Pattern Recognition
Recommending questions using the mdl-based tree cut model
Proceedings of the 17th international conference on World Wide Web
A comparative study of model selection criteria for computer vision applications
Image and Vision Computing
Parametric model-based motion segmentation using surface selection criterion
Computer Vision and Image Understanding
Nonlinear system identification via Laguerre network based fuzzy systems
Fuzzy Sets and Systems
Wavelet denoising with evolutionary algorithms
Digital Signal Processing
Scalable diagnosis in IP networks using path-based measurement and inference: A learning framework
Journal of Visual Communication and Image Representation
Context-based embedded image compression using binary wavelet transform
Image and Vision Computing
Computers in Biology and Medicine
Lossless geometry compression for steady-state and time-varying irregular grids
EUROVIS'06 Proceedings of the Eighth Joint Eurographics / IEEE VGTC conference on Visualization
Search for sparse active inputs: a review
Information Theory, Combinatorics, and Search Theory
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A connection between universal codes and the problems of prediction and statistical estimation is established. A known lower bound for the mean length of universal codes is sharpened and generalized, and optimum universal codes constructed. The bound is defined to give the information in strings relative to the considered class of processes. The earlier derived minimum description length criterion for estimation of parameters, including their number, is given a fundamental information, theoretic justification by showing that its estimators achieve the information in the strings. It is also shown that one cannot do prediction in Gaussian autoregressive moving average (ARMA) processes below a bound, which is determined by the information in the data.