One recent approach in developing computer-based learning environments advocates the idea of creating a social context inside the computer. It is claimed that when the learner is engaged into a meaningful dialogue with the software actors his/her learning will benefit. In this paper we concentrate on the collaboration with artificial social actors as peer learners. How ”able” should the learnin...

We study the task of online boosting — combining online weak learners into an online strong learner. While batch boosting has a sound theoretical foundation, online boosting deserves more study from the theoretical perspective. In this paper, we carefully compare the differences between online and batch boosting, and propose a novel and reasonable assumption for the online weak learner. Based o...

We study online boosting, the task of converting any weak online learner into a strong online learner. Based on a novel and natural definition of weak online learnability, we develop two online boosting algorithms. The first algorithm is an online version of boost-by-majority. By proving a matching lower bound, we show that this algorithm is essentially optimal in terms of the number of weak le...

We consider the problem of boosting the accuracy of weak learning algorithms in the agnostic learning framework of Haussler (1992) and Kearns et al. (1992). Known algorithms for this problem (BenDavid et al., 2001; Gavinsky, 2002; Kalai et al. , 2008) follow the same strategy as boosting algorithms in the PAC model: the weak learner is executed on the same target function but over different dis...

This paper describes a method for learner modelling for use within simulation-based learning environments. The goal of the learner modelling system is to provide the learner with advice on discovery learning. The system analyzes the evidence that a learner has generated for a specific hypothesis, assesses whether the learner needs support on the discovery process, and the nature of that support...

Learner preferences of students have been analysed within two modules that have been given in the department of media using Röll’s learner preference model. A qualitative analysis of the results of an online learner preference test based on this model has been conducted. This analysis showed that for the majority of the students the revealed results were valid. Starting from current methods use...

Current pulses are convenient to be actively implemented by a battery management system. However, the short-term features (STF) from current originate various sensors with uneven qualities, which hinder one powerful and strong learner STF for state of health (SOH) estimation. This article, thus, proposes an optimized weak formulation procedure lithium-ion SOH estimation, further enables automat...

We thank the authors for writing a thought-provoking piece that may ruffle the feathers of recent orthodoxies in boosting. We also thank JMLR for publishing this article! Since the late 1990s, boosting has undergone the equivalent of a simultaneous X-ray, fMRI and PET exam, and the common view these days is that boosting is a kind of model fitting. As such, it is subjected to assumptions that a...

We develop a method that can detect humans in a single image based on a new cascaded structure. In our approach, both the rectangle features and 1-D edge-orientation features are employed in the feature pool for weak-learner selection, which can be computed via the integral-image and the integral-histogram techniques, respectively. To make the weak learner more discriminative, Real AdaBoost is ...