In this paper we present an approach for reducing the memory footprint requirement of temporal difference methods in which the set of states is finite. We use case-based generaliza...
Abstract. In computer science methods to aid learning are very imporcause abstract models are used frequently. For this conventional teaching methods do not suffice. We have develo...
Beatrix Braune, Stephan Diehl, Andreas Kerren, Rei...
We consider the problem of learning a finite automaton M of n states with input alphabet X and output alphabet Y when a teacher has helpfully or randomly labeled the states of M u...
Dana Angluin, Leonor Becerra-Bonache, Adrian Horia...
This work introduces a new query inference model that can access data and communicate with a teacher by asking finitely many boolean queries in a language L. In this model the pa...
We present a new family of subgradient methods that dynamically incorporate knowledge of the geometry of the data observed in earlier iterations to perform more informative gradie...