no code implementations • 16 Jun 2015 • Wenjie Pei, Hamdi Dibeklioğlu, David M. J. Tax, Laurens van der Maaten
We present a new model for time series classification, called the hidden-unit logistic model, that uses binary stochastic hidden units to model latent structure in the data.
no code implementations • 23 Nov 2017 • Wenjie Pei, Hamdi Dibeklioğlu, Tadas Baltrušaitis, David M. J. Tax
In this paper, we present an end-to-end architecture for age estimation, called Spatially-Indexed Attention Model (SIAM), which is able to simultaneously learn both the appearance and dynamics of age from raw videos of facial expressions.
no code implementations • 23 Jan 2020 • Guangliang Li, Hamdi Dibeklioğlu, Shimon Whiteson, Hayley Hung
Interactive reinforcement learning provides a way for agents to learn to solve tasks from evaluative feedback provided by a human user.
1 code implementation • 26 Aug 2020 • Selim F. Yilmaz, E. Batuhan Kaynak, Aykut Koç, Hamdi Dibeklioğlu, Suleyman S. Kozat
We investigate cross-lingual sentiment analysis, which has attracted significant attention due to its applications in various areas including market research, politics and social sciences.
no code implementations • Journal on Multimodal User Interfaces 2020 • Dersu Giritlioğlu, Burak Mandira, Selim Fırat Yılmaz, Can Ufuk Ertenli, Berhan Faruk Akgür, Merve Kınıklıoğlu, Aslı Gül Kurt, Emre Mutlu, Şeref Can Gürel, Hamdi Dibeklioğlu
Personality analysis is an important area of research in several fields, including psychology, psychiatry, and neuroscience.
no code implementations • Image and Vision Computing 2021 • Süleyman Aslan, Uğur Güdükbay, Hamdi Dibeklioğlu
A novel loss function is employed to enforce the proposed model to give an equivalent importance for each of the personality traits to be estimated through a consistency constraint that keeps the trait-specific errors as close as possible.