Abstract. In this paper, we consider the problem of filtering in relational hidden Markov models. We present a compact representation for such models and an associated logical par...
Luke S. Zettlemoyer, Hanna M. Pasula, Leslie Pack ...
We propose a new sequential, adaptive, quadratic-time algorithm for variable-rate lossy compression of memoryless sources at a fixed distortion. The algorithm uses approximate pat...
Abstract. Predictive analysis aims at detecting concurrency errors during runtime by monitoring a concrete execution trace of a concurrent program. In recent years, various models ...
Chao Wang, Sudipta Kundu, Malay K. Ganai, Aarti Gu...
Distributed Partially Observable Markov Decision Problems (Distributed POMDPs) are a popular approach for modeling multi-agent systems acting in uncertain domains. Given the signi...
Pradeep Varakantham, Janusz Marecki, Yuichi Yabu, ...
Although computers are widely used to simulate complex physical systems, crafting the underlying models that enable computer analysis remains difficult. When a model is created fo...