resnotebook.blogspot.com

Misc Research Stuff

An online notebook for my jottings on NLP and machine learning. Blogs on ACL Wiki. JHU NLP Reading Group. These days on ACL Wiki. Dealing with large scale graphs. Friday, July 3, 2009. Dealing with large scale graphs. To a hammer everything looks like a nail but one great hammer to have in your toolbox is the graph. The ACL anthology. Alone lists more than 300 results for the query "graph based". Paper we started out scaling up Label Propagation. But eventually the connection to PageRank. Make more sense...

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An online notebook for my jottings on NLP and machine learning. Blogs on ACL Wiki. JHU NLP Reading Group. These days on ACL Wiki. Dealing with large scale graphs. Friday, July 3, 2009. Dealing with large scale graphs. To a hammer everything looks like a nail but one great hammer to have in your toolbox is the graph. The ACL anthology. Alone lists more than 300 results for the query graph based. Paper we started out scaling up Label Propagation. But eventually the connection to PageRank. Make more sense...

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1 misc research stuff

2 nearest neighbors

3 language log

4 oliver's ml thoughts

5 machine learning etc

6 discover

7 clsp seminar series

8 machine learning lunch

9 theory lunch

10 graphical models

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Misc Research Stuff | resnotebook.blogspot.com Reviews

https://resnotebook.blogspot.com

An online notebook for my jottings on NLP and machine learning. Blogs on ACL Wiki. JHU NLP Reading Group. These days on ACL Wiki. Dealing with large scale graphs. Friday, July 3, 2009. Dealing with large scale graphs. To a hammer everything looks like a nail but one great hammer to have in your toolbox is the graph. The ACL anthology. Alone lists more than 300 results for the query "graph based". Paper we started out scaling up Label Propagation. But eventually the connection to PageRank. Make more sense...

INTERNAL PAGES

resnotebook.blogspot.com

1

Misc Research Stuff: July 2007

http://resnotebook.blogspot.com/2007_07_01_archive.html

An online notebook for my jottings on NLP and machine learning. Blogs on ACL Wiki. JHU NLP Reading Group. These days on ACL Wiki. Google allows data binging for researchers. Readings from SIGIR 2007. Readings from AAAI 2007. Reading List from KDD 2007. Effect of Spouses on PhD. Papers from COLT: Occams Hammer. ICML 2007 reading list. Thursday, July 26, 2007. Google allows data binging for researchers. Google now opened access to university researchers to its search and MT systems in today's announcement.

2

Misc Research Stuff: June 2007

http://resnotebook.blogspot.com/2007_06_01_archive.html

An online notebook for my jottings on NLP and machine learning. Blogs on ACL Wiki. JHU NLP Reading Group. These days on ACL Wiki. UMASS Statistical NLP reading list. Thursday, June 7, 2007. UMASS Statistical NLP reading list. Http:/ ciir.cs.umass.edu/ fuchun/readlist all/readlist.pdf. Links to this post. Subscribe to: Posts (Atom).

3

Misc Research Stuff: August 2007

http://resnotebook.blogspot.com/2007_08_01_archive.html

An online notebook for my jottings on NLP and machine learning. Blogs on ACL Wiki. JHU NLP Reading Group. These days on ACL Wiki. NLP and Global Warming. People Search on the Web. Digital Reasoning awarded contextual similarity pa. Saturday, August 18, 2007. NLP and Global Warming. Those of us who were at EMNLP-CONLL 2007 remember the "NLP and Global Warming" exchange between James Clarke, Jason Eisner, and Dan Bikel at the Q/A session of the. Clarke and Lapata paper. I really liked Hal's ending remark.

4

Misc Research Stuff: April 2007

http://resnotebook.blogspot.com/2007_04_01_archive.html

An online notebook for my jottings on NLP and machine learning. Blogs on ACL Wiki. JHU NLP Reading Group. These days on ACL Wiki. Reading List from EMNLP 2007. Monday, April 30, 2007. Reading List from EMNLP 2007. A GRAPH-BASED APPROACH TO NAMED ENTITY CATEGORIZATION IN WIKIPEDIA. USING CONDITIONAL RANDOM FIELDS. Yotaro Watanabe, Masayuki Asahara and Yuji Matsumoto. A TOPIC MODEL FOR WORD SENSE DISAMBIGUATION. Jordan Boyd-Graber, Xiaojin Zhu and David Blei. Sander Canisius and Caroline Sporleder.

