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Wed 11 Nov 2020 17:39 - 17:40 at Virtual room 2 - ML Model Building

Success using machine learning (ML) in numerous fields has created a new class of users, who are not experts in the data science domain but want to use ML as a means to solve their inference problems. Various automatic machine learning (AutoML) approaches attempt to make ML solutions accessible to such users. In this work, we present a system that automatically synthesizes correct code within the context of the user’s data using sketching. In sketching, insight is determined through a partial program; a sketch expresses the high-level structure of implementation but leaves holes in place of the low-level details. We use meta-learning on meta-features to approximately solve holes. We observe that the sketch-based approach is more expressive, easier to implement, and easier to optimize than existing AutoML frameworks. Our initial results are very promising. Our approach uses fewer resources and still produces comparable results to existing techniques.

Wed 11 Nov
Times are displayed in time zone: (UTC) Coordinated Universal Time change

17:30 - 17:32
Talk
Research Papers
Jose CambroneroMassachusetts Institute of Technology, USA, Jürgen CitoTU Wien and MIT, Martin RinardMassachusetts Institute of Technology, USA
DOI
17:33 - 17:34
Talk
Visions and Reflections
Anh Nguyen-DucUniversity of South Eastern Norway, Pekka AbrahamssonUniversity of Jyväskylä
DOI
17:35 - 17:36
Talk
Research Papers
SiminChen University of Texas at Dallas, USA, Soroush BateniUniversity of Texas at Dallas, USA, Sampath GrandhiUniversity of Texas at Dallas, USA, Xiaodi LiUniversity of Texas at Dallas, USA, Cong LiuUniversity of Texas at Dallas, USA, Wei YangUniversity of Texas at Dallas, USA
DOI
17:37 - 17:38
Talk
Research Papers
Rangeet PanIowa State University, USA, Hridesh RajanIowa State University, USA
DOI Media Attached
17:39 - 17:40
Talk
Student Research Competition
Joshua GisiNorth Dakota State University, USA
DOI
17:41 - 18:00
Talk
Paper Presentations
Jose CambroneroMassachusetts Institute of Technology, USA, Rangeet PanIowa State University, USA, Simin Chen, Wei YangUniversity of Texas at Dallas, USA, M: John-Paul OreNorth Carolina State University