We explore a new Bayesian model for probabilistic grammars, a family of distributions over discrete structures that includes hidden Markov models and probabilistic context-free gr...
Background: Identifying candidate genes in genetic networks is important for understanding regulation and biological function. Large gene expression datasets contain relevant info...
Anup Parikh, Eryong Huang, Christopher Dinh, Blaz ...
We present a new approach to learning a semantic parser (a system that maps natural language sentences into logical form). Unlike previous methods, it exploits an existing syntact...
High compression of plant geometry is an important aspect in fast realistic visualization of plants. Hierarchical structuring plant morphology is a key factor for real time plant r...
The dependency pairs method is one of the most powerful technique for proving termination of rewriting and it is currently central in most automatic termination provers. Recently,...