Identifying maternal and paternal inheritance is essential to be able to find the set of genes responsible for a particular disease. Although we have access to genotype data (gene...
Classification is one of the most fundamental problems in machine learning, which aims to separate the data from different classes as far away as possible. A common way to get a g...
Bin Zhang, Fei Wang, Ta-Hsin Li, Wen Jun Yin, Jin ...
Compilation is an important approach to a range of inference problems, since it enables linear-time inference in the size S of the compiled representation. However, the main drawb...
This paper studies commitments in multiagent systems. A dialectical commitment corresponds to an agent taking a position about a putative fact, including for the sake of argument....
Markov logic networks (MLNs) combine first-order logic and Markov networks, allowing us to handle the complexity and uncertainty of real-world problems in a single consistent fram...
An unsupervised probabilistic learning framework for normalizing product records across different retailer Web sites is presented. Our framework decomposes the problem into two ta...
Answering conjunctive queries (CQs) has been recognized as a key task for the usage of Description Logics (DLs) in a number of applications, and has thus been studied by many auth...
Recent advances in classical planning have used the SAS+ formalism, and several effective heuristics have been developed based on the SAS+ formalism. Comparing to the traditional ...