Our understanding of learning—what it is, where it takes place, and who enables it—is changing and so too are our strategies for promoting it. In 2005, Harvard Family Research Project introduced the concept of complementary learning—the idea that integrating school and nonschool supports in an aligned and systemic way can better ensure learning and positive development for all children and yout...

There is a fundamental discrepancy between the targeted and actual users of current analytics frameworks. Most systems are designed for the challenges of the Googles and Facebooks of the world— petabytes of data distributed across large cloud deployments consisting of thousands of cheap commodity machines. Yet, the vast majority of users operate clusters ranging from a few to a few dozen nodes,...

Recently, deep learning based clustering methods are shown superior to traditional ones by jointly conducting representation learning and clustering. These methods rely on the assumptions that the number of clusters is known, and that there is one single partition over the data and all attributes define that partition. However, in real-world applications, prior knowledge of the number of cluste...

A new method for image clustering with density maps derived from Self-Organizing Maps (SOM) is proposed together with a clarification of learning processes during a construction of clusters. It is found that the proposed SOM based image clustering method shows much better clustered result for both simulation and real satellite imagery data. It is also found that the separability among clusters ...

The current Learning Management Systems used in e-learning lack intelligent mechanisms which can be used by an instructor to group learners during an online group task based on the learners‟ collaboration competence level. In this paper, we discuss a novel approach for grouping students in an online learning group task based on individual learners‟ collaboration competence level. We demonstrate...

Resource allocation in computing clusters is traditionally centralized, which limits the cluster scale. Effective resource allocation in a network of computing clusters may enable building larger computing infrastructures. We consider this problem as a novel application for multiagent learning (MAL). We propose a MAL algorithm and apply it for optimizing online resource allocation in cluster ne...

We investigate a general parametric model of adaptive learning. The model includes most of the adaptive learning procedures studied in the literature where agents optimize given their ranking over actions, perhaps allowing for experimentation. It provides a convenient parametric framework to analyze experimental data and to compare the performance of previously proposed learning hypotheses. We ...

Small and medium size enterprises (SMEs) lack an adequately skilled workforce and managers, since university education generally focuses on large enterprises and their needs. Complementary skills needed by SMEs have been of lesser interest even though several approaches, methods and environments could be utilized. For example, enterprise resource planning systems, business simulation games and ...

Students learned toy assembly sequences presented in picture, text, or one of three multimedia formats, and completed order verification, recall, and object assembly tasks. Experiment 1 compared repetitious (i.e. dual format presentations each conveying similar information) with complementary (i.e. dual format presentations each conveying different information) multimedia presentations. Repetit...