Abstract. We present basic concepts and an outlook on current approaches and techniques of personal learning environments to point out their demands, focussing on recommendations i...
Uwe Kirschenmann, Maren Scheffel, Martin Friedrich...
In order to understand whether conceptual obscurity is truly the reason for the slow uptake of IMS Learning Design (LD), we have initiated an investigation into teachers' unde...
Michael Derntl, Susanne Neumann, Dai Griffiths, Pe...
We study the regret of an online learner playing a multi-round game in a Banach space B against an adversary that plays a convex function at each round. We characterize the minima...
In the present paper, we introduce a variant of Gold-style learners that is not required to infer precise descriptions of the languages in a class, but that must find descriptive ...
We analyze the regret, measured in terms of log loss, of the maximum likelihood (ML) sequential prediction strategy. This "follow the leader" strategy also defines one o...
Multiarmed bandit problem is a typical example of a dilemma between exploration and exploitation in reinforcement learning. This problem is expressed as a model of a gambler playi...
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...
One of the most widely used techniques for data clustering is agglomerative clustering. Such algorithms have been long used across many different fields ranging from computational...
A significant Fourier transform (SFT) algorithm, given a threshold and oracle access to a function f, outputs (the frequencies and approximate values of) all the -significant Fou...