This dissertation explores techniques that synthesize and generate program fragments and test inputs. The main goal of these techniques is to improve and support automation in program synthesis and test input generation. This is important because performin ...
In this paper, we propose reduced basis multiscale finite element methods (RB-MsFEM) for elliptic problems with highly oscillating coefficients. The method is based on multiscale finite element methods with local test functions that encode the oscillatory ...
Society for Industrial and Applied Mathematics2015
Nowadays, business and scientific applications accumulate data at an increasing pace. This growth of information has already started to outgrow the capabilities of database management systems (DBMS). In a typical DBMS usage scenario, the user should define ...
Deep learning presents notorious computational challenges. These challenges in- clude, but are not limited to, the non-convexity of learning objectives and estimat- ing the quantities needed for optimization algorithms, such as gradients. While we do not a ...
Functional programming (FP) is regularly touted as the way forward for bringing parallel, concurrent, and distributed programming to the mainstream. The popularity of the rationale behind this viewpoint (immutable data transformed by function application) ...
Systems code is often written in low-level languages like C/C++, which offer many benefits but also delegate memory management to programmers. This invites memory safety bugs that attackers can exploit to divert control flow and compromise the system. Depl ...
Probabilistic programming is a powerful high-level paradigm for probabilistic modeling and inference. We present Odds, a small domain-specific language (DSL) for probabilistic programming, embedded in Scala. Odds provides first-class support for random var ...