Search Results for author: María Pérez-Ortiz

Found 8 papers, 3 papers with code

A Toolbox for Modelling Engagement with Educational Videos

no code implementations30 Dec 2023 Yuxiang Qiu, Karim Djemili, Denis Elezi, Aaneel Shalman, María Pérez-Ortiz, Emine Yilmaz, John Shawe-Taylor, Sahan Bulathwela

With the advancement and utility of Artificial Intelligence (AI), personalising education to a global population could be a cornerstone of new educational systems in the future.

TrueLearn: A Python Library for Personalised Informational Recommendations with (Implicit) Feedback

no code implementations20 Sep 2023 Yuxiang Qiu, Karim Djemili, Denis Elezi, Aaneel Shalman, María Pérez-Ortiz, Sahan Bulathwela

This work describes the TrueLearn Python library, which contains a family of online learning Bayesian models for building educational (or more generally, informational) recommendation systems.

Recommendation Systems

Comparing the carbon costs and benefits of low-resource solar nowcasting

no code implementations10 Oct 2022 Ben Dixon, María Pérez-Ortiz, Jacob Bieker

Solar PV yield nowcasting is used to help anticipate peaks and troughs in demand to support grid integration.

Semantic TrueLearn: Using Semantic Knowledge Graphs in Recommendation Systems

no code implementations8 Dec 2021 Sahan Bulathwela, María Pérez-Ortiz, Emine Yilmaz, John Shawe-Taylor

In informational recommenders, many challenges arise from the need to handle the semantic and hierarchical structure between knowledge areas.

Knowledge Graphs Recommendation Systems

Could AI Democratise Education? Socio-Technical Imaginaries of an EdTech Revolution

no code implementations3 Dec 2021 Sahan Bulathwela, María Pérez-Ortiz, Catherine Holloway, John Shawe-Taylor

Artificial Intelligence (AI) in Education has been said to have the potential for building more personalised curricula, as well as democratising education worldwide and creating a Renaissance of new ways of teaching and learning.

A PAC-Bayesian Perspective on Structured Prediction with Implicit Loss Embeddings

1 code implementation7 Dec 2020 Théophile Cantelobre, Benjamin Guedj, María Pérez-Ortiz, John Shawe-Taylor

Many practical machine learning tasks can be framed as Structured prediction problems, where several output variables are predicted and considered interdependent.

Generalization Bounds Structured Prediction

Tighter risk certificates for neural networks

1 code implementation25 Jul 2020 María Pérez-Ortiz, Omar Rivasplata, John Shawe-Taylor, Csaba Szepesvári

In the context of probabilistic neural networks, the output of training is a probability distribution over network weights.

Model Selection

Predicting Engagement in Video Lectures

1 code implementation31 May 2020 Sahan Bulathwela, María Pérez-Ortiz, Aldo Lipani, Emine Yilmaz, John Shawe-Taylor

The explosion of Open Educational Resources (OERs) in the recent years creates the demand for scalable, automatic approaches to process and evaluate OERs, with the end goal of identifying and recommending the most suitable educational materials for learners.

Recommendation Systems

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