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Found 9 papers, 3 papers with code
Co-Teaching Student-Model through Submission Results of Shared Task
In this research, we propose a scheme to utilize all those systems which participated in the shared tasks.
An experimental framework for designing document structure for users' decision making - An empirical study of recipes
This study proposed the experimental framework to identify useful contents of documents by aggregating lay readers' insights.
HumanACGAN: conditional generative adversarial network with human-based auxiliary classifier and its evaluation in phoneme perception
A DNN-based generator is trained using a human-based discriminator, i. e., humans' perceptual evaluations, instead of the GAN's DNN-based discriminator.
CrowDEA: Multi-view Idea Prioritization with Crowds
We propose an approach, called CrowDEA, which estimates the embeddings of the ideas in the multiple-criteria preference space, the best viewpoint for each idea, and preference criterion for each evaluator, to obtain a set of frontier ideas.
Iterative Machine Teaching without Teachers
In this study, we apply these to iterative machine teaching for estimating the true labels of teaching examples along with student models that are used for teaching.
HumanGAN: generative adversarial network with human-based discriminator and its evaluation in speech perception modeling
To model the human-acceptable distribution, we formulate a backpropagation-based generator training algorithm by regarding human perception as a black-boxed discriminator.
Dual Convolutional Neural Network for Graph of Graphs Link Prediction
Graphs are general and powerful data representations which can model complex real-world phenomena, ranging from chemical compounds to social networks; however, effective feature extraction from graphs is not a trivial task, and much work has been done in the field of machine learning and data mining.
BayesGrad: Explaining Predictions of Graph Convolutional Networks
A possible approach to answer this question is to visualize evidence substructures responsible for the predictions.
