This paper describes our approaches to raise the level of abstraction at which hardware suitable for accelerating computationally-intensive applications can be specified. Field-Pr...
Qiang Liu, George A. Constantinides, Konstantinos ...
A wide range of evidence points to a preference for syntactic structures in which dependencies are short. Here we examine the question: what kinds of dependency configurations min...
In this paper we consider uncountable classes recognizable by ω-automata and investigate suitable learning paradigms for them. In particular, the counterparts of explanatory, vac...
Sanjay Jain, Qinglong Luo, Pavel Semukhin, Frank S...
We present an algorithm that derives actions' effects and preconditions in partially observable, relational domains. Our algorithm has two unique features: an expressive rela...
Abstract. In this paper we introduce BioPubMiner, a machine learning component-based platform for biomedical information analysis. BioPubMiner employs natural language processing t...