Zobrazeno 1 - 10
of 42
pro vyhledávání: '"Torres, Mercedes Torres"'
Publikováno v:
526(2), 2023, 1742
Citizen science is gaining popularity as a valuable tool for labelling large collections of astronomical images by the general public. This is often achieved at the cost of poorer quality classifications made by amateur participants, which are usuall
Externí odkaz:
http://arxiv.org/abs/2302.00366
Autor:
Kumar, Aayush, Mase, Jimiama Mafeni, Rengasamy, Divish, Rothwell, Benjamin, Torres, Mercedes Torres, Winkler, David A., Figueredo, Grazziela P.
This paper presents an open-source Python toolbox called Ensemble Feature Importance (EFI) to provide machine learning (ML) researchers, domain experts, and decision makers with robust and accurate feature importance quantification and more reliable
Externí odkaz:
http://arxiv.org/abs/2208.04343
Autor:
Mase, Jimiama Mafeni, Pekaslan, Direnc, Agrawal, Utkarsh, Mesgarpour, Mohammad, Chapman, Peter, Torres, Mercedes Torres, Figueredo, Grazziela P.
Commercial driving is a complex multifaceted task influenced by personal traits and external contextual factors, such as weather, traffic, road conditions, etc. Previous intelligent commercial driver-assessment systems do not consider these factors w
Externí odkaz:
http://arxiv.org/abs/2202.09816
Autor:
Mase, Jimiama M., Leesakul, Natalie, Yang, Fan, Figueredo, Grazziela P., Torres, Mercedes Torres
Automatically understanding and recognising human affective states using images and computer vision can improve human-computer and human-robot interaction. However, privacy has become an issue of great concern, as the identities of people used to tra
Externí odkaz:
http://arxiv.org/abs/2111.07344
Mechanistic Interpretation of Machine Learning Inference: A Fuzzy Feature Importance Fusion Approach
Autor:
Rengasamy, Divish, Mase, Jimiama M., Torres, Mercedes Torres, Rothwell, Benjamin, Winkler, David A., Figueredo, Grazziela P.
With the widespread use of machine learning to support decision-making, it is increasingly important to verify and understand the reasons why a particular output is produced. Although post-training feature importance approaches assist this interpreta
Externí odkaz:
http://arxiv.org/abs/2110.11713
Publikováno v:
Neurocomputing, Volume 442, 28 June 2021, Pages 200-208
Few-shot learning focuses on learning a new visual concept with very limited labelled examples. A successful approach to tackle this problem is to compare the similarity between examples in a learned metric space based on convolutional neural network
Externí odkaz:
http://arxiv.org/abs/1904.04339
Advances in sampling schemes for Markov jump processes have recently enabled multiple inferential tasks. However, in statistical and machine learning applications, we often require that these continuous-time models find support on structured and infi
Externí odkaz:
http://arxiv.org/abs/1806.02458
Autor:
Rengasamy, Divish, Mase, Jimiama M., Kumar, Aayush, Rothwell, Benjamin, Torres, Mercedes Torres, Alexander, Morgan R., Winkler, David A., Figueredo, Grazziela P.
Publikováno v:
In Neurocomputing 28 October 2022 511:163-174
Publikováno v:
In Expert Systems With Applications 1 September 2021 177
Autor:
Valstar, Michel, Gratch, Jonathan, Schuller, Bjorn, Ringeval, Fabien, Lalanne, Denis, Torres, Mercedes Torres, Scherer, Stefan, Stratou, Guiota, Cowie, Roddy, Pantic, Maja
The Audio/Visual Emotion Challenge and Workshop (AVEC 2016) "Depression, Mood and Emotion" will be the sixth competition event aimed at comparison of multimedia processing and machine learning methods for automatic audio, visual and physiological dep
Externí odkaz:
http://arxiv.org/abs/1605.01600