Knowledge representation is essential for semantics modeling and intelligent information processing. For decades researchers have proposed many knowledge representation techniques...
This paper develops connections between objective Bayesian epistemology--which holds that the strengths of an agent's beliefs should be representable by probabilities, should...
Grid search and manual search are the most widely used strategies for hyper-parameter optimization. This paper shows empirically and theoretically that randomly chosen trials are ...
Many applications of natural language processing technologies involve analyzing texts that concern the psychological states and processes of people, including their beliefs, goals...
Andrew Gordon, Abe Kazemzadeh, Anish Nair, Milena ...
This paper demonstrates how unsupervised techniques can be used to learn models of deep linguistic structure. Determining the semantic roles of a verb's dependents is an impo...