Binary classification is a core data mining task. For large datasets or real-time applications, desirable classifiers are accurate, fast, and need no parameter tuning. We presen...
Self-adjusting computation enables writing programs that can automatically and efficiently respond to changes to their data (e.g., inputs). The idea behind the approach is to stor...
This paper considers the Valiant framework as it is applied to the task of learning logical concepts from random examples. It is argued that the current interpretation of this Val...
Parameters of a program’s runtime environment such as the machine architecture and operating system largely determine whether a vulnerability can be exploited. For example, the m...
We describe a new automatic static analysis for determining upper-bound functions on the use of quantitative resources for strict, higher-order, polymorphic, recursive programs de...
Steffen Jost, Hans-Wolfgang Loidl, Kevin Hammond, ...