We construct algorithms for deciding essentially any minor-closed parameter, with explicit time bounds. This result strengthens previous results by Robertson and Seymour [1,2], Fr...
We consider programming language aspects of algorithms that operate on data too large to fit into memory. In previous work we have introduced IntML, a functional programming langu...
We define a new model of quantum learning that we call Predictive Quantum (PQ). This is a quantum analogue of PAC, where during the testing phase the student is only required to a...
In today's society, people have very little control over what kinds of personal data are collected and stored by various agencies in both the private and public sectors. We de...
Intelligent desktop assistants could provide more help for users if they could learn models of the users’ workflows. However, discovering desktop workflows is difficult becau...
Jianqiang Shen, Erin Fitzhenry, Thomas G. Dietteri...