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William Cukierski
Researcher at University of Medicine and Dentistry of New Jersey
Publications - 15
Citations - 2254
William Cukierski is an academic researcher from University of Medicine and Dentistry of New Jersey. The author has contributed to research in topics: Multispectral image & Multimodal learning. The author has an hindex of 10, co-authored 14 publications receiving 1603 citations. Previous affiliations of William Cukierski include Rutgers University & Université de Montréal.
Papers
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Book ChapterDOI
Challenges in Representation Learning: A Report on Three Machine Learning Contests
Ian Goodfellow,Dumitru Erhan,Pierre Luc Carrier,Aaron Courville,Mehdi Mirza,Ben Hamner,William Cukierski,Yichuan Tang,David Thaler,Dong-Hyun Lee,Yingbo Zhou,Chetan Ramaiah,Fangxiang Feng,Ruifan Li,Xiaojie Wang,Dimitris Athanasakis,John Shawe-Taylor,Maxim Milakov,John Park,Radu Ionescu,Marius Popescu,Cristian Grozea,James Bergstra,Jingjing Xie,Lukasz Romaszko,Bing Xu,Zhang Chuang,Yoshua Bengio +27 more
TL;DR: The ICML 2013 Workshop on Challenges in Representation Learning focused on three challenges: the black box learning challenge, the facial expression recognition challenge, and the multimodal learning challenge.
Posted Content
Challenges in Representation Learning: A report on three machine learning contests
Ian Goodfellow,Dumitru Erhan,Pierre Luc Carrier,Aaron Courville,Mehdi Mirza,Ben Hamner,William Cukierski,Yichuan Tang,David Thaler,Dong-Hyun Lee,Yingbo Zhou,Chetan Ramaiah,Fangxiang Feng,Ruifan Li,Xiaojie Wang,Dimitris Athanasakis,John Shawe-Taylor,Maxim Milakov,John Park,Radu Ionescu,Marius Popescu,Cristian Grozea,James Bergstra,Jingjing Xie,Lukasz Romaszko,Bing Xu,Zhang Chuang,Yoshua Bengio +27 more
TL;DR: The ICML 2013 Workshop on Challenges in Representation Learning focused on three challenges: the black box learning challenge, the facial expression recognition challenge, and the multimodal learning challenge as mentioned in this paper.
Journal ArticleDOI
Challenges in representation learning
Ian Goodfellow,Dumitru Erhan,Pierre Luc Carrier,Aaron Courville,Mehdi Mirza,Ben Hamner,William Cukierski,Yichuan Tang,David Thaler,Dong-Hyun Lee,Yingbo Zhou,Chetan Ramaiah,Fangxiang Feng,Ruifan Li,Xiaojie Wang,Dimitris Athanasakis,John Shawe-Taylor,Maxim Milakov,John Park,Radu Ionescu,Marius Popescu,Cristian Grozea,James Bergstra,Jingjing Xie,Lukasz Romaszko,Bing Xu,Zhang Chuang,Yoshua Bengio +27 more
TL;DR: The datasets created for these challenges are described, the results of the competitions are summarized, and some comments are provided on what kind of knowledge can be gained from machine learning competitions.
Journal ArticleDOI
Crowdsourcing reproducible seizure forecasting in human and canine epilepsy
Benjamin H. Brinkmann,Joost B. Wagenaar,Drew Abbot,Phillip Adkins,Simone C. Bosshard,Min Chen,Quang M. Tieng,Jialune He,F. J. Muñoz-Almaraz,Paloma Botella-Rocamora,Juan Pardo,Francisco Zamora-Martínez,Michael Hills,Wei Wu,Iryna Korshunova,William Cukierski,Charles H. Vite,Edward E. Patterson,Brian Litt,Gregory A. Worrell +19 more
TL;DR: An online, open-access seizure forecasting competition using intracranial EEG recordings from canines with naturally occurring epilepsy and human patients undergoing presurgical monitoring wins, with the winning algorithms forecast seizures at rates significantly greater than chance.
Proceedings ArticleDOI
Graph-based features for supervised link prediction
TL;DR: This work presents a three-pronged approach to the link prediction task, along with several novel variations on established similarity metrics, and discusses the challenges of processing a graph with more than a million nodes.