Active Learning of Self-concordant like Multi-index Functions

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This work proposes a decentralized architecture, where individual agents aim at solving a classification problem while observing streaming features of different dimensions and arising from possibly different distributions. In the context of social learning ...

In superstructure optimization of processes and energy systems, the design space is defined as the combination of unit considerations, process conditions and model parameters that might be subjected to uncertainty. Most of the time, decision makers are not ...

Systems theory defines leverage points as places to intervene in order to change a system. Points with high impact on system behavior are notoriously hard to act upon, and indeed most policy intervention is based at the lowest level (#12 in Donella Meadows ...

Inclusive teaching is the intentional practice of recognising biases, working to mitigate their impact, and ensuring that students have equitable learning opportunities. In addition to improving students' sense of belonging and self efficacy, inclusive tea ...

Computational thinking (CT) skills are becoming increasingly relevant for future professionals across all domains, beyond computer science (CS). As such, an increasing number of bachelor and masters programs outside of the computer science discipline integ ...

Supplementary files containing datasets needed to reproduce the results of the manuscript "Generative machine learning produces kinetic models that accurately characterize intracellular metabolic states" by S. Choudhury et al. The code to use with these da ...

Addressing the complex challenges of sustainability demands for good teamwork abilities for future technicians and engineers. In our three institutions we adopted project-based learning to facilitate the development of these skills – but is this enough? Si ...

Occupant behavior, defined as the presence and energy-related actions of occupants, is today known as a key driver of building energy use. Closing the gap between what is provided by building energy systems and what is actually needed by occupants requires ...

Data redundancy has been one of the most important problems in data-intensive applications such as data mining and machine learning. Removing data redundancy brings many benefits in efficient data updating, effective data storage, and error-free query proc ...

One of the many purposes for which social robots are designed is education, and there have been many attempts to systematize their potential in this field. What these attempts have in common is the recognition that learning can be supported in a variety of ...

Learning from Demonstration permits non-expert users to easily and intuitively reprogram robots. Among approaches embracing this paradigm, probabilistic movement primitives (ProMPs) are a well-established and widely used method to learn trajectory distribu ...

A shift from fossil-based energy and products to more sustainable alternatives is essential to reduce greenhouse gas emissions and associated climate change impacts. Biomass represents a promising alternative for providing fuels and carbon-based products w ...

In Process Systems Engineering, computationally-demanding models are frequent and plentiful. Handling such complexity in an optimization framework in a fast and reliable way is essential, not only for generating meaningful solutions but also for providing ...

This book provides evidence-informed and practical advice on how to design, teach, and facilitate hands-on, experiential learning in practical higher education settings. With rich case studies and carefully considered analysis tasks, all underpinned by res ...

A novel technique based on machine learning is introduced to reconstruct the decays of highly Lorentz boosted particles. Using an end-to-end deep learning strategy, the technique bypasses existing rule-based particle reconstruction methods typically used i ...

Designing and implementing online or digital learning material is a demanding task for teachers. This is even more the case when this material is used for more engaged forms of learning, such as inquiry learning. In this article, we give an informed accoun ...

Orchestrating technology-enhanced learning is a difficult task, especially in demanding pedagogical approaches like inquiry-based learning (IBL). To foster effective teacher adoption, both the complexity of designing IBL activities and the uncertainty abou ...

Over the past few decades, the debates have shifted from whether to how Computer Science (CS) should be introduced into formal education. Given the diverse ways to introduce CS into formal education, and the struggles many countries have faced, considerabl ...

Correspondence pruning aims to correctly remove false matches (outliers) from an initial set of putative correspondences. The pruning process is challenging since putative matches are typically extremely unbalanced, largely dominated by outliers, and the r ...

Visual impairment can affect a student's ability to learn since their concept development when interacting with educational material is being limited. Learning activities based on images and visually rich content are mainstream learning methods, where faci ...

Active Learning of Self-concordant like Multi-index Functions

Chattez avec Graph Search

Learning From Heterogeneous Data Based on Social Interactions Over Graphs

Active learning for multi-objective optimization of processes and energy systems

Action Levers towards Sustainable Wellbeing: Re-Thinking Negative Emissions, Sufficiency, Deliberative Democracy

Inclusive engineering classrooms: student teaching assistants' perspectives

Promoting Computational Thinking Skills in Non-Computer Science Students Gamifying Computational Notebooks to Increase Student Engagement

Supplementary datasets for the manuscript "Generative machine learning produces kinetic models that accurately characterize intracellular metabolic states" -Part 2

FROM GROUP WORK TO TEAM WORK: COMPARATIVE ANALYSIS IN THREE EUROPEAN INSTITUTIONS

Reinforcement Learning for the occupant-centric operation of building energy systems: Theoretical and experimental investigations

Validating functional redundancy with mixed generative adversarial networks

Social/dialogical roles of social robots in supporting children's learning of language and literacy-A review and analysis of innovative roles

Active Learning of Bayesian Probabilistic Movement Primitives

Decision support for the design of integrated biorefineries

A combined genetic algorithm and active learning approach to build and test surrogate models in Process Systems Engineering

Facilitating Experiential Learning in Higher Education Teaching and Supervising in Labs, Fieldwork, Studios, and Projects

Reconstruction of decays to merged photons using end-to-end deep learning with domain continuation in the CMS detector

Understanding teacher design practices for digital inquiry-based science learning: the case of Go-Lab

ADA for IBL: Lessons Learned in Aligning Learning Design and Analytics for Inquiry-Based Learning Orchestration

Co-constructing an Effective, Sustainable and Scalable Primary School Computer Science Curricular Reform

Progressive Correspondence Pruning by Consensus Learning

Comic Based Learning for Students with Visual Impairments