This paper focuses on inductive invariants in unbounded model checking to improve efficiency and scalability. First of all, it introduces optimized techniques to speedup the comp...
We present a correlated bigram LSA approach for unsupervised LM adaptation for automatic speech recognition. The model is trained using efficient variational EM and smoothed using...
We present a new algorithm for probabilistic planning with no observability. Our algorithm, called Probabilistic-FF, extends the heuristic forward-search machinery of Conformant-F...
In this research, we investigate and address the challenges of asymmetry in High-End Computing (HEC) systems comprising heterogeneous architectures with varying I/O and computation...