We address the problem of testing and debugging concurrent, distributed Erlang applications. In concurrent programs, race conditions are a common class of bugs and are very hard t...
Koen Claessen, Michal Palka, Nicholas Smallbone, J...
Abstract— We propose a novel online framework for detecting moving shadows in video sequences using statistical learning techniques. In this framework, Support Vector Machines ar...
In the traditional setting, text categorization is formulated as a concept learning problem where each instance is a single isolated document. However, this perspective is not appr...
The purpose of the current study was to test whether we could create a system where students can learn by teaching a live machine-learning agent. SimStudent is a computer agent tha...
Noboru Matsuda, Victoria Keiser, Rohan Raizada, Ga...
This paper describes the concepts of TEA, a flexible tool that supports user tests by automating repetitive tasks and collecting data of user inputs and actions. TEA was specifica...