In many structured prediction problems, the highest-scoring labeling is hard to compute exactly, leading to the use of approximate inference methods. However, when inference is us...
Semi-supervised inductive learning concerns how to learn a decision rule from a data set containing both labeled and unlabeled data. Several boosting algorithms have been extended...
In this paper we formulate a novel AND/OR graph representation capable of describing the different configurations of deformable articulated objects such as horses. The representa...
Yuanhao Chen, Long Zhu, Chenxi Lin, Alan L. Yuille...
Stimulus selectivity of sensory neurons is often characterized by estimating their receptive field properties such as orientation selectivity. Receptive fields are usually deriv...
It is becoming increasingly evident that organisms acting in uncertain dynamical environments often employ exact or approximate Bayesian statistical calculations in order to conti...
Omer Bobrowski, Ron Meir, Shy Shoham, Yonina C. El...
Markov jump processes play an important role in a large number of application domains. However, realistic systems are analytically intractable and they have traditionally been ana...
Extensive games are a powerful model of multiagent decision-making scenarios with incomplete information. Finding a Nash equilibrium for very large instances of these games has re...
Martin Zinkevich, Michael Johanson, Michael H. Bow...
We extend the Bayesian skill rating system TrueSkill to infer entire time series of skills of players by smoothing through time instead of filtering. The skill of each participat...
Pierre Dangauthier, Ralf Herbrich, Tom Minka, Thor...