Hierarchical clustering methods are widely used in various scientific domains such as molecular biology, medicine, economy, etc. Despite the maturity of the research field of hie...
Abstract. Empirical hardness models are a recent approach for studying NP-hard problems. They predict the runtime of an instance using efficiently computable features. Previous res...
We propose a backoff model for phrasebased machine translation that translates unseen word forms in foreign-language text by hierarchical morphological abstractions at the word an...
E-business workloads are quite complex as demonstrated by the hierarchical workload characterization discussed here. While these features may pose challenges to performance model ...
This paper addresses agents' intentions as building blocks of imitation learning that abstract local situations of the agent, and proposes a hierarchical hidden Markov model ...