Browsing by Author "Van Der Schaar, M."
Now showing items 1-6 of 6
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Adaptive ensemble learning with confidence bounds for personalized diagnosis
Tekin, Cem; Yoon, J.; Van Der Schaar, M. (AAAI Press, 2016)With the advances in the field of medical informatics, automated clinical decision support systems are becoming the de facto standard in personalized diagnosis. In order to establish high accuracy and confidence in ... -
Big-data streaming applications scheduling based on staged multi-armed bandits
Kanoun, K.; Tekin, C.; Atienza, D.; Van Der Schaar, M. (Institute of Electrical and Electronics Engineers, 2016)Several techniques have been recently proposed to adapt Big-Data streaming applications to existing many core platforms. Among these techniques, online reinforcement learning methods have been proposed that learn how to ... -
Conservative policy construction using variational autoencoders for logged data with missing values
Abroshan, M.; Yip, K. H.; Tekin, Cem; Van Der Schaar, M. (Institute of Electrical and Electronics Engineers Inc., 2022-01-10)In high-stakes applications of data-driven decision-making such as healthcare, it is of paramount importance to learn a policy that maximizes the reward while avoiding potentially dangerous actions when there is uncertainty. ... -
Feedback adaptive learning for medical and educational application recommendation
Tekin, Cem; Elahi, Sepehr; Van Der Schaar, M. (IEEE, 2020)Recommending applications (apps) to improve health or educational outcomes requires long-term planning and adaptation based on the user feedback, as it is imperative to recommend the right app at the right time to improve ... -
Jamming bandits-a novel learning method for optimal jamming
Amuru, S.; Tekin, C.; Van Der Schaar, M.; Buehrer, R.M. (Institute of Electrical and Electronics Engineers Inc., 2016)Can an intelligent jammer learn and adapt to unknown environments in an electronic warfare-type scenario? In this paper, we answer this question in the positive, by developing a cognitive jammer that adaptively and optimally ... -
A non-atochastic learning approach to energy efficient mobility management
Shen, C.; Tekin, C.; Van Der Schaar, M. (Institute of Electrical and Electronics Engineers Inc., 2016)Energy efficient mobility management is an important problem in modern wireless networks with heterogeneous cell sizes and increased nodes densities. We show that optimization-based mobility protocols cannot achieve long-Term ...