Results 41 to 50 of about 9,437,008 (290)
Probe microscopy is all you need
Machine Learning: Science and Technology, 2023 We pose that microscopy offers an ideal real-world experimental environment for the development and deployment of active Bayesian and reinforcement learning methods.
Sergei V Kalinin +5 more
doaj +1 more source
A Bayesian Active Learning Approach to Comparative Judgement
CoRR, 2023 Assessment is a crucial part of education. Traditional marking is a source of inconsistencies and unconscious bias, placing a high cognitive load on the assessors. An approach to address these issues is comparative judgement (CJ). In CJ, the assessor is presented with a pair of items and is asked to select the better one.
Andy Gray +3 more
openaire +4 more sources
Efficient utility-based clustering over high dimensional partition spaces [PDF]
, 2009 Because of the huge number of partitions of even a moderately sized dataset, even when Bayes factors have a closed form, in model-based clustering a comprehensive search for the highest scoring (MAP) partition is usually impossible.
Smith, JQ +9 more
core +1 more source
Bayesian Active Distance Metric Learning
CoRR, 2012 Distance metric learning is an important component for many tasks, such as statistical classification and content-based image retrieval. Existing approaches for learning distance metrics from pairwise constraints typically suffer from two major problems.
Liu Yang 0001 +2 more
openaire +3 more sources
Active learning and autonomous learning: an educational experience [PDF]
, 2009 The obtained experience in the active and the autonomous learning tasks execution in the teaching of the subject: Reinforced Concrete Structures and Devices Construction, of the career of Technical Architecture by the Universidad Politécnica de ...
Gómez Soberón, José Manuel Vicente +2 more
core +1 more source
Bayesian Active Learning by Disagreements: A Geometric Perspective
CoRR, 2021 We present geometric Bayesian active learning by disagreements (GBALD), a framework that performs BALD on its core-set construction interacting with model uncertainty estimation. Technically, GBALD constructs core-set on ellipsoid, not typical sphere, preventing low-representative elements from spherical boundaries.
Xiaofeng Cao 0002, Ivor W. Tsang
openaire +2 more sources
Bayesian Active Learning for Sim-to-Real Robotic Perception [PDF]
2022 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), 2022 While learning from synthetic training data has recently gained an increased attention, in real-world robotic applications, there are still performance deficiencies due to the so-called Sim-to-Real gap. In practice, this gap is hard to resolve with only synthetic data.
Jianxiang Feng +3 more
openaire +3 more sources
Hierarchic Bayesian models for kernel learning [PDF]
, 2005 The integration of diverse forms of informative data by learning an optimal combination of base kernels in classification or regression problems can provide enhanced performance when compared to that obtained from any single data source.
Rogers, S. +3 more
core +1 more source
Bayesian active learning of interatomic force field for molecular dynamics simulation of Pt/Ag(111) [PDF]
, 2021 Force field is a central requirement in molecular dynamics (MD) simulation for accurate description of the potential energy landscape and the time evolution of individual atomic motions.
Kai, Xu, Lei, Yan, Bingran, You
core +1 more source
A model of active and significative learning in the resolution of problems [PDF]
, 2009 In this paper we present a description and analysis of an activity held in the Mathematics courses in Engineering at the Universidade de Caxias do Sul. The research was planned taking into account requirements for the training of engineers.
Zanol Sauer, Laurete +2 more
core +1 more source