Extractive summarization techniques cannot generate document summaries shorter than a single sentence, something that is often required. An ideal summarization system would unders...
Michele Banko, Vibhu O. Mittal, Michael J. Witbroc...
Precision achieved by stochastic sampling algorithms for Bayesian networks typically deteriorates in face of extremely unlikely evidence. To address this problem, we propose the E...
: Recurrent neural networks possess interesting universal approximation capabilities, making them good candidates for time series modeling. Unfortunately, long term dependencies ar...
Prioritized sweeping is a model-based reinforcement learning method that attempts to focus an agent’s limited computational resources to achieve a good estimate of the value of ...
This paper introduces a partition of the possible forms of knowledge according to their rela tionship to the basic objective of an intelligent agent, namely to act successfully ...