Deep Belief Networks (DBN's) are generative models that contain many layers of hidden variables. Efficient greedy algorithms for learning and approximate inference have allow...
We present a trainable sequential-inference technique for processes with large state and observation spaces and relational structure. Our method assumes "reliable observation...
Currently, there is an increasing effort to provide various personalized services on museum web sites. This paper presents an approach for determining user interests in a museum c...
Spoken Language Understanding aims at mapping a natural language spoken sentence into a semantic representation. In the last decade two main approaches have been pursued: generati...
Marco Dinarelli, Alessandro Moschitti, Giuseppe Ri...
The recent advances in hardware and software have enabled the capture of different measurements of data in a wide range of fields. These measurements are generated continuously an...
Mohamed Medhat Gaber, Arkady B. Zaslavsky, Shonali...