Ground truthing from multi-rater labeling with three-way decision and possibility theory

The three-way-in and three-way-out framework to treat and exploit ambiguity in data

(2020) Andrea Campagner et al.   INTERNATIONAL JOURNAL OF APPROXIMATE REASONING

The Elephant in the Machine: Proposing a New Metric of Data Reliability and its Application to a Medical Case to Assess Classification Reliability

(2020) Federico Cabitza et al.   Applied Sciences-Basel

The elephant in the record: On the multiplicity of data recording work

(2019) Federico Cabitza et al.   Health Informatics Journal

Droplet Microfluidics: Coding of Experimental Conditions in Microfluidic Droplet Assays Using Colored Beads and Machine Learning Supported Image Analysis (Small 4/2019)

(2019) Carl-Magnus Svensson et al.   Small

Fuzzy Sets in Data Analysis: From Statistical Foundations to Machine Learning

(2019) Ines Couso et al.   IEEE Computational Intelligence Magazine

Man against machine: diagnostic performance of a deep learning convolutional neural network for dermoscopic melanoma recognition in comparison to 58 dermatologists

(2018) H A Haenssle et al.   ANNALS OF ONCOLOGY

Naive semi-supervised deep learning using pseudo-label

(2018) Zhun Li et al.   Peer-to-Peer Networking and Applications

Deep-learning-assisted diagnosis for knee magnetic resonance imaging: Development and retrospective validation of MRNet

(2018) Nicholas Bien et al.   PLOS MEDICINE

A cost-sensitive three-way combination technique for ensemble learning in sentiment classification

(2018) Yuebing Zhang et al.   INTERNATIONAL JOURNAL OF APPROXIMATE REASONING

Enhancing Binary Classification by Modeling Uncertain Boundary in Three-Way Decisions

(2017) Yuefeng Li et al.   IEEE TRANSACTIONS ON KNOWLEDGE AND DATA ENGINEERING

Cost-sensitive sequential three-way decision modeling using a deep neural network

(2017) Huaxiong Li et al.   INTERNATIONAL JOURNAL OF APPROXIMATE REASONING

Three-way concept learning based on cognitive operators: An information fusion viewpoint

(2017) Chenchen Huang et al.   INTERNATIONAL JOURNAL OF APPROXIMATE REASONING

Dermatologist-level classification of skin cancer with deep neural networks

(2017) Andre Esteva et al.   NATURE

A solution to the single-question crowd wisdom problem

(2017) Dražen Prelec et al.   NATURE

Tri-partition cost-sensitive active learning through kNN

(2017) Fan Min et al.   SOFT COMPUTING

Decision-theoretic rough set model of multi-source decision systems

(2017) Binbin Sang et al.   International Journal of Machine Learning and Cybernetics

The aggregation of multiple three-way decision spaces

(2016) Bao Qing Hu et al.   KNOWLEDGE-BASED SYSTEMS

Automated Classification of Circulating Tumor Cells and the Impact of Interobsever Variability on Classifier Training and Performance

(2015) Carl-Magnus Svensson et al.   Journal of Immunology Research

Automated detection of circulating tumor cells with naive Bayesian classifiers

(2014) Carl-Magnus Svensson et al.   CYTOMETRY PART A

Learning from imprecise and fuzzy observations: Data disambiguation through generalized loss minimization

(2013) Eyke Hüllermeier   INTERNATIONAL JOURNAL OF APPROXIMATE REASONING

Statistical reasoning with set-valued information: Ontic vs. epistemic views

(2013) Inés Couso et al.   INTERNATIONAL JOURNAL OF APPROXIMATE REASONING

Tapping into the Wisdom of the Crowd--with Confidence

(2012) R. Hertwig   SCIENCE

Maximum likelihood estimation from fuzzy data using the EM algorithm

(2011) Thierry Denœux   FUZZY SETS AND SYSTEMS

Three-way decisions with probabilistic rough sets

(2009) Yiyu Yao   INFORMATION SCIENCES

Lung Cancer: Interobserver Agreement on Interpretation of Pulmonary Findings at Low-Dose CT Screening

(2007) David S. Gierada et al.   RADIOLOGY