NIGEL 2006 Part II: Dasgupta vs. Booker

The second weekly release of NIGEL 2006 talks is available at LCS & GBML Central. This week Dipankar Dasgupta reviews the negative selection algorithm, where as Lashon Booker travels in time to the past and future of learning classifier systems.

Related posts:NIGEL 2006 Part IV: Llorà vs. CasillasNIGEL 2006 Part III: Butz vs. BarryNIGEL […]

Related posts:

  1. NIGEL 2006 Part IV: Llorà vs. Casillas
  2. NIGEL 2006 Part III: Butz vs. Barry
  3. NIGEL 2006 Part V: Bernardó vs. Lanzi

The second weekly release of NIGEL 2006 talks is available at LCS & GBML Central. This week Dipankar Dasgupta reviews the negative selection algorithm, where as Lashon Booker travels in time to the past and future of learning classifier systems.

Related posts:

  1. NIGEL 2006 Part IV: Llorà vs. Casillas
  2. NIGEL 2006 Part III: Butz vs. Barry
  3. NIGEL 2006 Part V: Bernardó vs. Lanzi

NIGEL 2006 revisited (Part II): Booker and Dasgupta

This week two more NIGEL 2006 talks. Enjoy this second release, Dasgupta vs. Booker.

Dipankar Dasgupta

Video
[vimeo clip_id=4592273 width=”432″ height=”320″]

Slides
[slideshare id=1384601&doc=nigel-2006-dasgupta-090504153353-phpapp01]

Lashon Booker

Video
[vimeo clip_id=4592087 width=”432″ height=”320″]

Slides
[slideshare id=1384637&doc=nigel-2006-booker-090504153739-phpapp02]

Transcoding NIGEL 2006 videos

Last week Pier Luca Lanzi was visiting IlliGAL. Yesterday, before he left for Chicago, we went for one last brunch.  He mentioned that he liked a lot the videos we shot during NIGEL 2006. Thinking about it we agreed would be useful to recover the videos and upload them into some of the usual video […]

Related posts:

  1. NIGEL 2006 Part VI: Bacardit
  2. NIGEL 2006 Part V: Bernardó vs. Lanzi
  3. NIGEL 2006 Part IV: Llorà vs. Casillas

Last week Pier Luca Lanzi was visiting IlliGAL. Yesterday, before he left for Chicago, we went for one last brunch.  He mentioned that he liked a lot the videos we shot during NIGEL 2006. Thinking about it we agreed would be useful to recover the videos and upload them into some of the usual video sharing site suspects. Currently they are hosted, for long term storage purposes, at NCSA’s web archive. I spent sometime retrieving them from the archive (they are pretty fat and encoded in wmv) and I stated transcoding it in m4a. My plan? Make them available via Vimeo and LCS & GBML Central. Also, I will be uploading the presentation slides to SlideShare and also make them available via LCS & GBML Central.

Update: The first two videos (Wilson and Goldberg) are already available at LCS & GBML Central.

Related posts:

  1. NIGEL 2006 Part VI: Bacardit
  2. NIGEL 2006 Part V: Bernardó vs. Lanzi
  3. NIGEL 2006 Part IV: Llorà vs. Casillas

Meandre overview slides

On May 26th I gave a seminar about Meandre’s basics at the Computer Science department at University of Illinois . The talk was part of the Cloud Computing Seminars. I merged together slides I have been using to talk about Meandre, and tried to give it an easy to grasp overview flavor. You view […]

Related posts:

  1. An Overview of the DISCUS project
  2. Meandre: Semantic-Driven Data-Intensive Flows in the Clouds
  3. Meandre 1.4.0 released, 1.4.1 coming short after

On May 26th I gave a seminar about Meandre’s basics at the Computer Science department at University of Illinois . The talk was part of the Cloud Computing Seminars. I merged together slides I have been using to talk about Meandre, and tried to give it an easy to grasp overview flavor. You view them below, or you can also download them here.

Related posts:

  1. An Overview of the DISCUS project
  2. Meandre: Semantic-Driven Data-Intensive Flows in the Clouds
  3. Meandre 1.4.0 released, 1.4.1 coming short after

NCSA/IlliGAL Gathering on Evolutionary Learning (NIGEL’2006)

On May 16th and 17th, a group formed by more than twenty researchers got together in Urbana-Champaign (Illlinois) to participate in the gathering on evolutionary learning organized by the National Center for Supercomputer Applications and the Illinois Genetic Algorithms Laboratory (NIGEL 2006). The goals were to discus current state-of-the-art research in learning classifier systems and other genetics-based machine learning, and to identify future research trends and applications where evolutionary learning might provide a competitive advantage. The first day attendees gave presentations about challenges and current research topics (see the materials below). The second day, a series of three topic-oriented brainstorming sessions were conducted covering: (1) future of LCS and other GBML, (2) areas of application, and (3) techniques.

