• Debiased offline evaluation of recommender systems: A weighted-sampling approach 

  Carraro, Diego; Bridge, Derek (Association for Computing Machinery, 2020-03)

  Offline evaluation of recommender systems mostly relies on historical data, which is often biased by many confounders. In such data, user-item interactions are Missing Not At Random (MNAR). Measures of recommender system ...
• Deep Learning Human Activity Recognition 

  Browne, David; Giering, Michael; Prestwich, Steven (Sun SITE Central Europe, 2019-12)

  Human activity recognition is an area of interest in various domains such as elderly and health care, smart-buildings and surveillance, with multiple approaches to solving the problem accurately and efficiently. For many ...
• A multi-sensors wearable system for remote assessment of physiotherapy exercises during ACL rehabilitation 

  Tedesco, Salvatore; Belcastro, Marco; Manzano Torre, Oscar; Torchia, Pasqualino; Alfieri, Davide; Khokhlova, Liudmila; O'Flynn, Brendan (Institute of Electrical and Electronics Engineers (IEEE), 2019-11)

  In this paper, the challenges associated with the design of a novel multi-sensor wearable system for the objective assessment of exercises during lower-limbs rehabilitation are described. The overall system architecture ...
• Monitoring emergency first responders' activities via gradient boosting and inertial sensor data 

  Scheurer, Sebastian; Tedesco, Salvatore; Manzano, Óscar; Brown, Kenneth N.; O'Flynn, Brendan (Springer, 2019-01-18)

  Emergency first response teams during operations expend much time to communicate their current location and status with their leader over noisy radio communication systems. We are developing a modular system to provide as ...
• Subject-dependent and -independent human activity recognition with person-specific and -independent models 

  Scheurer, Sebastian; Tedesco, Salvatore; Brown, Kenneth N.; O'Flynn, Brendan (Association for Computing Machinery, ACM, 2019-09-16)

  The distinction between subject-dependent and subject-independent performance is ubiquitous in the Human Activity Recognition (HAR) literature. We test the hypotheses that HAR models achieve better subject-dependent ...

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