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Schedule : Spring 2021
This is the tentative schedule of Mélange group for the Spring 2021 semester.
Meeting time & Place : Mondays 12:00 PM - 1:00 PM (MST) via Zoom/Webex
WEEK | DATE | TOPIC | PRESENTER |
1 | 01/29/2021 | Intro meeting | |
2 | 02/08/2021 | | |
3 | 02/15/2021 | | |
4 | 02/22/2021 | | |
5 | 03/01/2021 | | |
6 | 03/08/2021 | | |
7 | 03/15/2021 | | |
8 | 03/22/2021 | | |
9 | 03/29/2021 | | |
10 | 04/05/2021 | | |
11 | 04/12/2021 | | |
12 | 04/19/2021 | | |
13 | 04/26/2021 | | |
14 | 05/03/2021 | | |
15 | 05/10/2021 | | |
Previous Semesters, including legacy reading lists
Standard paper study questions
Write a short (max 5 sentences) summary of the paper.
What is the problem addressed in the paper?
Why is the problem important?
How do the authors address the problem?
How do they evaluate their approach?
What is the punch-line (key cool idea, or “what I got out of this paper”)? This is often different for different people and different from what the authors may have intended.
Make a list of deeper questions that you would like discussed in the meeting.
Current Reading Pool
Nathanaël Courant, Xavier Leroy.
Verified Code Generation for the Polyhedral Model. In
Proc. ACM Program. Lang., POPL, 2021.
https://doi.org/10.1145/3434321
Rui Li, Yufan Xu, Aravind Sukumaran-Rajam, Atanas Rountev, P. Sadayappan.
Analytical Characterization and Design Space Exploration for Optimization of CNNs. In
The ACM Conference on Architectural Support for Programming Languages and Operating
Systems, ASPLOS, 2021.
https://arxiv.org/pdf/2101.09808.pdf
Rajan Walia, Praveen Narayanan, Jacques Carette, Sam Tobin-Hochstadt, Chung-chieh Shan.
From High-Level Inference Algorithms to Efficient Code. In
Proc. ACM Program. Lang., ICFP, 2019.
https://doi.org/10.1145/3341702
Eli Bingham, Jonathan P. Chen, Martin Jankowiak, Fritz Obermeyer, Neeraj Pradhan, Theofanis Karaletsos, Rohit Singh, Paul Szerlip, Paul Horsfall, Noah D. Goodman.
Pyro: Deep Universal Probabilistic Programming. In
J. Mach. Learn. Res., JMLR, 2019.
https://paperswithcode.com/paper/pyro-deep-universal-probabilistic-programming