Related papers: Implementation, Compilation, Optimization of Objec…

Model Transformations in Practice (MTiP) 2005 was a workshop which provided a forum for the model transformation community to discuss practical model transformation issues. Although many different model transformation approaches have been…

Context: Machine Learning Operations (MLOps) has emerged as a set of practices that combines development, testing, and operations to deploy and maintain machine learning applications. Objective: In this paper, we assess the benefits and…

The Eleventh Workshop on Logic Programming Environments (WLPE'01) was one in a series of international workshops in the topic area. It was held on December 1, 2001 in Paphos, Cyprus as a post-conference workshop at ICLP 2001. Eight refereed…

Modern hardware platforms, from the very small to the very large, increasingly provide parallel and distributed computing resources for applications to maximise performance. Many applications therefore need to make effective use of tens,…

MLOps tools enable continuous development of machine learning, following the DevOps process. Different MLOps tools have been presented on the market, however, such a number of tools often create confusion on the most appropriate tool to be…

PLACES 2015 (full title: Programming Language Approaches to Concurrency- and Communication-Centric Software) is the eighth edition of the PLACES workshop series. After the first PLACES, which was affiliated to DisCoTec in 2008, the workshop…

Multiobjective optimization is a hot topic in the artificial intelligence and operations research communities. The design and development of multiobjective methods is a frequent task for researchers and practitioners. As a result of this…

This is the list of the full papers accepted for presentation at the 32nd International Conference on Logic Programming, New York City, USA, October 18-21, 2016. In addition to the main conference itself, ICLP hosted four pre-conference…

Applying DevOps practices to machine learning system is termed as MLOps and machine learning systems evolve on new data unlike traditional systems on requirements. The objective of MLOps is to establish a connection between different…

Computation nowadays is becoming inherently concurrent, either because of characteristics of the hardware (with multicore processors becoming omnipresent) or due to the ubiquitous presence of distributed systems (incarnated in the…

The aim of the workshop was to bring together experts working on open-domain dialogue research. In this speedily advancing research area many challenges still exist, such as learning information from conversations, and engaging in a…

Welcome to the proceedings of FOCLASA 2012, the 11th International Workshop on the Foundations of Coordination Languages and Self-Adaptation. FOCLASA 2012 was held in Newcastle upon Tyne, UK, on September 8, 2012 as a satellite event of…

Optimization modeling underlies critical decision-making across industries, yet remains difficult to automate: natural-language problem descriptions must be translated into precise mathematical formulations and executable solver code.…

In the Hydro project we are designing a compiler toolkit that can optimize for the concerns of distributed systems, including scale-up and scale-down, availability, and consistency of outcomes across replicas. This invited paper overviews…

This volume contains the papers presented at WLPE'06: the 16th Workshop on Logic-based Methods in Programming Environments held on August 16, 2006 in the Seattle Sheraton Hotel and Towers, Seattle, Washington (USA). It was organised as a…

This volume contains the proceedings of the Combined 21st International Workshop on Expressiveness in Concurrency and the 11th Workshop on Structural Operational Semantics (EXPRESS/SOS 2014) which was held on 1st September 2014 in Rome,…

An empirical study was conducted to analyse design strategies and knowledge used in object-oriented software design. Eight professional programmers experienced with procedural programming languages and either experienced or not experienced…

This paper presents El0ps, a Python toolbox providing several utilities to handle L0-regularized problems related to applications in machine learning, statistics, and signal processing, among other fields. In contrast to existing toolboxes,…

This paper is an overview of the Machine Learning Operations (MLOps) area. Our aim is to define the operation and the components of such systems by highlighting the current problems and trends. In this context, we present the different…

The accelerated adoption of AI-based software demands precise development guidelines to guarantee reliability, scalability, and ethical compliance. MLOps (Machine Learning and Operations) guidelines have emerged as the principal reference…