Fair assortment planning
Many online platforms, ranging from online retail stores to social media platforms, employ
algorithms to optimize their offered assortment of items (eg, products and contents). These …
algorithms to optimize their offered assortment of items (eg, products and contents). These …
Social Media Informatics for Sustainable Cities and Societies: An Overview of the Applications, associated Challenges, and Potential Solutions
In the modern world, our cities and societies face several technological and societal
challenges, such as rapid urbanization, global warming & climate change, the digital divide …
challenges, such as rapid urbanization, global warming & climate change, the digital divide …
A multidisciplinary framework for deconstructing bots' pluripotency in dualistic antagonism
Anthropomorphic social bots are engineered to emulate human verbal communication and
generate toxic or inflammatory content across social networking services (SNSs). Bot …
generate toxic or inflammatory content across social networking services (SNSs). Bot …
On the Interplay of Transparency and Fairness in AI-Informed Decision-Making
J Schöffer - 2023 - publikationen.bibliothek.kit.edu
Using artificial intelligence (AI) systems for informing high-stakes decisions has become
increasingly pervasive in a variety of domains, including but not limited to hiring, lending, or …
increasingly pervasive in a variety of domains, including but not limited to hiring, lending, or …
[图书][B] Information and Fairness in Resource Allocation Problems
F Monachou - 2022 - search.proquest.com
Abstract Information is an orchestrating component in many operational settings, from supply
chains to online platforms to decision-making algorithms. For example, online marketplaces …
chains to online platforms to decision-making algorithms. For example, online marketplaces …
[PDF][PDF] agenda examines the bidirectional relationship between algorithm design and decision-making
S Loss - jessiefin.com
In supervised machine learning, empirical risk minimization is the dominant paradigm for
learning from data. Therein, one learns to predict by minimizing a surrogate loss function L …
learning from data. Therein, one learns to predict by minimizing a surrogate loss function L …