This paper describes and analyzes sporadic model building, which can be used to enhance the efficiency of the hierarchical Bayesian optimization algorithm (hBOA) and other advance...
We present a Bayesian framework for learning higherorder transition models in video surveillance networks. Such higher-order models describe object movement between cameras in the...
An open problem in Simultaneous Localization and Mapping (SLAM) is the development of algorithms which scale with the size of the environment. A few promising methods exploit the ...
Recommender systems are an important component of many websites. Two of the most popular approaches are based on matrix factorization (MF) and Markov chains (MC). MF methods learn...
Steffen Rendle, Christoph Freudenthaler, Lars Schm...
Solomonoff unified Occam’s razor and Epicurus’ principle of multiple explanations to one elegant, formal, universal theory of inductive inference, which initiated the field...