134 citations · 217 across the 13 of their papers we have counts for
24 papers
Predicting Driver Self-Reported Stress by Analyzing the Road Scene
Cristina Bustos, Neska Elhaouij, Albert Sole-Ribalta +3
Several studies have shown the relevance of biosignals in driver stress recognition. In this work, we examine something important that has been less frequently explored: We develop…
Personalized Federated Deep Learning for Pain Estimation From Face Images
Ognjen Rudovic, Nicolas Tobis, Sebastian Kaltwang +4
Standard machine learning approaches require centralizing the users' data in one computer or a shared database, which raises data privacy and confidentiality concerns. Therefore, l…
openXDATA: A Tool for Multi-Target Data Generation and Missing Label Completion
Felix Weninger, Yue Zhang, Rosalind W. Picard
A common problem in machine learning is to deal with datasets with disjoint label spaces and missing labels. In this work, we introduce the openXDATA tool that completes the missin…
Characterizing Sources of Uncertainty to Proxy Calibration and Disambiguate Annotator and Data Bias
Asma Ghandeharioun, Brian Eoff, Brendan Jou +1
Supporting model interpretability for complex phenomena where annotators can legitimately disagree, such as emotion recognition, is a challenging machine learning task. In this wor…
Hierarchical Reinforcement Learning for Open-Domain Dialog
Abdelrhman Saleh, Natasha Jaques, Asma Ghandeharioun +2
Open-domain dialog generation is a challenging problem; maximum likelihood training can lead to repetitive outputs, models have difficulty tracking long-term conversational goals,…
Pain Detection with fNIRS-Measured Brain Signals: A Personalized Machine Learning Approach Using the Wavelet Transform and Bayesian Hierarchical Modeling with Dirichlet Process Priors
Daniel Lopez-Martinez, Ke Peng, Arielle Lee +2
Currently self-report pain ratings are the gold standard in clinical pain assessment. However, the development of objective automatic measures of pain could substantially aid pain…