LCS & GBML on Twitter- Cloud Services Lab Research Lead: Applied Analytics and Machine Learning Job: Cloud Services Lab Research Lead... http://t.co/GPYIJCMy6M May 19, 2013
- Job: Search Architect-Java/Machine Learning/Lucene/NLP in Noida, India http://t.co/3hJ2056Av2 #job May 19, 2013
- RT @TheNextWeb: Google sets up a new lab to research how quantum computing can propel machine learning http://t.co/0XGPCOCmOF by @robinwaut… May 19, 2013
- AYASDI: large-scale machine learning 'n topological data analysis combined into a single platform http://t.co/PJq8U37IPf May 19, 2013
- Leaving love messages for @brookstim in machine learning notes. http://t.co/31ThVzRnDA May 19, 2013
- @zozoped c'est une définition très "machine learning", j'en suis assez content en fait. May 19, 2013
Category Archives: Books
Parallel and Distributed Computational Intelligence book is out for pre-order
“Parallel and Distributed Computational Intelligence” edited by Francisco Fernández de Vega & Erick Cantú-Paz and published by Springer is out for pre-order. The first chapter “When Huge is Routine: Scaling Genetic Algorithms and Estimation of Distribution Algorithms via Data-Intensive Computing” of the book was written together with coauthors Abhishek Verma, Roy Campbell, and David E. [...]
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Posted in Books, Data-Intensive Computing, Estimation of distribution algorithms, Genetic algorithms, Publications
Tagged distributed computing, parallel programming
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CIG-2009 proceedings available online
Pier Luca Lanzi just sent a note saying saying that the proceedings of the 2009 Symposium on Computational Intelligence and Games (CIG-2009) are now available on-line at
http://www.ieee-cig.org/cig-2009/Proceedings/
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Posted in Community Feeds, Proceedings
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Reinforcement Learning, Logic and Evolutionary Computation
Drew Mellor is pleased to announce the publication of his new LCS book. Reinforcement Learning, Logic and Evolutionary Computation: A Learning Classifier System Approach to Relational Reinforcement Learning, published by Lambert Academic Publishing (ISBN 978-3-8383-0196-9). Abstract Reinforcement learning (RL) consists … Continue reading
Posted in Books, Featured
Tagged evolutionary computation, Learning classifier systems, logic
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Learning Classifier Systems, Springer LNAI 4998
Learning Classifier Systems: 10th International Workshop, IWLCS 2006, Seattle, MA, USA, July 8, 2006, and 11th International Workshop, IWLCS 2007, London, UK, July 8, 2007, Revised Selected Papers Series: Lecture Notes in Computer Science Subseries: Lecture Notes in Artificial Intelligence , Vol. 4998 … Continue reading
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Design and Analysis of Learning Classifier Systems: A Probabilistic Approach
The book Design and Analysis of Learning Classifier Systems: A Probabilistic Approach by Jan Drugowitsch presents a machine learning approach to Learning Classifier Systems. In the author’s own words: This book provides a comprehensive introduction to the design and analysis … Continue reading
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The Entrepreneurial Engineer
Entrepreneurial times call for The Entrepreneurial Engineer In an age when technology and business are merging as never before, today’s engineers need skills matched with the times. Today, career success as an engineer is determined as much by an ability … Continue reading → Continue reading
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Genetic Algorithms in Search, Optimization, and Machine Learning
Reviews from amazon.com: David Goldberg’s Genetic Algorithms in Search, Optimization and Machine Learning is by far the bestselling introduction to genetic algorithms. Goldberg is one of the preeminent researchers in the field–he has published over 100 research articles on genetic … Continue reading → Continue reading
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Advances at the frontier of LCS: LNCS 4399
“Advances at the frontier of Learning Classifier Systems” has been shipped to Springer for the final stages of editing and printing. The volume is going to be printed as Springer’s LNCS 4399 volume. When we started editing this volume, we … Continue reading
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Scalable Optimization via Probabilistic Modeling: From Algorithms to Applications (Studies in Computational Intelligence)
This book focuses like a laser beam on one of the hottest topics in evolutionary computation over the last decade or so: estimation of distribution algorithms (EDAs). EDAs are an important current technique that is leading to breakthroughs in genetic … Continue reading → Continue reading
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Scalable optimization via probabilistic modeling: From algorithms to applications
The book “Scalable Optimization via Probabilistic Modeling: From Algorithms to Applications” edited by Martin Pelikan, Kumara Sastry, and Erick Cantu-Paz has just been published by Springer. Estimation of distribution algorithms combine evolutionary computation and machine learning to provide a class … Continue reading
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