European Union Accession to the European Convention on Human Rights: An Institutional “Marriage”

A possible accession of European Union (hereinafter: EU/the Union) to the European Convention on Human Rights (ECHR/the Convention) has been discussed in legal society for more than thirty years. The topic had widely opened after the 1979 Commission Memorandum where the major pros and cons were underlined and practical problems were addressed. This discussion led to an official request to the European Court of Justice (ECJ/the Court) in relation to the legality of such accession; the outcome was included in opinion 2/94 that found such accession incompatible with the European Community (EC/the Community) Treaty. © Konstantinos G. Margaritis. All rights reserved. This paper may be freely circulated in electronic or hard copy provided it is not modified in any way, the rights of the author not infringed, and the paper is not quoted or cited without express permission of the author. The editors cannot guarantee a stable URL for any paper posted here, nor will they be responsible for notifying others if the URL is changed or the paper is taken off the site. Electronic copies of this paper may not be posted on any other website without express permission of the author

An Optimal Scaling Approach to Collaborative Filtering using Categorical Principal Component Analysis and Neighborhood Formation

Abstract. Collaborative Filtering (CF) is a popular technique employed by Recommender Systems, a term used to describe intelligent methods that generate personalized recommendations. The most common and accurate approaches to CF are based on latent factor models. Latent factor models can tackle two fundamental problems of CF, data sparsity and scalability and have received considerable attention in recent literature. In this work, we present an optimal scaling approach to address both of these problems using Categorical Principal Component Analysis for the low-rank approximation of the user-item ratings matrix, followed by a neighborhood formation step. The optimal scaling approach has the advantage that it can be easily extended to the case when there are missing data and restrictions for ordinal and numerical variables can be easily imposed. We considered different measurement levels for the user ratings on items, starting with a multiple nominal and consecutively applying nominal, ordinal and numeric levels. Experiments were executed on the MovieLens dataset, aiming to evaluate the aforementioned options in terms of accuracy. Results indicated that a combined approach (multiple nominal measurement level, "passive" missing data strategy) clearly outperformed the other tested options

A study of systolic algorithms for VLSI processor arrays and optical computing

This thesis presents some new systolic algorithms for numerical computation, that are suitable for implementation on VLSI processor arrays or optical processors. [Continues.

The Charter of Fundamental Rights of the European Union: The First Ten Years-New Challenges and Perspectives

Since 1 December 2009, the time when the Treaty of Lisbon came into force, the Charter of Fundamental Rights of the European Union (hereinafter: the EU Charter, the Charter) has been formally included in the EU legal order as primary EU law [...

Unison-CF: a multiple-component, adaptive collaborative filtering system

Abstract. In this paper we present the Unison-CF algorithm, which provides an efficient way to combine multiple collaborative filtering approaches, drawing advantages from each one of them. Each collaborative filtering approach is treated as a separate component, allowing the Unison-CF algorithm to be easily extended. We evaluate the Unison-CF algorithm by applying it on three existing filtering approaches: User-based Filtering, Item-based Filtering and Hybrid-CF. Adaptation is utilized and evaluated as part of the filtering approaches combination. Our experiments show that the Unison-CF algorithm generates promising results in improving the accuracy and coverage of the existing filtering algorithms

Hands-on ensemble learning with Python: build highly optimized ensemble machine learning models using scikit-learn and Keras

Ensemble learning can provide the necessary methods to improve the accuracy and performance of existing models. In this book, you'll understand how to combine different machine learning algorithms to produce more accurate results from your models