Many artificial intelligence techniques rely on the notion ate" as an abstraction of the actual state of the nd an "operator" as an abstraction of the actions that ...
Abstract: Structure learning of dynamic Bayesian networks provide a principled mechanism for identifying conditional dependencies in time-series data. This learning procedure assum...
We present an extension to the Lasso [9] for binary classification problems with ordered attributes. Inspired by the Fused Lasso [8] and the Group Lasso [10, 4] models, we aim to...
Boolean Satisfiability is a ubiquitous modeling tool in Electronic Design Automation, It finds application in test pattern generation, delay-fault testing, combinational equivalen...
In this paper, we propose a Quantified Distributed Constraint Optimization problem (QDCOP) that extends the framework of Distributed Constraint Optimization problems (DCOPs). DCOP...