Evaluating a policy by deploying it in the real world can be risky and costly. Off-policy evaluation (OPE) algorithms use historical data collected from running a previous policy to evaluate a new policy, which provides a means for evaluating a policy without requiring it to ever be deployed. Importance sampling is a popular OPE method because it is robust to partial observability and works wit...

The paper introduces AND/OR importance sampling for probabilistic graphical models. In contrast to importance sampling, AND/OR importance sampling caches samples in the AND/OR space and then extracts a new sample mean from the stored samples. We prove that AND/OR importance sampling may have lower variance than importance sampling; thereby providing a theoretical justification for preferring it...

This paper describes a discrete-time retrial queue and shows how importance sampling simulations can be applied for estimating the probability of large orbit content and the overflow fraction of primary calls.

We propose a method for sequential Bayesian kernel regression. As is the case for the popular Relevance Vector Machine (RVM) [10, 11], the method automatically identifies the number and locations of the kernels. Our algorithm overcomes some of the computational difficulties related to batch methods for kernel regression. It is non-iterative, and requires only a single pass over the data. It is ...

In this paper we extend previously proposed state-dependent importance sampling heuristics for simulation of population overflow in Markovian tandem queuing networks to nonMarkovian tandem networks, and experimentally demonstrate the asymptotic efficiency of the resulting heuristics.

In this paper, we propose a particle filtering approach for tracking applications in image sequences. The system we propose combines a measurement equation and a dynamic equation which both depend on the image sequence. Taking into account several possible observations, the likelihood is modeled as a linear combination of Gaussian laws. Such a model allows inferring an analytic expression of th...

Weight is conceptualized as an embodiment of importance, according to recent research on embodied cognition (Ackerman, Nocera, & Bargh, 2010; Jostmann, Lakens, & Schubert, 2009). Is importance as embodied by weight used as a cue that items are memorable? Four experiments varied participants' perceptual experiences of weight as they studied words and predicted later memory performance via judgme...

Overconcern with weight and shape and body dissatisfaction have both emerged as significant predictors of disordered eating. However, it is unclear how these constructs relate to each other, and if each has different antecedents and consequences. This study aimed to identify prospective predictors of each construct and to determine their relative importance in predicting dietary restraint and b...