hunch_net hunch_net-2005 hunch_net-2005-66 knowledge-graph by maker-knowledge-mining
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Introduction: For anyone planning to do research, conference attendance is virtually mandatory for success. Aside from exposing yourself to a large collection of different ideas, many interesting conversations leading to new research happen at conferences. If you are a student, you should plan to go to at least one summer conference. Your advisor should cover the costs. Conference Location Early Registration deadline normal/student cost in US dollars AAAI Pittsburgh, PA, USA May 13 590/170 IJCAI Edinburgh, Scotland May 21 663/351 COLT Bertinoro, Italy May 30 256/178 KDD Chicago, IL, USA July 15 590/260 ICML Bonn, Germany July 1 448 UAI Edinburgh, Scotland not ready yet ???
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same-blog 1 0.99999994 66 hunch net-2005-05-03-Conference attendance is mandatory
Introduction: For anyone planning to do research, conference attendance is virtually mandatory for success. Aside from exposing yourself to a large collection of different ideas, many interesting conversations leading to new research happen at conferences. If you are a student, you should plan to go to at least one summer conference. Your advisor should cover the costs. Conference Location Early Registration deadline normal/student cost in US dollars AAAI Pittsburgh, PA, USA May 13 590/170 IJCAI Edinburgh, Scotland May 21 663/351 COLT Bertinoro, Italy May 30 256/178 KDD Chicago, IL, USA July 15 590/260 ICML Bonn, Germany July 1 448 UAI Edinburgh, Scotland not ready yet ???
2 0.55814385 17 hunch net-2005-02-10-Conferences, Dates, Locations
Introduction: Conference Locate Date COLT Bertinoro, Italy June 27-30 AAAI Pittsburgh, PA, USA July 9-13 UAI Edinburgh, Scotland July 26-29 IJCAI Edinburgh, Scotland July 30 – August 5 ICML Bonn, Germany August 7-11 KDD Chicago, IL, USA August 21-24 The big winner this year is Europe. This is partly a coincidence, and partly due to the general internationalization of science over the last few years. With cuts to basic science in the US and increased hassle for visitors, conferences outside the US become more attractive. Europe and Australia/New Zealand are the immediate winners because they have the science, infrastructure, and english in place. China and India are possible future winners.
3 0.23962089 4 hunch net-2005-01-26-Summer Schools
Introduction: There are several summer schools related to machine learning. We are running a two week machine learning summer school in Chicago, USA May 16-27. IPAM is running a more focused three week summer school on Intelligent Extraction of Information from Graphs and High Dimensional Data in Los Angeles, USA July 11-29. A broad one-week school on analysis of patterns will be held in Erice, Italy, Oct. 28-Nov 6.
4 0.22511244 422 hunch net-2011-01-16-2011 Summer Conference Deadline Season
Introduction: Machine learning always welcomes the new year with paper deadlines for summer conferences. This year, we have: Conference Paper Deadline When/Where Double blind? Author Feedback? Notes ICML February 1 June 28-July 2, Bellevue, Washington, USA Y Y Weak colocation with ACL COLT February 11 July 9-July 11, Budapest, Hungary N N colocated with FOCM KDD February 11/18 August 21-24, San Diego, California, USA N N UAI March 18 July 14-17, Barcelona, Spain Y N The larger conferences are on the west coast in the United States, while the smaller ones are in Europe.
5 0.22020313 145 hunch net-2005-12-29-Deadline Season
Introduction: Many different paper deadlines are coming up soon so I made a little reference table. Out of curiosity, I also computed the interval between submission deadline and conference. Conference Location Date Deadline interval COLT Pittsburgh June 22-25 January 21 152 ICML Pittsburgh June 26-28 January 30/February 6 140 UAI MIT July 13-16 March 9/March 16 119 AAAI Boston July 16-20 February 16/21 145 KDD Philadelphia August 23-26 March 3/March 10 166 It looks like the northeastern US is the big winner as far as location this year.
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same-blog 1 0.9687348 66 hunch net-2005-05-03-Conference attendance is mandatory
Introduction: For anyone planning to do research, conference attendance is virtually mandatory for success. Aside from exposing yourself to a large collection of different ideas, many interesting conversations leading to new research happen at conferences. If you are a student, you should plan to go to at least one summer conference. Your advisor should cover the costs. Conference Location Early Registration deadline normal/student cost in US dollars AAAI Pittsburgh, PA, USA May 13 590/170 IJCAI Edinburgh, Scotland May 21 663/351 COLT Bertinoro, Italy May 30 256/178 KDD Chicago, IL, USA July 15 590/260 ICML Bonn, Germany July 1 448 UAI Edinburgh, Scotland not ready yet ???
2 0.91076517 17 hunch net-2005-02-10-Conferences, Dates, Locations
Introduction: Conference Locate Date COLT Bertinoro, Italy June 27-30 AAAI Pittsburgh, PA, USA July 9-13 UAI Edinburgh, Scotland July 26-29 IJCAI Edinburgh, Scotland July 30 – August 5 ICML Bonn, Germany August 7-11 KDD Chicago, IL, USA August 21-24 The big winner this year is Europe. This is partly a coincidence, and partly due to the general internationalization of science over the last few years. With cuts to basic science in the US and increased hassle for visitors, conferences outside the US become more attractive. Europe and Australia/New Zealand are the immediate winners because they have the science, infrastructure, and english in place. China and India are possible future winners.
