Titlebook: Rules and Reasoning; 4th International Jo Víctor Gutiérrez-Basulto,Tomáš Kliegr,Dumitru Roma Conference proceedings 2020 Springer Nature Sw

Ordnance

ation, finances, and personnel of the ecclesiastical hierarchy. The influence of the king over the church in this restricted sense (which will remain its sense throughout this chapter) had already been considerable even before the break with Rome. The king had wide powers of patronage within the chu

Generosity

Luigi Bellomarini,Eleonora Laurenza,Emanuel Sallinger,Evgeny Sherkhonovation, finances, and personnel of the ecclesiastical hierarchy. The influence of the king over the church in this restricted sense (which will remain its sense throughout this chapter) had already been considerable even before the break with Rome. The king had wide powers of patronage within the chu

无能的人

Arash Karimi,Jia-Huai Younteel enfeeblement here. The king had a disease. Its symptoms were obvious and distasteful, copied carefully by Elizabeth Moss in her make-up scheme from illustrations in a medical book. In Part 2, Jon Finch’s face was progressively invaded by a scarlet and yellow crust around his mouth, nose and ch

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Juliana K. F. Bowles,Agastya Silvina,Eyal Bin,Michael Vinov been followed, over the past ten years, by an explosion of interest in how these viruses replicate, maintain chronic infections, and cause liver disease and hepatocellular carcinoma. The purpose of this book is two-fold. First, the authors of each chapter provide a summary of their specialty that w

harmony

Guido Governatori,Pompeu Casanovas Romeu,Louis de Kokerrtilage and other connective tissues. Their high histological and genetic heterogeneity makes diagnosis and treatment very challenging. Deregulation of heparanase has been found in several sarcoma subtypes and high expression levels have been correlated with poor prognosis in Ewing’s sarcoma and ost

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diabetes

insidious

Rule-Based Multi-label Classification: Challenges and Opportunitiesexible way, and the facile customization of a predictor to different loss functions. In this paper, we present a modular framework for rule-based MLC and discuss related challenges and opportunities for multi-label rule learning.