Deepak Vijaykeerthy

Learn More
We show how to automatically synthesize probabilistic programs from real-world datasets. Such a synthesis is feasible due to a combination of two techniques: (1) We borrow the idea of ``sketching'' from synthesis of deterministic programs, and allow the programmer to write a skeleton program with ``holes''. Sketches enable the programmer(More)
Unlike traditional programs (such as operating systems or word processors) which have large amounts of code, machine learning tasks use programs with relatively small amounts of code (written in machine learning libraries), but voluminous amounts of data. Just like developers of traditional programs debug errors in their code, developers of machine learning(More)
  • 1