Increasing non-recurring engineering (NRE) and mask costs are making it harder to turn to hardwired Application Specific Integrated Circuit (ASIC) solutions for high performance a...
In this paper we study the topic of CBR systems learning from observations in which those observations can be represented as stochastic policies. We describe a general framework wh...
Kellen Gillespie, Justin Karneeb, Stephen Lee-Urba...
Abstract. We propose a flexible method for verifying the security of ML programs that use cryptography and recursive data structures. Our main applications are X.509 certificate ch...
Our research explores the possibilities for factoring culture into user models, working towards cultural adaptivity in the semantic web. The aim is to represent the user’s positi...
Reinforcement learning problems are commonly tackled with temporal difference methods, which use dynamic programming and statistical sampling to estimate the long-term value of ta...