no code implementations • 26 Sep 2023 • Wan-Duo Kurt Ma, Muhammad Ghifary, J. P. Lewis, Byungkuk Choi, Haekwang Eom
This paper describes FDLS (Facial Deep Learning Solver), which is Weta Digital's solution to these challenges.
2 code implementations • 12 Jul 2016 • Muhammad Ghifary, W. Bastiaan Kleijn, Mengjie Zhang, David Balduzzi, Wen Li
In this paper, we propose a novel unsupervised domain adaptation algorithm based on deep learning for visual object recognition.
no code implementations • 6 Feb 2016 • David Balduzzi, Muhammad Ghifary
This paper imports ideas from physics and functional programming into RNN design to provide guiding principles.
no code implementations • 15 Oct 2015 • Muhammad Ghifary, David Balduzzi, W. Bastiaan Kleijn, Mengjie Zhang
We propose Scatter Component Analyis (SCA), a fast representation learning algorithm that can be applied to both domain adaptation and domain generalization.
Ranked #7 on Domain Adaptation on Office-Caltech
no code implementations • 10 Sep 2015 • David Balduzzi, Muhammad Ghifary
Firstly, we present a temporal-difference based method for learning the gradient of the value-function.
3 code implementations • ICCV 2015 • Muhammad Ghifary, W. Bastiaan Kleijn, Mengjie Zhang, David Balduzzi
The problem of domain generalization is to take knowledge acquired from a number of related domains where training data is available, and to then successfully apply it to previously unseen domains.
no code implementations • 21 Sep 2014 • Muhammad Ghifary, W. Bastiaan Kleijn, Mengjie Zhang
We propose a simple neural network model to deal with the domain adaptation problem in object recognition.