Search results for "Learning"
showing 10 items of 6669 documents
Vectors of Pairwise Item Preferences
2019
Neural embedding has been widely applied as an effective category of vectorization methods in real-world recommender systems. However, its exploration of users’ explicit feedback on items, to create good quality user and item vectors is still limited. Existing neural embedding methods only consider the items that are accessed by the users, but neglect the scenario when a user gives high or low rating to a particular item. In this paper, we propose Pref2Vec, a method to generate vector representations of pairwise item preferences, users and items, which can be directly utilized for machine learning tasks. Specifically, Pref2Vec considers users’ pairwise item preferences as elementary units. …
Artificial Decision Maker Driven by PSO : An Approach for Testing Reference Point Based Interactive Methods
2018
Over the years, many interactive multiobjective optimization methods based on a reference point have been proposed. With a reference point, the decision maker indicates desirable objective function values to iteratively direct the solution process. However, when analyzing the performance of these methods, a critical issue is how to systematically involve decision makers. A recent approach to this problem is to replace a decision maker with an artificial one to be able to systematically evaluate and compare reference point based interactive methods in controlled experiments. In this study, a new artificial decision maker is proposed, which reuses the dynamics of particle swarm optimization f…
Realistic Implementation of the Particle Model for the Visualization of Nanoparticle Precipitation and Growth
2019
An application for visualizing the aggregation of structureless atoms is presented. The application allows us to demonstrate on a qualitative basis, as well as by quantitatively monitoring the aggregate surface/volume ratio, that the enhanced reactivity of nanoparticles can be connected with their large specific surface. It is suggested that, along with the use of geometric analogies, this bottom-up approach can be effective in discussing the enhanced reactivity proprieties of nanoparticles. The application is based on a two-dimensional realistic dynamic model where atoms move because of their thermal and interaction potential energies, and the trajectories are determined by solving numeric…
Challenges for the Teacher's Role in Promoting Productive Knowledge Construction in Computer-Supported Collaborative Learning Contexts
2010
This chapter discusses challenges related to teachers’ pedagogical activities in facilitating productive discussions among students in Computer-Supported Collaborative Learning (CSCL) contexts. In the light of two different cases from secondary-level and higher education contexts, the authors examine how teachers’ pedagogical choices influenced the quality of students’ activity, namely Web-based discussion. The results of our studies indicated that rich moments of collaboration were rare and distributed unequally among the students. The obvious weakness from the perspective of teachers’ pedagogical activities was that in neither of the studies was the students’ interaction in the discussion…
A HOLISTIC MULTI-METHODOLOGY FOR SUSTAINABLE RENOVATION
2019
A review of the barriers for building renovation has revealed a lack of methodologies, which can promote sustainability objectives and assist various stakeholders during the design stage of building renovation/retrofitting projects. The purpose of this paper is to develop a Holistic Multi-methodology for Sustainable Renovation, which aims to deal with complexity of renovation projects. It provides a framework through which to involve the different stakeholders in the design process to improve group learning and group decision-making, and hence make the building renovation design process more robust and efficient. Therefore, the paper discusses the essence of multifaceted barriers in buildin…
Breast Ultra-Sound image segmentation: an optimization approach based on super-pixels and high-level descriptors
2015
International audience; Breast cancer is the second most common cancer and the leading cause of cancer death among women. Medical imaging has become an indispensable tool for its diagnosis and follow up. During the last decade, the medical community has promoted to incorporate Ultra-Sound (US) screening as part of the standard routine. The main reason for using US imaging is its capability to differentiate benign from malignant masses, when compared to other imaging techniques. The increasing usage of US imaging encourages the development of Computer Aided Diagnosis (CAD) systems applied to Breast Ultra-Sound (BUS) images. However accurate delineations of the lesions and structures of the b…
Khmer character recognition using artificial neural network
2014
Character Recognition has become an interesting and a challenge topic research in the field of pattern recognition in recent decade. It has numerous applications including bank cheques, address sorting and conversion of handwritten or printed character into machine-readable form. Artificial neural network including self-organization map and multilayer perceptron network with the learning ability could offer the solution to character recognition problem. In this paper presents Khmer Character Recognition (KCR) system implemented in Matlab environment using artificial neural networks. The KCR system described the utilization of integrated self-organization map (SOM) network and multilayer per…
An optimization approach to segment breast lesions in ultra-sound images using clinically validated visual cues
2015
International audience; As long as breast cancer remains the leading cause of cancer deaths among female population world wide, developing tools to assist radiologists during the diagnosis process is necessary. However, most of the technologies developed in the imaging laboratories are rarely integrated in this assessing process, as they are based on information cues differing from those used by clinicians. In order to grant Computer Aided Diagnosis (CAD) systems with these information cues when performing non-aided diagnosis, better segmentation strategies are needed to automatically produce accurate delineations of the breast structures. This paper proposes a highly modular and flexible f…
A Robust Minimal Learning Machine based on the M-Estimator
2017
In this paper we propose a robust Minimal Learning Machine (R-RLM) for regression problems. The proposed method uses a robust M-estimator to generate a linear mapping between input and output distances matrices of MLM. The R-MLM was tested on one synthetic and three real world datasets that were contaminated with an increasing number of outliers. The method achieved a performance comparable to the robust Extreme Learning Machine (R-RLM) and thus can be seen as a valid alternative for regression tasks on datasets with outliers. peerReviewed
The effect of culture on educational methodologies in international business programs: an application to the iMBA program
2012
As the world becomes global, there are growing needs and opportunities for intercultural exchanges in learning processes. In the context of the Spanish University Strategy for 2015, one of the most important objectives is to increase internationalisation through international postgraduate courses (Spanish Ministry of Education, 2010). Intercultural teaching capabilities are now becoming necessary for better achieving perceived service quality among international students. In the area of business studies, research on pedagogical issues is needed in order to provide recommendations and group management implications. For instance, a challenge for international business programs is dealing with…