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Leveraging Semi-Supervised Learning for Fairness using Neural Networks.

V. Noroozi, S. Bahaadini, S. Sheikhi, N. Mojab, and P. Yu. CoRR, (2019)

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Practical Newton-Type Distributed Learning using Gradient Based Approximations.S. Sheikhi. CoRR, (2019)Recognizing the Visual Focus of Attention for Human Robot Interaction.S. Sheikhi, and J. Odobez. HBU, volume 7559 of Lecture Notes in Computer Science, page 99-112. Springer, (2012)Who Will Get the Grant?: A Multimodal Corpus for the Analysis of Conversational Behaviours in Group Interviews.C. Oertel, K. Mora, S. Sheikhi, J. Odobez, and J. Gustafson. UM3I@ICMI, page 27-32. ACM, (2014)Combining dynamic head pose-gaze mapping with the robot conversational state for attention recognition in human-robot interactions.S. Sheikhi, and J. Odobez. Pattern Recognition Letters, (2015)Evaluation of Background Subtraction Methods.S. Panahi, S. Sheikhi, S. Hadadan, and N. Gheissari. DICTA, page 357-364. IEEE Computer Society, (2008)Leveraging Semi-Supervised Learning for Fairness using Neural Networks.V. Noroozi, S. Bahaadini, S. Sheikhi, N. Mojab, and P. Yu. CoRR, (2019)The vernissage corpus: a conversational human-robot-interaction dataset.D. Jayagopi, S. Sheikhi, D. Klotz, J. Wienke, J. Odobez, S. Wrede, V. Khalidov, L. Nyugen, B. Wrede, and D. Gatica-Perez. HRI, page 149-150. IEEE/ACM, (2013)Leveraging the robot dialog state for visual focus of attention recognition.S. Sheikhi, V. Khalidov, D. Klotz, B. Wrede, and J. Odobez. ICMI, page 107-110. ACM, (2013)Context aware addressee estimation for human robot interaction.S. Sheikhi, D. Jayagopi, V. Khalidov, and J. Odobez. GazeIn@ICMI, page 1-6. ACM, (2013)Investigating the midline effect for visual focus of attention recognition.S. Sheikhi, and J. Odobez. ICMI, page 221-224. ACM, (2012)

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Leveraging Semi-Supervised Learning for Fairness using Neural Networks.

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copydeleteadd this publication to your clipboardcommunity posthistory of this postURLDOIBibTeXEndNoteAPAChicagoDIN 1505HarvardMSOffice XML Leveraging Semi-Supervised Learning for Fairness using Neural Networks.

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Leveraging Semi-Supervised Learning for Fairness using Neural Networks.