Learning efficient representations of mouse movements to predict user attention

Abstract: Tracking mouse cursor movements can be used to predict user attention on heterogeneous page layouts like SERPs. So far, previous work has relied heavily on handcrafted features, which is a time-consuming approach that often requires domain expertise. We investigate different representations of mouse cursor movements, including time series, heatmaps, and trajectory-based images, to build and contrast both recurrent and convolutional neural networks that can predict user attention to direct displays, such as SERP advertisements. Our models are trained over raw mouse cursor data and achieve competitive performance. We conclude that neural network models should be adopted for downstream tasks involving mouse cursor movements, since they can provide an invaluable implicit feedback signal for re-ranking and evaluation.

25/04/2020

Heuristic Search and Game Playing, Evaluation and Analysis, Heuristic Search and Machine Learning, Meta-Reasoning and Meta-Heuristics

13:51

16/11/2020

Self-Supervised Learning of Scene-Graph Representations for Robotic Sequential Manipulation Planning

Son Nguyen, Ozgur Oguz Uni. of Stuttgart &, Max Planck Inst. for Intelligent Systems and
Valentin Hartmann, Marc Toussaint

Keywords Paper

5:01

06/12/2020

PyGlove: Symbolic Programming for Automated Machine Learning

Daiyi Peng, Xuanyi Dong, Esteban Real and
Mingxing Tan, Yifeng Lu, Gabriel Bender, Hanxiao Liu, Adam Kraft, Chen Liang, Quoc V Le

Ashutosh Adhikari, Eric Yuan, Marc-Alexandre Côté and
Mikuláš Zelinka, Marc-Antoine Rondeau, Romain Laroche, Pascal Poupart, Jian Tang, Adam Trischler, Will Hamilton

Yufei Feng, Fuyu Lv, Binbin Hu and
Fei Sun, Kun Kuang, Yang Liu, Qingwen Liu, Wenwu Ou

gan, game, simulation, video generation, memory, disentangle, interactive

1:01

25/07/2020

Models for code, Differentiable program generator, Combinatorial optimization, Program obfuscation, Adversarial computer programs, Machine Learning (ML) for Programming Languages (PL)/Software Engineering (SE)

6:27

16/11/2020

Shijie Geng, Peng Gao, Moitreya Chatterjee and
Chiori Hori, Jonathan Le Roux, Yongfeng Zhang, Hongsheng Li, Anoop Cherian

biologically plausible, translation invariance, robustness, sequential vision, transsaccadic vision, grid cells, path integration, continual learning, predictive representations, Hebbian learning

11:21

14/06/2020

Markus Wulfmeier, Dushyant Rao, Roland Hafner and
Thomas Lampe, Abbas Abdolmaleki, Tim Hertweck, Michael Neunert, Dhruva Tirumala Bukkapatnam, Noah Siegel, Nicolas Heess, Martin Riedmiller