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20202022
most citedAdapting User Interfaces with Model-based Reinforcement Learning

90 citations · 222 across the 8 of their papers we have counts for

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cs.HC20225 cited

A Contextual Framework for Adaptive User Interfaces: Modelling the Interaction Environment

Mateusz Dubiel, Bereket Abera Yilma, Kayhan Latifzadeh +1

The interaction context (or environment) is key to any HCI task and especially to adaptive user interfaces (AUIs), since it represents the conditions under which users interact wit…

cs.HC202190 cited

Adapting User Interfaces with Model-based Reinforcement Learning

Kashyap Todi, Gilles Bailly, Luis A. Leiva +1

Adapting an interface requires taking into account both the positive and negative effects that changes may have on the user. A carelessly picked adaptation may impose high costs to…

cs.HC202181 cited

Understanding Visual Saliency in Mobile User Interfaces

Luis A. Leiva, Yunfei Xue, Avya Bansal +4

For graphical user interface (UI) design, it is important to understand what attracts visual attention. While previous work on saliency has focused on desktop and web-based UIs, mo…

cs.HC202119 cited

My Mouse, My Rules: Privacy Issues of Behavioral User Profiling via Mouse Tracking

Luis A. Leiva, Ioannis Arapakis, Costas Iordanou

This paper aims to stir debate about a disconcerting privacy issue on web browsing that could easily emerge because of unethical practices and uncontrolled use of technology. We de…

cs.HC2020

Learning Efficient Representations of Mouse Movements to Predict User Attention

Ioannis Arapakis, Luis A. Leiva

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, wh…

cs.HC202013 cited

Omnis Prædictio: Estimating the Full Spectrum of Human Performance with Stroke Gestures

Luis A. Leiva, Radu-Daniel Vatavu, Daniel Martín-Albo +1

Designing effective, usable, and widely adoptable stroke gesture commands for graphical user interfaces is a challenging task that traditionally involves multiple iterative rounds…