5

Misc Research Stuff: Sentiment Analysis is AI-Hard

http://resnotebook.blogspot.com/2009/03/sentiment-analysis-is-ai-hard.html

An online notebook for my jottings on NLP and machine learning. Blogs on ACL Wiki. JHU NLP Reading Group. These days on ACL Wiki. Sentiment Analysis is AI-Hard. Tuesday, March 31, 2009. Sentiment Analysis is AI-Hard. In a breezy article. On sentiment analysis, Alex Wright quotes Bo Pang saying:. We are dealing with sentiment that can be expressed in subtle ways. This is so true with the examples I've encountered while working and my favorite is this one I saw on iTunes recently.

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machine-learning.blogspot.com

Social Media, Data Mining & Machine Learning: Workshop NLP in the Enterprise: Envisioning the Next 10 Years

http://machine-learning.blogspot.com/2010/04/workshop-nlp-in-enterprise-envisioning.html

Social Media, Data Mining and Machine Learning. Workshop NLP in the Enterprise: Envisioning the Next 10 Years. Saturday, April 10, 2010. The workshop " NLP in the Enterprise: Envisioining the next 10 years. PLN-E) will be held in Valencia (Spain), as a satellite workshop of SEPLN 2010, on September 6-7, 2010 . We aim the submission of works that shows how NLP can help enterprises to solve problems, or develop new products and services. We expect 3 different types of works:. Virtual Worlds and Massive Mul...

machine-learning.blogspot.com

Social Media, Data Mining & Machine Learning: October 2010

http://machine-learning.blogspot.com/2010_10_01_archive.html

Social Media, Data Mining and Machine Learning. ACM TIST Special Issue on Search and Mining User-generated Contents. Tuesday, October 12, 2010. Deadline: 1 December 2010. More info at ACM TIST webpage. The primary goal of this special issue of ACM Transactions on Intelligent Systems and Technology is to foster research in the interplay between Social Media, Data/Opinion Mining and Search, aiming to reflect the actual developments on technologies that exploit user generated contents. Manuscripts submitted...

ml.typepad.com

Machine Learning Thoughts

http://ml.typepad.com/machine_learning_thoughts

Some thoughts about philosophical, theoretical and practical aspects of Machine Learning. On Why do we do Science? On Why do we do Science? On Happiness of a scientist II: the 80/20 rule. On The Failure of AI. On Happiness of a scientist II: the 80/20 rule. On The Failure of AI. On Happiness of a scientist I: rationalization. Director of Science and Innovation, Nielsen BuzzMetrics; co-creator of BlogPulse. Algorithmic Learning in a Random World (Vladimir Vovk,Alex Gammerman,Glenn Shafer). Scientific rese...

ml.typepad.com

Machine Learning Thoughts: Personal

http://ml.typepad.com/machine_learning_thoughts/personal

Some thoughts about philosophical, theoretical and practical aspects of Machine Learning. On Why do we do Science? On Why do we do Science? On Happiness of a scientist II: the 80/20 rule. On The Failure of AI. On Happiness of a scientist II: the 80/20 rule. On The Failure of AI. On Happiness of a scientist I: rationalization. Director of Science and Innovation, Nielsen BuzzMetrics; co-creator of BlogPulse. Algorithmic Learning in a Random World (Vladimir Vovk,Alex Gammerman,Glenn Shafer). Scientific rese...

ml.typepad.com

Machine Learning Thoughts:

http://ml.typepad.com/machine_learning_thoughts/2006/09/index.html

Some thoughts about philosophical, theoretical and practical aspects of Machine Learning. On Why do we do Science? On Why do we do Science? On Happiness of a scientist II: the 80/20 rule. On The Failure of AI. On Happiness of a scientist II: the 80/20 rule. On The Failure of AI. On Happiness of a scientist I: rationalization. Director of Science and Innovation, Nielsen BuzzMetrics; co-creator of BlogPulse. Algorithmic Learning in a Random World (Vladimir Vovk,Alex Gammerman,Glenn Shafer). Laquo; June 2006.

