necessary for observation learning of functional grasp classes. We explor...
Lillian Y. Chang, Nancy S. Pollard, Tom M. Mitchel...
We propose a simple two-level hierarchical probability model for unsupervised word segmentation. By treating words as strings composed of morphemes/phonemes which are themselves c...
Transfer learning addresses the problem of how to utilize plenty of labeled data in a source domain to solve related but different problems in a target domain, even when the train...
This paper addresses the problem of generating conflict-free periodic train timetables for large railway networks. We follow a two level approach, where a simplified track topolo...
Gabrio Curzio Caimi, Martin Fuchsberger, Marco Lau...