Tag Archives: Types
Abstract There has been great interest in creating probabilistic programming languages to simplify the coding of statistical tasks; however, there still does not exist a formal language that simultaneously provides (1) continuous probability distributions, (2) the ability to naturally express … Continue reading
Thanks to Rich Vuduc for inviting me to give a talk at CScADS. Autotuning is an approach for generating efficient code for high performance computing. I’ll try to summarize how my PL work can contribute to and benefit from this … Continue reading
Here are the abstract and slides for my talk at IBM PL Day. Title: Mechanizing Optimization and Statistics Abstract: Scientific and engineering investigations are formalized most often in the language of numerical mathematics. The tools supporting this are numerous but … Continue reading
Abstract and slides are here.
Abstract When solving machine learning problems, there is currently little automated support for easily experimenting with alternative statistical models or solution strategies. This is because this activity often requires expertise from several diﬀerent ﬁelds (e.g., statistics, optimization, linear algebra), and … Continue reading
Abstract Mathematical programs (MPs) are a class of constrained optimization problems that include linear, mixed-integer, and disjunctive programs. Strategies for solving MPs rely heavily on various transformations between these subclasses, but most are not automated because MP theory does not … Continue reading
See you in Madrid! Paper details are here.
Abstract Often, it is very difficult to pose a model for a system even after the system is conceptually understood. The reason is the mathematical languages we employ have few forms of expression. We define more expressive languages, first for … Continue reading
Thanks to my great advisors Robert Harper and Ignacio Grossmann. Read all about it here.