Home » Posts tagged 'deep learning'
Tag Archives: deep learning
Talk at University of Tokyo
On August 18, I visited Professor Shigeru Chiba at the Core Software Group of the Dept. of Creative Informatics Graduate School of Information Science and Technology at The University of Tokyo. I gave a talk about preliminary research in automated refactoring of Deep Learning software.(more…)
Slides from GMU talk about challenges in executing imperative Deep Learning programs as graphs
Slides from my talk at George Mason University (GMU) on “Challenges in Migrating Imperative Deep Learning Programs to Graph Execution: An Empirical Study” are now available.
“Migrating Imperative Deep Learning Programs to Graph Execution” guest lecture on YouTube
Thanks to Stevens Institute of Technology for posting my guest lecture on imperative Deep Learning program execution to YouTube!
Paper on hybridization challenges in imperative Deep Learning programs accepted at MSR ’22
Our paper entitled, “Challenges in migrating imperative Deep Learning programs to graph execution: An empirical study,” has been accepted to the main technical research track at the IEEE/ACM SIGSOFT 2022 International Conference on Mining Software Repositories (MSR)! Out of 138 papers, 45 were accepted, amounting to a 32.6% acceptance rate. The conference will take place later this year in Pittsburgh and is co-located with ICSE 2022.
A special congratulations to Tatiana for publishing her first full conference paper as first-author in the second year of her Ph.D. studies! Also congrats to Mehdi and Anita, and thank you for all of your hard work!