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Machine Learning and Knowledge Discovery in Databases
  • Language: en
  • Pages: 770

Machine Learning and Knowledge Discovery in Databases

The 5-volume proceedings, LNAI 12457 until 12461 constitutes the refereed proceedings of the European Conference on Machine Learning and Knowledge Discovery in Databases, ECML PKDD 2020, which was held during September 14-18, 2020. The conference was planned to take place in Ghent, Belgium, but had to change to an online format due to the COVID-19 pandemic. The 232 full papers and 10 demo papers presented in this volume were carefully reviewed and selected for inclusion in the proceedings. The volumes are organized in topical sections as follows: Part I: Pattern Mining; clustering; privacy and fairness; (social) network analysis and computational social science; dimensionality reduction and ...

Machine Learning and Knowledge Discovery in Databases. Applied Data Science Track
  • Language: en
  • Pages: 542

Machine Learning and Knowledge Discovery in Databases. Applied Data Science Track

The multi-volume set LNAI 12975 until 12979 constitutes the refereed proceedings of the European Conference on Machine Learning and Knowledge Discovery in Databases, ECML PKDD 2021, which was held during September 13-17, 2021. The conference was originally planned to take place in Bilbao, Spain, but changed to an online event due to the COVID-19 pandemic. The 210 full papers presented in these proceedings were carefully reviewed and selected from a total of 869 submissions. The volumes are organized in topical sections as follows: Research Track: Part I: Online learning; reinforcement learning; time series, streams, and sequence models; transfer and multi-task learning; semi-supervised and f...

Applied Machine Learning Using mlr3 in R
  • Language: en
  • Pages: 385

Applied Machine Learning Using mlr3 in R

  • Type: Book
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  • Published: 2024-01-18
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  • Publisher: CRC Press

mlr3 is an award-winning ecosystem of R packages that have been developed to enable state-of-the-art machine learning capabilities in R. Applied Machine Learning Using mlr3 in R gives an overview of flexible and robust machine learning methods, with an emphasis on how to implement them using mlr3 in R. It covers various key topics, including basic machine learning tasks, such as building and evaluating a predictive model; hyperparameter tuning of machine learning approaches to obtain peak performance; building machine learning pipelines that perform complex operations such as pre-processing followed by modelling followed by aggregation of predictions; and extending the mlr3 ecosystem with cu...

Machine Learning and Knowledge Discovery in Databases. Research Track
  • Language: en
  • Pages: 857

Machine Learning and Knowledge Discovery in Databases. Research Track

The multi-volume set LNAI 12975 until 12979 constitutes the refereed proceedings of the European Conference on Machine Learning and Knowledge Discovery in Databases, ECML PKDD 2021, which was held during September 13-17, 2021. The conference was originally planned to take place in Bilbao, Spain, but changed to an online event due to the COVID-19 pandemic. The 210 full papers presented in these proceedings were carefully reviewed and selected from a total of 869 submissions. The volumes are organized in topical sections as follows: Research Track: Part I: Online learning; reinforcement learning; time series, streams, and sequence models; transfer and multi-task learning; semi-supervised and f...

Computational Social Science
  • Language: en
  • Pages: 339

Computational Social Science

This book provides an overview of cutting-edge approaches to computational social science.

Machine Learning and Knowledge Discovery in Databases: Research Track
  • Language: en
  • Pages: 506

Machine Learning and Knowledge Discovery in Databases: Research Track

The multi-volume set LNAI 14169 until 14175 constitutes the refereed proceedings of the European Conference on Machine Learning and Knowledge Discovery in Databases, ECML PKDD 2023, which took place in Turin, Italy, in September 2023. The 196 papers were selected from the 829 submissions for the Research Track, and 58 papers were selected from the 239 submissions for the Applied Data Science Track. The volumes are organized in topical sections as follows: Part I: Active Learning; Adversarial Machine Learning; Anomaly Detection; Applications; Bayesian Methods; Causality; Clustering. Part II: ​Computer Vision; Deep Learning; Fairness; Federated Learning; Few-shot learning; Generative Models;...

Algorithms for the People
  • Language: en
  • Pages: 320

Algorithms for the People

How to put democracy at the heart of AI governance Artificial intelligence and machine learning are reshaping our world. Police forces use them to decide where to send police officers, judges to decide whom to release on bail, welfare agencies to decide which children are at risk of abuse, and Facebook and Google to rank content and distribute ads. In these spheres, and many others, powerful prediction tools are changing how decisions are made, narrowing opportunities for the exercise of judgment, empathy, and creativity. In Algorithms for the People, Josh Simons flips the narrative about how we govern these technologies. Instead of examining the impact of technology on democracy, he explore...

Networked Systems
  • Language: en
  • Pages: 176

Networked Systems

This book constitutes the refereed proceedings of the 11th International Conference on Networked Systems, NETYS 2023, held in Benguerir, Morocco, during May 22–24, 2023. The 9 full papers and 3 short papers presented were carefully reviewed and selected from 31 submissions. The scope of the conference covers all aspects related to the design and the development of these systems, including, e.g., cloud systems, formal verification, concurrent and distributed algorithms, data management, data science, parallel/concurrent/distributed programming, machine learning, multi-core architectures, networks, and security.

Machine Learning, Optimization, and Data Science
  • Language: en
  • Pages: 701

Machine Learning, Optimization, and Data Science

This two-volume set, LNCS 12565 and 12566, constitutes the refereed proceedings of the 6th International Conference on Machine Learning, Optimization, and Data Science, LOD 2020, held in Siena, Italy, in July 2020. The total of 116 full papers presented in this two-volume post-conference proceedings set was carefully reviewed and selected from 209 submissions. These research articles were written by leading scientists in the fields of machine learning, artificial intelligence, reinforcement learning, computational optimization, and data science presenting a substantial array of ideas, technologies, algorithms, methods, and applications.