Probabilistic inference was shown effective in non-deterministic diagnosis of end-to-end service failures. Since exact probabilistic diagnosis is known to be an NP-hard problem, a...
—We consider the problem of inferring and modeling topics in a sequence of documents with known publication dates. The documents at a given time are each characterized by a topic...
Iulian Pruteanu-Malinici, Lu Ren, John William Pai...
The Conditional Restricted Boltzmann Machine (CRBM) is a recently proposed model for time series that has a rich, distributed hidden state and permits simple, exact inference. We ...
We describe a method to axiomatize computations in deterministic Turing machines (TMs). When applied to computations in non-deterministic TMs, this method may produce contradictor...
The acceleration of acoustic likelihood calculation has been an important research issue for developing practical speech recognition systems. And there are various specification ...