We consider a planning problem where the dynamics and rewards of the environment
depend on a hidden static parameter referred to as the context. The objective is to learn a …

Abstract In February 2012, the Obama White House endorsed a Privacy Bill of Rights,
comprising seven principles. The third,“Respect for Context,” is explained as the expectation …

Simulated user retrieval system interactions enable studies with controlled user behavior. To
this end, the SimIIR framework offers static, rule-based methods. We present an extended …

Businesses in high-risk environments have been reluctant to adopt modern machine
learning approaches due to their complex and uninterpretable nature. Most current solutions …

Sorption-enhanced reverse water–gas shift (SE-RWGS, here designated as 'COMAX') was
studied with bifunctional reactive sorbents. First proof-of-concept is presented of the …

Recommender systems take inputs from user history, use an internal ranking algorithm to
generate results and possibly optimize this ranking based on feedback. However, often the …

For more than a century, Markov chain models have had a tremendous effect on research
and industry alike in various domains such as physics, chemistry, biology, and computer …

Discrete Markov chains are frequently used to analyse transition behaviour in sequential
data. Here, the transition probabilities can be estimated using varying order Markov chains …

In this work we address the development of a smart personal assistant that is capable of
anticipating a user's information needs based on a novel type of context: the person's activity …

The iPhone was introduced only a decade ago in 2007 but has fundamentally changed the
way we interact with online information. Mobile devices differ radically from classic …