Reasoning about agents that we observe in the world is challenging. Our available information is often limited to observations of the agent’s external behavior in the past and p...
H. Van Dyke Parunak, Sven Brueckner, Robert S. Mat...
A common approach in machine learning is to use a large amount of labeled data to train a model. Usually this model can then only be used to classify data in the same feature spac...
A system that segments and labels tabla strokes from real performances is described. Performance is evaluated on a large database taken from three performers under different recor...
—We describe a semantic imitation model of social tagging that integrates formal representations of semantics and a stochastic tag choice process to explain and predict emergent ...
Wai-Tat Fu, Thomas George Kannampallil, Ruogu Kang
In this paper, we propose a novel discriminative language model, which can be applied quite generally. Compared to the well known N-gram language models, discriminative language m...