Probabilistic model building methods can render difficult problems feasible by identifying and exploiting dependencies. They build a probabilistic model from the statistical prope...
This paper describes an approach to detect the entrance of building with hopeful that it will be applied for autonomous navigation robot. The entrance is an important component whi...
Suk-Ju Kang, Hoang-Hon Trinh, Dae-Nyeon Kim, Kang-...
There is evidence that the numbers in probabilistic inference don't really matter. This paper considers the idea that we can make a probabilistic model simpler by making fewe...
Our aim in this paper is to identify genreindependent factors that influence the decision to pronominalize. Results based on the annotation of twelve texts from four genres show t...
Muhiagent systems (MAS) can "go down" for a large number of reasons, ranging from system malfunctions and power failures to malicious attacks. The placement of agents on...
In this paper we propose a probabilistic model for online document clustering. We use non-parametric Dirichlet process prior to model the growing number of clusters, and use a pri...
We propose a general method for reranker construction which targets choosing the candidate with the least expected loss, rather than the most probable candidate. Different approac...
This paper describes an extremely lexicalized probabilistic model for fast and accurate HPSG parsing. In this model, the probabilities of parse trees are defined with only the pro...
Traditional noun phrase coreference resolution systems represent features only of pairs of noun phrases. In this paper, we propose a machine learning method that enables features ...
In this paper, we describe a new algorithm for recovering WH-trace empty nodes. Our approach combines a set of hand-written patterns together with a probabilistic model. Because t...