312 citations · 649 across the 29 of their papers we have counts for
5 papers · 1 filter
Budgeted Learning of Naive-Bayes Classifiers
Daniel J. Lizotte, Omid Madani, Russell Greiner
Frequently, acquiring training data has an associated cost. We consider the situation where the learner may purchase data during training, subject TO a budget. IN particular, we ex…
Active Model Selection
Omid Madani, Daniel J. Lizotte, Russell Greiner
Classical learning assumes the learner is given a labeled data sample, from which it learns a model. The field of Active Learning deals with the situation where the learner begins…
A Generalized Loop Correction Method for Approximate Inference in Graphical Models
Siamak Ravanbakhsh, Chun-Nam Yu, Russell Greiner
Belief Propagation (BP) is one of the most popular methods for inference in probabilistic graphical models. BP is guaranteed to return the correct answer for tree structures, but c…
Speeding Up Planning in Markov Decision Processes via Automatically Constructed Abstractions
Alejandro Isaza, Csaba Szepesvari, Vadim Bulitko +1
In this paper, we consider planning in stochastic shortest path (SSP) problems, a subclass of Markov Decision Problems (MDP). We focus on medium-size problems whose state space can…
Improved Mean and Variance Approximations for Belief Net Responses via Network Doubling
Peter Hooper, Yasin Abbasi-Yadkori, Russell Greiner +1
A Bayesian belief network models a joint distribution with an directed acyclic graph representing dependencies among variables and network parameters characterizing conditional dis…