Zobrazeno 1 - 10
of 157
pro vyhledávání: '"Ghinita, Gabriel"'
Smart grids are a valuable data source to study consumer behavior and guide energy policy decisions. In particular, time-series of power consumption over geographical areas are essential in deciding the optimal placement of expensive resources (e.g.,
Externí odkaz:
http://arxiv.org/abs/2408.16017
Autor:
Shaham, Sina, Hajisafi, Arash, Quan, Minh K, Nguyen, Dinh C, Krishnamachari, Bhaskar, Peris, Charith, Ghinita, Gabriel, Shahabi, Cyrus, Pathirana, Pubudu N.
Privacy and fairness are two crucial pillars of responsible Artificial Intelligence (AI) and trustworthy Machine Learning (ML). Each objective has been independently studied in the literature with the aim of reducing utility loss in achieving them. D
Externí odkaz:
http://arxiv.org/abs/2307.15838
Autor:
Mokbel, Mohamed, Sakr, Mahmoud, Xiong, Li, Züfle, Andreas, Almeida, Jussara, Anderson, Taylor, Aref, Walid, Andrienko, Gennady, Andrienko, Natalia, Cao, Yang, Chawla, Sanjay, Cheng, Reynold, Chrysanthis, Panos, Fei, Xiqi, Ghinita, Gabriel, Graser, Anita, Gunopulos, Dimitrios, Jensen, Christian, Kim, Joon-Seok, Kim, Kyoung-Sook, Kröger, Peer, Krumm, John, Lauer, Johannes, Magdy, Amr, Nascimento, Mario, Ravada, Siva, Renz, Matthias, Sacharidis, Dimitris, Shahabi, Cyrus, Salim, Flora, Sarwat, Mohamed, Schoemans, Maxime, Speckmann, Bettina, Tanin, Egemen, Teng, Xu, Theodoridis, Yannis, Torp, Kristian, Trajcevski, Goce, van Kreveld, Marc, Wenk, Carola, Werner, Martin, Wong, Raymond, Wu, Song, Xu, Jianqiu, Youssef, Moustafa, Zeinalipour, Demetris, Zhang, Mengxuan, Zimányi, Esteban
Mobility data captures the locations of moving objects such as humans, animals, and cars. With the availability of GPS-equipped mobile devices and other inexpensive location-tracking technologies, mobility data is collected ubiquitously. In recent ye
Externí odkaz:
http://arxiv.org/abs/2307.05717
Machine learning (ML) is playing an increasing role in decision-making tasks that directly affect individuals, e.g., loan approvals, or job applicant screening. Significant concerns arise that, without special provisions, individuals from under-privi
Externí odkaz:
http://arxiv.org/abs/2302.02306
Location-based alerts have gained increasing popularity in recent years, whether in the context of healthcare (e.g., COVID-19 contact tracing), marketing (e.g., location-based advertising), or public safety. However, serious privacy concerns arise wh
Externí odkaz:
http://arxiv.org/abs/2301.06238
Several companies (e.g., Meta, Google) have initiated "data-for-good" projects where aggregate location data are first sanitized and released publicly, which is useful to many applications in transportation, public health (e.g., COVID-19 spread) and
Externí odkaz:
http://arxiv.org/abs/2208.09744
Fairness in data-driven decision-making studies scenarios where individuals from certain population segments may be unfairly treated when being considered for loan or job applications, access to public resources, or other types of services. In locati
Externí odkaz:
http://arxiv.org/abs/2204.01880
Conventional origin-destination (OD) matrices record the count of trips between pairs of start and end locations, and have been extensively used in transportation, traffic planning, etc. More recently, due to use case scenarios such as COVID-19 pande
Externí odkaz:
http://arxiv.org/abs/2202.12342
Mobile apps and location-based services generate large amounts of location data that can benefit research on traffic optimization, context-aware notifications and public health (e.g., spread of contagious diseases). To preserve individual privacy, on
Externí odkaz:
http://arxiv.org/abs/2108.01496