Tag Archives: Optimization
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 We ﬁrst introduce a novel modeling framework, called linear coupled component automata (LCCA), to facilitate the modeling of discrete-continuous dynamical systems with piecewise constant derivatives. Second, we provide a procedure for transforming models in this framework to mixed-integer linear … Continue reading
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.