Active Learning of Self-concordant like Multi-index Functions

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Laser material processing (LMP) has revolutionized modern manufacturing, emerging as a cornerstone technology valued for its precision, speed, and versatility, especially in high-stakes sectors like aerospace, automotive, and medical device production. Des ...

Demographic fairness or equity is a crucial aspect of machine learning models, particularly in critical domains such as healthcare, where errors can have severe consequences. A fair model avoids making distinctions between groups with different sensitive o ...

Dynamic aperture is an important concept for the study of non-linear beam dynamics in circular accelerators. It describes the extent of the phase-space region where a particle's motion remains bounded over a given number of turns. Understanding the feature ...

Informative sample selection in an active learning (AL) setting helps a machine learning system attain optimum performance with minimum labeled samples, thus reducing annotation costs and boosting performance of computer-aided diagnosis systems in the pres ...

Students learn more when they are actively engaged in the learning process. While hands-on activities, labs and projects are moments when students are active, the learning benefits can be amplified with coaching strategies. This activity will enable studen ...

By 'social learning,' in this article we refer to mechanisms for opinion formation and decision making over graphs and the study of how agents' decisions evolve dynamically through interactions with neighbors and the environment. The study of social learni ...

Our understanding of the generalization capabilities of neural networks (NNs) is still incomplete. Prevailing explanations are based on implicit biases of gradient descent (GD) but they cannot account for the capabilities of models from gradient-free metho ...

This work studies the learning process over social networks under partial and random information sharing. In traditional social learning models, agents exchange full belief information with each other while trying to infer the true state of nature. We stud ...

The sum-of-squares (SOS) approximation method is a technique used in optimization problems to derive lower bounds on the optimal value of an objective function. By representing the objective function as a sum of squares in a feature space, the SOS method t ...

Distributed learning is the key for enabling training of modern large-scale machine learning models, through parallelising the learning process. Collaborative learning is essential for learning from privacy-sensitive data that is distributed across various ...

Conversational tutoring systems (CTSs) offer a promising avenue for individualized learning support, especially in domains like persuasive writing. Although these systems have the potential to enhance the learning process, the specific role of learner cont ...

Accurate human trajectory prediction is crucial for applications such as autonomous vehicles, robotics, and surveillance systems. Yet, existing models often fail to fully leverage the non-verbal social cues human subconsciously communicate when navigating ...

Data-driven approaches based on high-throughput capabilities and machine learning hold promise in revolutionizing human-centred materials discovery for sustainability and decarbonization. This Review examines the strengths and limitations of different trad ...

We study the random binary symmetric perceptron problem, focusing on the behavior of rare high-margin solutions. While most solutions are isolated, we demonstrate that these rare solutions are part of clusters of extensive entropy, heuristically correspond ...

Aging civil infrastructures are closely monitored by engineers for damage and critical defects. As the manual inspection of such large structures is costly and time-consuming, we are working towards fully automating the visual inspections to support the pr ...

Advances in computing have enabled widespread access to pose estimation, creating new sources of data streams. Unlike mock set-ups for data collection, tapping into these data streams through on-device active learning allows us to directly sample from the ...

The paper presents ICAP (interactive, constructive, active and passive) as the theoretical framework to understand the role of informal learning spaces as an active learning tool when students have informal meetings to work on projects. Students in our En ...

The learning process depends on the nature of the learning environment, particularly in the case of open-ended learning environments, where the learning process is considered to be non-linear. In this paper, we report on the findings of employing a multimo ...

The trend towards generalized blended and active learning approaches in engineering education is redefining the requirements and the deployment schemes for digital education platforms. This paper presents a quadriptych techno- pedagogical model highlightin ...

Active Learning of Self-concordant like Multi-index Functions

Chattez avec Graph Search

Toward Autonomous Laser Manufacturing: Solving Key Challenges in Optimization, Monitoring, and Control

Optimizing fairness and utility in healthcare machine learning models

Optimizing Dynamic Aperture Studies with Active Learning

GANDALF: Graph-based transformer and Data Augmentation Active Learning Framework with interpretable features for multi-label chest Xray classification

How to support students to develop coaching and peer teaching skills

Socially Intelligent Networks: A framework for decision making over graphs

Neural Redshift: Random Networks are not Random Functions

Social Opinion Formation and Decision Making Under Communication Trends

Theory and applications of the sum-of-squares technique

Statistical mechanics of deep learning

Optimization Algorithms for Decentralized, Distributed and Collaborative Machine Learning

Evaluating the Impact of Learner Control and Interactivity in Conversational Tutoring Systems for Persuasive Writing

Social-Transmotion: Promptable Human Trajectory Prediction

Human- and machine-centred designs of molecules and materials for sustainability and decarbonization

On the atypical solutions of the symmetric binary perceptron

Active Learning for Imbalanced Civil Infrastructure Data

VL4Pose: Active Learning Through Out-Of-Distribution Detection For Pose Estimation

Work in progress: Imagining / Designing informal spaces for learning

Temporal Pathways to Learning: How Learning Emerges in an Open-ended Collaborative Activity

Integrated Model for Comprehensive Digital Education Platforms