Cross Entropy
Cross Entropy and Linguistic Typology
... It is easier and more accurate to measure cross-entropy in this way, is sensitive to the sublan- guage of the samples used and hence can be used for smaller-scale experiments, and is sen[r] ...
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Some Order Preserving Inequalities for Cross Entropy and Kullback–Leibler Divergence
... Cross entropy and Kullback–Leibler (K-L) divergence are applied to and discussed in studies on machine learning [1], visualization ...fields. Cross entropy and K-L divergence are two ...
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Language Model Weight Adaptation Based on Cross-entropy for Statistical Machine Translation
... In this paper, different from (Li et al., 2010), we focus on the adaptation of LM weight only, as LM is one of the key components of SMT and has its own characteristic. In our work, we adopt cross-entropy ...
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A Cross Entropy Genetic Algorithm for m Machines No Wait Job ShopScheduling Problem
... differently, cross entropy (CE) is inspired by a concept of modern information theory namely the concept of Kullback-Leibler distance, also well-known with the same name: the concept of cross ...
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Cross entropy as a measure of musical contrast
... In a similar vein, Marsden [5] has questioned whether musical similarity is a definitive phenomenon or a product of interpretation. He reviews a number of approaches: the edit distance between melodies, possibly under ...
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Dual Monolingual Cross Entropy Delta Filtering of Noisy Parallel Data
... We introduce a purely monolingual approach to filtering for parallel data from a noisy cor- pus in a low-resource scenario. Our work is inspired by Junczys-Dowmunt (2018), but we relax the requirements to allow for cases ...
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Extensions of the Cross-Entropy Method with Applications to Diffusion Processes and Portfolio Losses
... The cross-entropy methodology is a well-established method to determine how sim- ilar two measures are (see Asmussen and Glynn (2007) and references therein for a comprehensive treatment of the ...the ...
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NC-Cross Entropy Based MADM under Neutrosophic Cubic Set Environment
... Single valued neutrosophic cross-entropy for multi criteria decision making problems. Improved cross entropy measures of single valued neutrosophic sets and interval neutrosophic 633[r] ...
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Dual Conditional Cross-Entropy Filtering of Noisy Parallel Corpora
... conditional cross-entropy filtering for noisy parallel ...compute cross-entropy scores accord- ing to two inverse translation models trained on clean ...divergent cross- entropies and ...
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Global Regularizer and Temporal aware Cross entropy for Skeleton based Early Action Recognition
... Abstract. In this paper, we propose a new approach to recognize the class label of an action before this action is fully performed based on skeleton sequences. Compared to action recognition which uses fully ob- served ...
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Classification of Music Genre using Neural Networks with Cross-Entropy Optimization and Soft-Max Output
... In this paper, an abstract model to predict the genre of a music audio file is proposed (specifically a wave file).The output of the model is the probability distribution along the considered genres. A machine learning ...
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Monotonic Estimation for Probability Distribution and Multivariate Risk Scales by Constrained Minimum Generalized Cross Entropy
... subject to (1.4) and (1.5) is a special case of minimizing (1.6) for 𝐺𝐶𝐸 subject to (1.4) and (1.7). Main results. We show in this paper that for a given sample 𝑆 = {(𝑦 𝑖1 ,𝑦 𝑖2 , … , 𝑦 𝑖𝑘 )} 𝑖=1 𝑛 , where 𝑦 𝑖𝑗 ≥ 0 for 1 ...
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Diversity Promoting GAN: A Cross Entropy Based Generative Adversarial Network for Diversified Text Generation
... Instead of using a classifier, we propose a novel language-model based discriminator and use the output of the language model, cross-entropy, as the reward.. The main advantage of our mo[r] ...
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Introduce a Novel PCA Method for Intuitionistic Fuzzy Sets Based on Cross Entropy
... In this paper, a new method for Principal Component Analysis in intuitionistic fuzzy situations has been proposed. This approach is based on cross entropy as an information index. This new me- thod is a ...
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Mutual Information and Cross Entropy Framework to Determine Relevant Gene Subset for Cancer Classification
... Classification of microarray datasets has drawn attention of research community in last few years. Microarray datasets are characterized by high dimension and small sample size. To avoid curse of dimensionality good gene ...
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An Affect-Rich Neural Conversational Model with Biased Attention and Weighted Cross-Entropy Loss
... In this paper, we propose an end-to-end open-domain neu- ral conversational model that produces affect-rich responses without performance degradation in language fluency. Our model leverages external word-VAD knowledge ...
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Considerations on Applying Cross Entropy Methods to the Vehicle Routing Problem
... The cross entropy method (CEM) derives its name from the cross-entropy (or Kullback-Leiber) distance and was motivated by an adaptive algorithm for estimating probabilities of rare events in ...
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Cross Entropy and Estimation of Probabilistic Context Free Grammars
... We investigate the problem of training probabilistic context-free grammars on the basis of a distribution defined over an infinite set of trees, by minimizing the cross-entropy. This problem can be seen as ...
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The Cross-Entropy Method for Policy Search in Decentralized POMDPs
... the Cross-Entropy (CE) method, a recently introduced method for combinatorial optimization, to Dec-POMDPs, resulting in a randomized (sampling-based) algorithm for approximately solving ...
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Deconstructing cross-entropy for probabilistic binary classifiers
... Another contribution of this article is the decomposition of cross-entropy into its discrimination and calibration components. Not only can this significantly help system designers to focus on the right ...
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