I’m happy to announce that I’ve been selected as a CIFAR Azrieli Global Scholar this year (announcement). This appointment is for two years, and I will be able to attend awesome CIFAR meetings to hang out with and hear from awesome CIFAR fellows. I am especially looking forward to meetings organized by the Learning in Brain and Machine (LMB) Programme of CIFAR co-directed by Yoshua Bengion and Yann LeCun, in addition to interacting with other Azrieli Global Scholars and a broader set of fellows from other programmes at CIFAR . It is my understanding that this is not intended to award my
Author: kyunghyuncho
Lecture note “Brief Introduction to Machine Learning without Deep Learning”
This past Spring (2017), I taught the undergrad <Intro to Machine Learning> course. This was not only the first time for me to teach <Intro to Machine Learning> but also the first time for me to teach an undergrad course (!) This course was taught a year before by David Sontag who has now moved to MIT. Obviously, I thought about re-using David’s materials as they were, which you can find at http://cs.nyu.edu/~dsontag/courses/ml16/. These materials are really great, and the coverage of various topics in ML is simply amazing. I highly recommend all the materials on this web page. All the things
Google Faculty Award: 2016
My research proposal on <A Trainable Decoding Algorithm for Neural Machine Translation> has been selected for Google Research Award 2016 (it’s a bit confusing whether it’s 2016 or 2017; deadline in 2016 but decision in 2017.) I’d like to thank Google for this award which would greatly help my research. Gotta go buy a few more GPU’s! For more info, see https://research.googleblog.com/2017/02/google-research-awards-2016.html.
Best paper runner-up at NAACL’16
A paper by Orhan Firat, me and Yoshua Bengio on multi-way, multilingual neural machine translation is sadly but also happily a best paper runner up at NAACL’16. You can find the paper at https://arxiv.org/abs/1601.01073 The code has also been made public recently by Orhan at https://github.com/nyu-dl/dl4mt-multi
[Closed] A Post-Doctoral Researcher Position in Deep Learning for Medical Image Analysis
Update on March 15, 2016 Thanks for sending me your CV! I have screened the applications and have made an offer. Prof. Kyunghyun Cho (https://www.kyunghyuncho.me/) at the Computational Intelligence, Learning, Vision, and Robotics (CILVR) Group (http://cilvr.cs.nyu.edu/), Department of Computer Science (https://cs.nyu.edu/), New York University invites applications for a postdoctoral position on deep learning for medical image analysis. Applicants are expected to have strong background and experience in developing and investigating deep neural networks for computer vision, in addition to good knowledge of machine learning and excellent programming skills. Applicants should be able to implement deep neural networks, including multilayered convolutional