The list of participants included Loretta Auvil, Jaume Bacardit, Alwyn Barry, Lashon Booker, Ester Bernado, Will Browne, Martin Butz, Jorge Casillas, Helen Dam, Dipankar Dasgupta, Deon Garrett, David Goldberg, Noriko Imafuji, Pier Luca Lanzi, Xavier Llora, Kumara Sastry, Kamran Shafi, Kenneth Turvey, Michael Welge, Ashley Williams, Stewart Wilson, and Paul Winward.

Presentations slides and videos of the presentations

Some pictures of the event can be found here or at the NIGEL web site.

Xavier Llorà: “Welcome and presentation”[Slides][Video]
Stewart W. Wilson: “Can We Do Captchas?” [Slides][Video]
David E. Goldberg: “Searle, Intentionality, and the Future of Classifier Systems” [Slides][Video]
Dipankar Dasgupta: “Artificial Immune Systems in Anomaly Detection” [Slides][Video]
Lashon Booker: “A Retrospective Look at Classifier System Research” [Slides][Video]
Martin Butz: “XCS: Current Capabilities and Future Challenges” [Slides][Video]
Alwyn Barry: “Towards a Formal Framework for Accuracy-based LCS” [Slides][Video]
Xavier Llorà: “Linkage Learning for Pittsburgh Learning Classifier Systems: Making Problems Tractable” [Slides][Video]
Jorge Casillas: “Scalability in GBML, Accuracy-Based Michigan Fuzzy LCS, and New Trends” [Slides][Video]
Ester Bernadó: “Learning Classifier Systems for Unbalanced Datasets” [Slides][Video]
Pier-Luca Lanzi: “Computed Prediction: so far, so good. Now what?” [Slides][Video]
Jaume Bacardit: “Pittsburgh Learning Classifier Systems for Protein Structure Prediction: Scalability and Explanatory Power” [Slides][Video]

NCSA/IlliGAL Gathering on Evolutionary Learning (NIGEL’2006)

On May 16th and 17th, a group formed by more than twenty researchers got together in Urbana-Champaign (Illlinois) to participate in the gathering on evolutionary learning organized by the National Center for Supercomputer Applications and the Illinois Genetic Algorithms Laboratory (NIGEL 2006). The goals were to discus current state-of-the-art research in learning classifier systems and other genetics-based machine learning, and to identify future research trends and applications where evolutionary learning might provide a competitive advantage. The first day attendees gave presentations about challenges and current research topics (see the materials below). The second day, a series of three topic-oriented brainstorming sessions were conducted covering: (1) future of LCS and other GBML, (2) areas of application, and (3) techniques.

The list of participants included Loretta Auvil, Jaume Bacardit, Alwyn Barry, Lashon Booker, Ester Bernado, Will Browne, Martin Butz, Jorge Casillas, Helen Dam, Dipankar Dasgupta, Deon Garrett, David Goldberg, Noriko Imafuji, Pier Luca Lanzi, Xavier Llora, Kumara Sastry, Kamran Shafi, Kenneth Turvey, Michael Welge, Ashley Williams, Stewart Wilson, and Paul Winward.

Presentations slides and videos of the presentations

Some pictures of the event can be found here or at the NIGEL web site.

Xavier Llorà: “Welcome and presentation”[Slides]
Stewart W. Wilson: “Can We Do Captchas?” [Slides]
David E. Goldberg: “Searle, Intentionality, and the Future of Classifier Systems” [Slides]
Dipankar Dasgupta: “Artificial Immune Systems in Anomaly Detection” [Slides]
Lashon Booker: “A Retrospective Look at Classifier System Research” [Slides]
Martin Butz: “XCS: Current Capabilities and Future Challenges” [Slides]
Alwyn Barry: “Towards a Formal Framework for Accuracy-based LCS” [Slides]
Xavier Llorà: “Linkage Learning for Pittsburgh Learning Classifier Systems: Making Problems Tractable” [Slides]
Jorge Casillas: “Scalability in GBML, Accuracy-Based Michigan Fuzzy LCS, and New Trends” [Slides]
Ester Bernadó: “Learning Classifier Systems for Unbalanced Datasets” [Slides]
Pier-Luca Lanzi: “Computed Prediction: so far, so good. Now what?” [Slides]
Jaume Bacardit: “Pittsburgh Learning Classifier Systems for Protein Structure Prediction: Scalability and Explanatory Power” [Slides]