Markov logic networks (MLNs) are a statistical relational model that consists of weighted firstorder clauses and generalizes first-order logic and Markov networks. The current sta...
This paper examines high dimensional regression with noise-contaminated input and output data. Goals of such learning problems include optimal prediction with noiseless query poin...
This paper presents a novel framework called proto-reinforcement learning (PRL), based on a mathematical model of a proto-value function: these are task-independent basis function...
Mutants are automatically-generated, possibly faulty variants of programs. The mutation adequacy ratio of a test suite is the ratio of non-equivalent mutants it is able to identif...
Akbar Siami Namin, James H. Andrews, Duncan J. Mur...
This paper presents a specification-based approach for systematic testing of products from a software product line. Our approach uses specifications given as formulas in Alloy, a ...
Engin Uzuncaova, Daniel Garcia, Sarfraz Khurshid, ...