NeurIPS 2019 Competition and Demonstration Track: Revised selected papers

Hugo Jair Escalante, Raia Hadsell
Proceedings of the NeurIPS 2019 Competition and Demonstration Track, PMLR 123:1-12, 2020.

Abstract

Machine learning competitions have grown in popularity and impact over the last decade, emerging as an effective means to advance the state of the art by posing well-structured, relevant, and challenging problems to the community at large. Motivated by a reward or merely the satisfaction of seeing their machine learning algorithm reach the top of a leaderboard, practitioners innovate, improve, and tune their approach before evaluating on a held-out dataset or environment. The competition track of NeurIPS has matured in 2019, its third year, with a considerable increase in both the number of challenges and the diversity of domains and topics. Demonstrations offer a complementary dimension to the competitions, focusing on areas of machine learning which are either human interactive or demonstrable in some way, for instance robotics applications or generative models. This volume is a compilation of selected papers associated with the NeurIPS 2019 Demonstration and Competition Track. The scope of the volume includes the design of the competitions, analysis of the results, novel methodologies developed to respond to the competitions’ challenges, and the design and development of creative demonstrations.

Cite this Paper

BibTeX
@InProceedings{pmlr-v123-escalante20a, title = {{NeurIPS 2019} Competition and Demonstration Track: Revised selected papers}, author = {Escalante, Hugo Jair and Hadsell, Raia}, booktitle = {Proceedings of the NeurIPS 2019 Competition and Demonstration Track}, pages = {1--12}, year = {2020}, editor = {Escalante, Hugo Jair and Hadsell, Raia}, volume = {123}, series = {Proceedings of Machine Learning Research}, month = {08--14 Dec}, publisher = {PMLR}, pdf = {http://proceedings.mlr.press/v123/escalante20a/escalante20a.pdf}, url = {https://proceedings.mlr.press/v123/escalante20a.html}, abstract = {Machine learning competitions have grown in popularity and impact over the last decade, emerging as an effective means to advance the state of the art by posing well-structured, relevant, and challenging problems to the community at large. Motivated by a reward or merely the satisfaction of seeing their machine learning algorithm reach the top of a leaderboard, practitioners innovate, improve, and tune their approach before evaluating on a held-out dataset or environment. The competition track of NeurIPS has matured in 2019, its third year, with a considerable increase in both the number of challenges and the diversity of domains and topics. Demonstrations offer a complementary dimension to the competitions, focusing on areas of machine learning which are either human interactive or demonstrable in some way, for instance robotics applications or generative models. This volume is a compilation of selected papers associated with the NeurIPS 2019 Demonstration and Competition Track. The scope of the volume includes the design of the competitions, analysis of the results, novel methodologies developed to respond to the competitions’ challenges, and the design and development of creative demonstrations. } }
Endnote
%0 Conference Paper %T NeurIPS 2019 Competition and Demonstration Track: Revised selected papers %A Hugo Jair Escalante %A Raia Hadsell %B Proceedings of the NeurIPS 2019 Competition and Demonstration Track %C Proceedings of Machine Learning Research %D 2020 %E Hugo Jair Escalante %E Raia Hadsell %F pmlr-v123-escalante20a %I PMLR %P 1--12 %U https://proceedings.mlr.press/v123/escalante20a.html %V 123 %X Machine learning competitions have grown in popularity and impact over the last decade, emerging as an effective means to advance the state of the art by posing well-structured, relevant, and challenging problems to the community at large. Motivated by a reward or merely the satisfaction of seeing their machine learning algorithm reach the top of a leaderboard, practitioners innovate, improve, and tune their approach before evaluating on a held-out dataset or environment. The competition track of NeurIPS has matured in 2019, its third year, with a considerable increase in both the number of challenges and the diversity of domains and topics. Demonstrations offer a complementary dimension to the competitions, focusing on areas of machine learning which are either human interactive or demonstrable in some way, for instance robotics applications or generative models. This volume is a compilation of selected papers associated with the NeurIPS 2019 Demonstration and Competition Track. The scope of the volume includes the design of the competitions, analysis of the results, novel methodologies developed to respond to the competitions’ challenges, and the design and development of creative demonstrations.
APA
Escalante, H.J. & Hadsell, R.. (2020). NeurIPS 2019 Competition and Demonstration Track: Revised selected papers. Proceedings of the NeurIPS 2019 Competition and Demonstration Track, in Proceedings of Machine Learning Research 123:1-12 Available from https://proceedings.mlr.press/v123/escalante20a.html.

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