Results 21 to 30 of about 204,288 (176)
Entropy, 2020 The meta-synthesis method has achieved good results in China’s aerospace engineering and population economic regulation. This theoretical achievement obtained from engineering practice becomes an effective way to solve complex decision-making problems ...
Lei Wang, Huifeng Xue
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Cross-Entropy Randomized Motion Planning [PDF]
, 2011 —This paper is concerned with motion planning for nonlinear robotic systems operating in constrained environments. Motivated by recent developments in sampling-based motion planning and Monte Carlo optimization we propose a general randomized path ...
Kobilarov, Marin
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An Alternative Cross Entropy Loss for Learning-to-Rank
, 2021 Listwise learning-to-rank methods form a powerful class of ranking algorithms that are widely adopted in applications such as information retrieval. These algorithms learn to rank a set of items by optimizing a loss that is a function of the entire set --
Bruch, Sebastian
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Active function Cross-Entropy Clustering
Expert Systems with Applications, 2017 Gaussian Mixture Models (GMM) have found many applications in density estimation and data clustering. However, the model does not adapt well to curved and strongly nonlinear data. Recently there appeared an improvement called AcaGMM (Active curve axis Gaussian Mixture Model), which fits Gaussians along curves using an EM-like (Expectation Maximization)
Spurek, Przemysław +2 more
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Learning from Knowledge Graphs: Neural Fine-Grained Entity Typing with Copy-Generation Networks
Entropy, 2022 Fine-grained entity typing (FET) aims to identify the semantic type of an entity in a plain text, which is a significant task for downstream natural language processing applications.
Zongjian Yu +5 more
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Marginal Likelihood Estimation with the Cross-Entropy Method [PDF]
, 2012 We consider an adaptive importance sampling approach to estimating the marginal likelihood, a quantity that is fundamental in Bayesian model comparison and Bayesian model averaging.
Chan, Joshua, Eisenstat, Eric
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Journal of Uncertainty Analysis and Applications, 2015 This paper deals with the divergence of fuzzy variables from a priori one. Within the framework of credibility theory, a fuzzy cross-entropy is defined to measure the divergence, and some mathematical properties are investigated. Furthermore, a minimum cross-entropy principle is proposed, which tells us that out of all membership functions satisfying ...
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Machine Learning-Inspired Hybrid Precoding for mmWave MU-MIMO Systems with Domestic Switch Network
Sensors, 2021 Hybrid precoding is an attractive technique in MU-MIMO systems with significantly reduced hardware costs. However, it still requires a complex analog network to connect the RF chains and antennas.
Xiang Li, Yang Huang, Wei Heng, Jing Wu
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CEoptim: Cross-Entropy R Package for Optimization
Journal of Statistical Software, 2017 The cross-entropy (CE) method is a simple and versatile technique for optimization, based on Kullback-Leibler (or cross-entropy) minimization. The method can be applied to a wide range of optimization tasks, including continuous, discrete, mixed and ...
Tim Benham +3 more
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The Role of Information in Managing Interactions from a Multifractal Perspective
Entropy, 2021 In the framework of the multifractal hydrodynamic model, the correlations informational entropy–cross-entropy manages attractive and repulsive interactions through a multifractal specific potential.
Maricel Agop +9 more
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