We are studying long term sequence prediction (forecasting). We approach this by investigating criteria for choosing a compact useful state representation. The state is supposed t...
We provide a novel view of learning an approximate model of a partially observable environment from data and present a simple implemenf the idea. The learned model abstracts away ...
Abstract. The key for providing a robust context for personalized information retrieval is to build a library which gathers the long term and the short term user’s interests and ...
Predictive state representations (PSRs) have recently been proposed as an alternative to partially observable Markov decision processes (POMDPs) for representing the state of a dy...
Matthew Rosencrantz, Geoffrey J. Gordon, Sebastian...
With the increased use of the web has come a corresponding increase in information overload that users face when trying to locate specific webpages, especially as a majority of vi...