Research over the past several decades in learning logical and probabilistic models has greatly increased the range of phenomena that machine learning can address. Recent work has ...
We present a new methodology to automate decision making over time and uncertainty. We adopt a knowledge-based model construction approach to support automated and interactive form...
A new language and inference algorithm for stochastic modeling is presented. This work refines and generalizes the stochastic functional language originally proposed by [1]. The l...
Abstract Read-write locking is an important mechanism to improve concurrent granularity, but it is difficult to reason about the safety of concurrent programs with read-write locks...
Most real-world data is heterogeneous and richly interconnected. Examples include the Web, hypertext, bibliometric data and social networks. In contrast, most statistical learning...