3 0.80103672 283 hunch net-2008-01-07-2008 Summer Machine Learning Conference Schedule
Introduction: Conference Paper due date Conference Date Location AAAI January 22/23/25/30 July 13-17 Chicago, Illinois ICML Feb 8 July 5-9 Helsinki, Finland COLT Feb 20 July 9-12 Helsinki, Finland KDD Feb 23/29 August 24-27 Las Vegas, Nevada UAI Feb 27/Feb 29 July 9-12 Helsinki, Finland Helsinki is a fun place to visit.
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Introduction: Many different paper deadlines are coming up soon so I made a little reference table. Out of curiosity, I also computed the interval between submission deadline and conference. Conference Location Date Deadline interval COLT Pittsburgh June 22-25 January 21 152 ICML Pittsburgh June 26-28 January 30/February 6 140 UAI MIT July 13-16 March 9/March 16 119 AAAI Boston July 16-20 February 16/21 145 KDD Philadelphia August 23-26 March 3/March 10 166 It looks like the northeastern US is the big winner as far as location this year.
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Introduction: There are several summer schools related to machine learning. We are running a two week machine learning summer school in Chicago, USA May 16-27. IPAM is running a more focused three week summer school on Intelligent Extraction of Information from Graphs and High Dimensional Data in Los Angeles, USA July 11-29. A broad one-week school on analysis of patterns will be held in Erice, Italy, Oct. 28-Nov 6.
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same-blog 1 0.92626739 66 hunch net-2005-05-03-Conference attendance is mandatory
Introduction: For anyone planning to do research, conference attendance is virtually mandatory for success. Aside from exposing yourself to a large collection of different ideas, many interesting conversations leading to new research happen at conferences. If you are a student, you should plan to go to at least one summer conference. Your advisor should cover the costs. Conference Location Early Registration deadline normal/student cost in US dollars AAAI Pittsburgh, PA, USA May 13 590/170 IJCAI Edinburgh, Scotland May 21 663/351 COLT Bertinoro, Italy May 30 256/178 KDD Chicago, IL, USA July 15 590/260 ICML Bonn, Germany July 1 448 UAI Edinburgh, Scotland not ready yet ???
2 0.47055832 331 hunch net-2008-12-12-Summer Conferences
Introduction: Here’s a handy table for the summer conferences. Conference Deadline Reviewer Targeting Double Blind Author Feedback Location Date ICML ( wrong ICML ) January 26 Yes Yes Yes Montreal, Canada June 14-17 COLT February 13 No No Yes Montreal June 19-21 UAI March 13 No Yes No Montreal June 19-21 KDD February 2/6 No No No Paris, France June 28-July 1 Reviewer targeting is new this year. The idea is that many poor decisions happen because the papers go to reviewers who are unqualified, and the hope is that allowing authors to point out who is qualified results in better decisions. In my experience, this is a reasonable idea to test. Both UAI and COLT are experimenting this year as well with double blind and author feedback, respectively. Of the two, I believe author feedback is more important, as I’ve seen it make a difference. However, I still consider double blind reviewing a net wi
3 0.44401211 17 hunch net-2005-02-10-Conferences, Dates, Locations
Introduction: Conference Locate Date COLT Bertinoro, Italy June 27-30 AAAI Pittsburgh, PA, USA July 9-13 UAI Edinburgh, Scotland July 26-29 IJCAI Edinburgh, Scotland July 30 – August 5 ICML Bonn, Germany August 7-11 KDD Chicago, IL, USA August 21-24 The big winner this year is Europe. This is partly a coincidence, and partly due to the general internationalization of science over the last few years. With cuts to basic science in the US and increased hassle for visitors, conferences outside the US become more attractive. Europe and Australia/New Zealand are the immediate winners because they have the science, infrastructure, and english in place. China and India are possible future winners.
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Introduction: Many conference deadlines are coming soon. Deadline Double Blind / Author Feedback Time/Place ICML January 18((workshops) / February 1 (Papers) / February 13 (Tutorials) Y/Y Haifa, Israel, June 21-25 KDD February 1(Workshops) / February 2&5 (Papers) / February 26 (Tutorials & Panels)) / April 17 (Demos) N/S Washington DC, July 25-28 COLT January 18 (Workshops) / February 19 (Papers) N/S Haifa, Israel, June 25-29 UAI March 11 (Papers) N?/Y Catalina Island, California, July 8-11 ICML continues to experiment with the reviewing process, although perhaps less so than last year. The S “sort-of” for COLT is because author feedback occurs only after decisions are made. KDD is notable for being the most comprehensive in terms of {Tutorials, Workshops, Challenges, Panels, Papers (two tracks), Demos}. The S for KDD is because there is sometimes author feedback at the decision of the SPC. The (past) January 18 de
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Introduction: Suppose we had an infinitely powerful mathematician sitting in a room and proving theorems about learning. Could he solve machine learning? The answer is “no”. This answer is both obvious and sometimes underappreciated. There are several ways to conclude that some bias is necessary in order to succesfully learn. For example, suppose we are trying to solve classification. At prediction time, we observe some features X and want to make a prediction of either 0 or 1 . Bias is what makes us prefer one answer over the other based on past experience. In order to learn we must: Have a bias. Always predicting 0 is as likely as 1 is useless. Have the “right” bias. Predicting 1 when the answer is 0 is also not helpful. The implication of “have a bias” is that we can not design effective learning algorithms with “a uniform prior over all possibilities”. The implication of “have the ‘right’ bias” is that our mathematician fails since “right” is defined wi
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