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Machine Learning for Data Streams
A hands-on approach to tasks and techniques in data stream mining and real-time analytics, with examples in MOA, a popular freely available open-source software framework. Today many information sources—including sensor networks, financial markets, social networks, and healthcare monitoring—are so-called data streams, arriving sequentially and at high speed. Analysis must take place in real time, with partial data and without the capacity to store the entire data set. This book presents algorithms and techniques used in data stream mining and real-time analytics. Taking a hands-on approach, the book demonstrates the techniques using MOA (Massive Online Analysis), a popular, freely availa...
Adaptive Stream Mining
This book is a significant contribution to the subject of mining time-changing data streams and addresses the design of learning algorithms for this purpose. It introduces new contributions on several different aspects of the problem, identifying research opportunities and increasing the scope for applications. It also includes an in-depth study of stream mining and a theoretical analysis of proposed methods and algorithms. The first section is concerned with the use of an adaptive sliding window algorithm (ADWIN). Since this has rigorous performance guarantees, using it in place of counters or accumulators, it offers the possibility of extending such guarantees to learning and mining algori...
IoT Streams for Data-Driven Predictive Maintenance and IoT, Edge, and Mobile for Embedded Machine Learning
This book constitutes selected papers from the Second International Workshop on IoT Streams for Data-Driven Predictive Maintenance, IoT Streams 2020, and First International Workshop on IoT, Edge, and Mobile for Embedded Machine Learning, ITEM 2020, co-located with ECML/PKDD 2020 and held in September 2020. Due to the COVID-19 pandemic the workshops were held online. The 21 full papers and 3 short papers presented in this volume were thoroughly reviewed and selected from 35 submissions and are organized according to the workshops and their topics: IoT Streams 2020: Stream Learning; Feature Learning; ITEM 2020: Unsupervised Machine Learning; Hardware; Methods; Quantization.
Data Mining In Time Series Databases
Adding the time dimension to real-world databases produces Time Series Databases (TSDB) and introduces new aspects and difficulties to data mining and knowledge discovery. This book covers the state-of-the-art methodology for mining time series databases. The novel data mining methods presented in the book include techniques for efficient segmentation, indexing, and classification of noisy and dynamic time series. A graph-based method for anomaly detection in time series is described and the book also studies the implications of a novel and potentially useful representation of time series as strings. The problem of detecting changes in data mining models that are induced from temporal databases is additionally discussed.
ECAI 2020
This book presents the proceedings of the 24th European Conference on Artificial Intelligence (ECAI 2020), held in Santiago de Compostela, Spain, from 29 August to 8 September 2020. The conference was postponed from June, and much of it conducted online due to the COVID-19 restrictions. The conference is one of the principal occasions for researchers and practitioners of AI to meet and discuss the latest trends and challenges in all fields of AI and to demonstrate innovative applications and uses of advanced AI technology. The book also includes the proceedings of the 10th Conference on Prestigious Applications of Artificial Intelligence (PAIS 2020) held at the same time. A record number of ...
Artificial Intelligence Research and Development
For almost twenty years the Catalan Association of Artificial Intelligence (ACIA) has been promoting cooperation between researchers in artificial intelligence within the Catalan speaking community. This book presents the proceedings of the 16th International Conference (CCIA 2013), held at the University of Vic (UVIC), Catalonia, Spain, in October 2013. This annual conference aims to foster discussion of the latest developments in artificial intelligence within the community of Catalan countries, as well as amongst members of the AI community worldwide. The book contains the 26 full papers, 5 short papers and 12 poster presentations from the conference, which are grouped under the following topics: relational learning, planning; satisfiability and constraints; perception and image processing; preprocessing; patterns extraction and learning; post-processing, model interpretability and decision support; recommenders, similarity and CBR; and multiagent systems.
Discovery Science
Annotation. This book constitutes the refereed proceedings of the 13th International Conference on Discovery Science, DS 2010, held in Canberra, Australia, in October 2010. The 25 revised full papers presented were carefully selected from 43 submissions and include the first part of the book. In a second part invited talks of ALT 2010 and DS 2010 are presented. The scope of the conference is the exchange of new ideas and information among researchers working in the area of automatic scientific discovery or working on tools for supporting the human process of discovery in science.
Research and Development in Intelligent Systems XXIX
The papers in this volume are the refereed papers presented at AI-2012, the Thirty-second SGAI International Conference on Innovative Techniques and Applications of Artificial Intelligence, held in Cambridge in December 2012 in both the technical and the application streams. They present new and innovative developments and applications, divided into technical stream sections on Data Mining, Data Mining and Machine Learning, Planning and Optimisation, and Knowledge Management and Prediction, followed by application stream sections on Language and Classification, Recommendation, Practical Applications and Systems, and Data Mining and Machine Learning. The volume also includes the text of short papers presented as posters at the conference. This is the twenty-ninth volume in the Research and Development in Intelligent Systems series, which also incorporates the twentieth volume in the Applications and Innovations in Intelligent Systems series. These series are essential reading for those who wish to keep up to date with developments in this important field.
Advances in Machine Learning
The First Asian Conference on Machine Learning (ACML 2009) was held at Nanjing, China during November 2–4, 2009.This was the ?rst edition of a series of annual conferences which aim to provide a leading international forum for researchers in machine learning and related ?elds to share their new ideas and research ?ndings. This year we received 113 submissions from 18 countries and regions in Asia, Australasia, Europe and North America. The submissions went through a r- orous double-blind reviewing process. Most submissions received four reviews, a few submissions received ?ve reviews, while only several submissions received three reviews. Each submission was handled by an Area Chair who co...
Machine Learning and Knowledge Discovery in Databases
The three volume proceedings LNAI 11906 – 11908 constitutes the refereed proceedings of the European Conference on Machine Learning and Knowledge Discovery in Databases, ECML PKDD 2019, held in Würzburg, Germany, in September 2019. The total of 130 regular papers presented in these volumes was carefully reviewed and selected from 733 submissions; there are 10 papers in the demo track. The contributions were organized in topical sections named as follows: Part I: pattern mining; clustering, anomaly and outlier detection, and autoencoders; dimensionality reduction and feature selection; social networks and graphs; decision trees, interpretability, and causality; strings and streams; privacy...
