Titlebook: Integrated Uncertainty in Knowledge Modelling and Decision Making; 6th International Sy Van-Nam Huynh,Masahiro Inuiguchi,Thierry Denoeux Co

終端

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Do It Today or Do It Tomorrow: Empirical Non-exponential Discounting Explained by Symmetry Ideas long-term consequences will be disastrous. In real life, few people behave like that, since the actual empirical discounting function is different: it is hyperbolic .. In this paper, we use symmetry ideas to explain this empirical phenomenon.

通便

fMKL-DR: A Fast Multiple Kernel Learning Framework with Dimensionality Reductionion. To reach this conclusion, we performed several comparative evaluations on various biomedical data sets. The results demonstrate that, compared to previous work, the fMKL-DR remarkably improves computational cost. Therefore, the proposed framework is beneficial to the manipulation and integration of huge and complex datasets.

上釉彩

laxative

An Evidence Theoretic Approach to Interval Analytic Hierarchy Processate the problem estimating a BPA from a given pairwise comparison matrix as a linear programming problem. We investigate the relation between the proposed approach and the interval AHP. We show that the formulated BPA estimation problem is equivalent to the problem of estimating a normalized interval weight vector with an additional constraint.

PAD416

A New Context-Based Similarity Measure for Categorical Data Using Information Theoryrmation into the quantification of similarity between categorical data. The evaluation experiment conducted on classification task shows that the effectiveness of our proposed measure is competitive with other current state-of-the-art similarity measures.

Germinate

An Attention-Based Long-Short-Term-Memory Model for Paraphrase GenerationTM) neural network for forming an end-to-end paraphrase generation model. Extensive experiments on the two most popular corpora (. and .) show that our proposed model’s performance is better than the state-of-the-art models for paragraph generation problem.

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巫婆

Linguistic Summarization Based on the Inherent Semantics of Linguistic Wordsthis LFoCs that can preserve order-based semantics relation and generality-specificity relation of words. Theoretically, the number of words in LFoC are not limited. A simulation study using dataset Iris shows that the proposed method can extract sentences using words of length 3 characterizing dataset Iris that other existing ones cannot do.

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