RankNEAT: Outperforming Stochastic Gradient Search in Preference Learning Tasks

14 April 2022

Papers citing "RankNEAT: Outperforming Stochastic Gradient Search in Preference Learning Tasks"

7 / 7 papers shown

Title
Towards General Models of Player Experience: A Study Within Genres Dávid Melhárt Antonios Liapis Georgios N. Yannakakis 50 16 0 03 Oct 2021
The Pixels and Sounds of Emotion: General-Purpose Representations of Arousal in Games Konstantinos Makantasis Antonios Liapis Georgios N. Yannakakis 46 30 0 26 Jan 2021
An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale Alexey Dosovitskiy Lucas Beyer Alexander Kolesnikov Dirk Weissenborn Xiaohua Zhai ... Matthias Minderer G. Heigold Sylvain Gelly Jakob Uszkoreit N. Houlsby ViT 555 40,739 0 22 Oct 2020
Eigen-CAM: Class Activation Map using Principal Components Mohammed Bany Muhammad M. Yeasin 50 342 0 01 Aug 2020
From Pixels to Affect: A Study on Games and Player Experience Konstantinos Makantasis Antonios Liapis Georgios N. Yannakakis 30 35 0 04 Jul 2019
On the Relationship Between the OpenAI Evolution Strategy and Stochastic Gradient Descent Xingwen Zhang Jeff Clune Kenneth O. Stanley 57 57 0 18 Dec 2017
Three Factors Influencing Minima in SGD Stanislaw Jastrzebski Zachary Kenton Devansh Arpit Nicolas Ballas Asja Fischer Yoshua Bengio Amos Storkey 76 463 0 13 Nov 2017