Results 91 to 100 of about 7,842 (187)
T‐calibration in semi‐parametric models
Canadian Journal of Statistics, Volume 54, Issue 1, March 2026.AbstractThis article relates the calibration of models to the consistent loss functions for the target functional of the model. Correctly specified models are calibrated. Conversely, we demonstrate that if there is a parameter value that is optimal under all consistent loss functions, then a model is calibrated.
Anja Mühlemann, Johanna Ziegel
wiley +1 more source
Convex Optimization via Symmetrical Hölder Divergence for a WLAN Indoor Positioning System
Entropy, 2018 Modern indoor positioning system services are important technologies that play vital roles in modern life, providing many services such as recruiting emergency healthcare providers and for security purposes.
Osamah Abdullah
doaj +1 more source
Interpretable Machine Learning: A Comprehensive Review of Foundations, Methods, and the Path Forward
WIREs Data Mining and Knowledge Discovery, Volume 16, Issue 1, March 2026.This systematic review of 352 studies establishes a comprehensive taxonomy for Interpretable Machine Learning, transitioning from foundational intrinsic models to advanced deep learning explanations. It reveals a critical paradigm shift toward “mechanistic interpretability” and actionable recourse, emphasizing that future AI systems must be rigorously ...
Shimon Fridkin, Michael Bendersky
wiley +1 more source
Entropy, 2015 A scoring rule is a device for evaluation of forecasts that are given in terms of the probability of an event. In this article we will restrict our attention to binary forecasts.
Gareth Hughes, Cairistiona F.E. Topp
doaj +1 more source
Clinical Transplantation, Volume 40, Issue 2, February 2026.ABSTRACT Introduction There are no effective therapeutic agents for preventing or treating delayed graft function (DGF) among deceased donor kidney transplant recipients (DDKTRs). Donor and recipient factors are important to predicting DGF and associated outcomes, which we hypothesize differed over time.
Camille C. Ylagan +7 more
wiley +1 more source
Statistical Analysis of Distance Estimators with Density Differences and Density Ratios
Entropy, 2014 Estimating a discrepancy between two probability distributions from samples is an important task in statistics and machine learning. There are mainly two classes of discrepancy measures: distance measures based on the density difference, such as the Lp ...
Takafumi Kanamori, Masashi Sugiyama
doaj +1 more source
General H-theorem and Entropies that Violate the Second Law
Entropy, 2014 H-theorem states that the entropy production is nonnegative and, therefore, the entropy of a closed system should monotonically change in time. In information processing, the entropy production is positive for random transformation of signals (the ...
Alexander N. Gorban
doaj +1 more source
Bregman-Divergence-Based Arimoto-Blahut Algorithm
IEEE Transactions on Information TheoryWe generalize the generalized Arimoto-Blahut algorithm to a general function defined over Bregman-divergence system. In existing methods, when linear constraints are imposed, each iteration needs to solve a convex minimization. Exploiting our obtained algorithm, we propose a minimization-free-iteration algorithm.
openaire +2 more sources
Entropy, 2017 An abstract, quantitative theory which connects elements of information —key ingredients in the cognitive proces—is developed. Seemingly unrelated results are thereby unified.
Flemming Topsøe
doaj +1 more source
Robustness Property of Robust-BD Wald-Type Test for Varying-Dimensional General Linear Models
Entropy, 2018 An important issue for robust inference is to examine the stability of the asymptotic level and power of the test statistic in the presence of contaminated data.
Xiao Guo, Chunming Zhang
doaj +1 more source