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Relations Between Machine Learning Problems - NIPS 2011Workshop

Relations between machine learning problems – an approach to unify the field. Workshop, December 16 or 17, 2011, Sierra Nevada. The only essential knowledge pertains to the. This workshop will focus on relations. Between machine learning problems. The idea is that by better understanding how different machine learning problems relate to each other, we will be able to better understand the field as a whole. For the workshop is several-fold:. Typically only care about solving their problem. One question th...

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Relations Between Machine Learning Problems - NIPS 2011Workshop | rml.anu.edu.au Reviews

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Relations between machine learning problems – an approach to unify the field. Workshop, December 16 or 17, 2011, Sierra Nevada. The only essential knowledge pertains to the. This workshop will focus on relations. Between machine learning problems. The idea is that by better understanding how different machine learning problems relate to each other, we will be able to better understand the field as a whole. For the workshop is several-fold:. Typically only care about solving their problem. One question th...

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7 inter relatedness of things

8 jorge luis borges

9 video lectures

10 the motivation

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Relations Between Machine Learning Problems - NIPS 2011Workshop | rml.anu.edu.au Reviews

https://rml.anu.edu.au

Relations between machine learning problems – an approach to unify the field. Workshop, December 16 or 17, 2011, Sierra Nevada. The only essential knowledge pertains to the. This workshop will focus on relations. Between machine learning problems. The idea is that by better understanding how different machine learning problems relate to each other, we will be able to better understand the field as a whole. For the workshop is several-fold:. Typically only care about solving their problem. One question th...

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Workshop Description

http://rml.anu.edu.au/Workshop%20Description.html

The workshop proposes to focus on relations between machine learning problems. We use “relation” quite generally to include (but not limit ourselves to) notions such as:. One type of problem being viewed special case of another type (e.g., classification as thresholded probability estimation);. Between learning problems (e.g., transforming ranking problems into classification problems);. The use of surrogate losses. Eg, replacing misclassification loss with some other, convex loss). Much recent work in m...

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Call for Submissions

http://rml.anu.edu.au/Call%20for%20Submissions.html

SUBMISSION DEADLINE EXTENDED TO 16 October. To align with a number of other workshop deadlines, we have extended the submission deadline to 16 October. We will send out decisions before the early registration deadline). Submissions are invited to the workshop. The selection criteria we will use are:. Does the proposal address the core topic of the workshop, or is it a force fit? Does the submission relate problems. Or is it solely focussed on particular techniques. There is no fixed format for submission...

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Crowdsourcing: Beyond Label Generation at NIPS 2016. Prediction, Belief, and Markets at AAAI 2013. Also presented at the Machine Learning Summer School. UC Santa Cruz, 2012. Workshop on Mathematical Foundations of Human Computation. With Shuchi Chawla, Chien-Ju Ho, Michael Kearns, and Santosh Vempala. CCC Visioning Workshop on Theoretical Foundations for Social Computing. With Yiling Chen, Arpita Ghosh, and Tim Roughgarden. Here is the resulting white paper. With Jason Hartline and Vahab Mirrokni. COBE 2...

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Relations Between Machine Learning Problems - NIPS 2011Workshop

Relations between machine learning problems – an approach to unify the field. Workshop, December 16 or 17, 2011, Sierra Nevada. The only essential knowledge pertains to the. This workshop will focus on relations. Between machine learning problems. The idea is that by better understanding how different machine learning problems relate to each other, we will be able to better understand the field as a whole. For the workshop is several-fold:. Typically only care about solving their problem. One question th...

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