highlights archive

the archive of (mostly) professional news and highlights

Sep 9, 2019 Honored to be part of the 2019 class of Google PhD Fellows in Machine Learning. Huge thank you to all my mentors, colleagues, and collaborators! And thank you, Google! :tada:
May 15, 2019 It was a lot of work (and fun!) to help teach PGM 2019 class this past Spring. Check out an excellent set of lecture notes written by students in distill-like style. Recordings of all lectures are now available on YouTube.
Apr 5, 2019 How do we make zero-shot NMT consistent? Our NAACL 2019 paper on Consistency by Agreement shows how to do that! Joint work with Ankur Parikh at Google NYC last year. Update (more resources): arXiv, NAACL19 slides, AI Science Seminar virtual talk.
Mar 29, 2019 Excited to be co-organizing a workshop on Adaptive & Multitask Learning this year at ICML. Please consider submitting your latest work!
Jan 25, 2019 Grateful to be awarded $12,000 in Cloud Credits for Research from AWS.
Time to burn some compute! :fire:
Jan 11, 2019 Excited to be on the teaching crew of PGM 2019. Expect new lecture material focused on deep generative models and RL. Everything will be online, lectures will be live-streamed and recorded. Stay tuned!
Dec 12, 2018 We’ve just launched the ML@CMU Blog! If you would like to contribute a post, please reach out.
Dec 10, 2018 New short paper, On the Complexity of Exploration in Goal-Driven Navigation, to presented at the R2L Workshop at NeurIPS 2018 (with Lisa, Russ, Eric).
Jul 15, 2018 Some highlights from AAMAS 2018 and ICML 2018:
May 21, 2018 Spending this summer at Google Research on the Language team in NYC, hosted by Ankur Parikh. Thinking about language generation in low-resource and multi-task settings.
May 5, 2018 Some highlights from ICLR 2018:
Apr 15, 2018 Very grateful to be awarded the 2018 CMLH Fellowship in Digital Healthcare by the Center of Machine Learning and Health. Looking forward to doing a lot of new exciting work in #ML4Health!
Apr 3, 2018 Gave a talk at ML Lunch Seminar on meta-learning for continuous adaptation. Here are the slides.
Jan 29, 2018 Two papers accepted for oral presentation:
Dec 20, 2017 Contextual Explanations Networks were presented at two NIPS workshops.
Materials are now online:
Oct 10, 2017 Technical report on the work this summer at OpenAI is now on arXiv. :sparkles:
Jul 31, 2017 Together with William Herlands and Dylan Fitzpatrick, we won a combined five categories in the NIJ Crime Forecasting Challenge. :tada:
Jun 30, 2017 Spoke with Waleed and Matt on the NLP Highlights podcast about our recent paper on Contextual Explanation Networks. Check it out!
May 30, 2017 New preprint: Contextual Explanation Networks. Available on arXiv. :sparkles:
May 21, 2017 Spending this summer at OpenAI working with Pieter Abbeel, Yuri Burda, and Igor Mordatch.
Nov 15, 2016 GP-LSTMs will be presented at the Bayesian Deep Learning workshop.
Oct 28, 2016 Our paper on learning scalable recurrent kernels is now available on arXiv.
Gaussian Processes for Keras: initial code release on Github. :sparkles:
For updates, tutorials, and examples follow the project on GitHub.
Aug 12, 2016 A paper on HMMs with nonparametric emissions has been accepted to NIPS!
Preprint is available on arXiv and code on GitHub.
Jul 1, 2016 Code releases for past and recent projects. Check out the code page.
Apr 24, 2016 Architectures Deep In Output Space accepted at ICML’16.
Oct 25, 2015 New homepage powered by Jekyll with al-folio theme. :sparkles:
Oct 1, 2015 I’m fortunate to join Sailing Lab and be advised by Prof. Eric Xing.
Sep 1, 2015 Started my PhD in machine learning at CMU!