ml.typepad.com

Machine Learning Thoughts: Machine Learning

http://ml.typepad.com/machine_learning_thoughts/machine_learning

Some thoughts about philosophical, theoretical and practical aspects of Machine Learning. On Why do we do Science? On Why do we do Science? On Happiness of a scientist II: the 80/20 rule. On The Failure of AI. On Happiness of a scientist II: the 80/20 rule. On The Failure of AI. On Happiness of a scientist I: rationalization. Director of Science and Innovation, Nielsen BuzzMetrics; co-creator of BlogPulse. Algorithmic Learning in a Random World (Vladimir Vovk,Alex Gammerman,Glenn Shafer). Luis von Ahn ha...

ml.typepad.com

Machine Learning Thoughts: Pertinence

http://ml.typepad.com/machine_learning_thoughts/pertinence

Some thoughts about philosophical, theoretical and practical aspects of Machine Learning. On Why do we do Science? On Why do we do Science? On Happiness of a scientist II: the 80/20 rule. On The Failure of AI. On Happiness of a scientist II: the 80/20 rule. On The Failure of AI. On Happiness of a scientist I: rationalization. Director of Science and Innovation, Nielsen BuzzMetrics; co-creator of BlogPulse. Algorithmic Learning in a Random World (Vladimir Vovk,Alex Gammerman,Glenn Shafer). Complex systems...

ml.typepad.com

Machine Learning Thoughts: Happiness of a scientist I: rationalization

http://ml.typepad.com/machine_learning_thoughts/2007/02/happiness_of_a_.html

Some thoughts about philosophical, theoretical and practical aspects of Machine Learning. On Why do we do Science? On Why do we do Science? On Happiness of a scientist II: the 80/20 rule. On The Failure of AI. On Happiness of a scientist II: the 80/20 rule. On The Failure of AI. On Happiness of a scientist I: rationalization. Director of Science and Innovation, Nielsen BuzzMetrics; co-creator of BlogPulse. Algorithmic Learning in a Random World (Vladimir Vovk,Alex Gammerman,Glenn Shafer). This is why I i...

ml.typepad.com

Machine Learning Thoughts: Decision-making

http://ml.typepad.com/machine_learning_thoughts/2005/06/decisionmaking.html

Some thoughts about philosophical, theoretical and practical aspects of Machine Learning. On Why do we do Science? On Why do we do Science? On Happiness of a scientist II: the 80/20 rule. On The Failure of AI. On Happiness of a scientist II: the 80/20 rule. On The Failure of AI. On Happiness of a scientist I: rationalization. Director of Science and Innovation, Nielsen BuzzMetrics; co-creator of BlogPulse. Algorithmic Learning in a Random World (Vladimir Vovk,Alex Gammerman,Glenn Shafer). The reality mig...

ml.typepad.com

Machine Learning Thoughts: Data Mining

http://ml.typepad.com/machine_learning_thoughts/data_mining

Some thoughts about philosophical, theoretical and practical aspects of Machine Learning. On Why do we do Science? On Why do we do Science? On Happiness of a scientist II: the 80/20 rule. On The Failure of AI. On Happiness of a scientist II: the 80/20 rule. On The Failure of AI. On Happiness of a scientist I: rationalization. Director of Science and Innovation, Nielsen BuzzMetrics; co-creator of BlogPulse. Algorithmic Learning in a Random World (Vladimir Vovk,Alex Gammerman,Glenn Shafer). Luis von Ahn ha...

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resnotebook.blogspot.com

Misc Research Stuff

An online notebook for my jottings on NLP and machine learning. Blogs on ACL Wiki. JHU NLP Reading Group. These days on ACL Wiki. Dealing with large scale graphs. Friday, July 3, 2009. Dealing with large scale graphs. To a hammer everything looks like a nail but one great hammer to have in your toolbox is the graph. The ACL anthology. Alone lists more than 300 results for the query "graph based". Paper we started out scaling up Label Propagation. But eventually the connection to PageRank. Make more sense...

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