Zobrazeno 1 - 4
of 4
pro vyhledávání: '"Farastu, Paresha"'
Autor:
Aird, Amanda, All, Cassidy, Farastu, Paresha, Stefancova, Elena, Sun, Joshua, Mattei, Nicholas, Burke, Robin
Fairness problems in recommender systems often have a complexity in practice that is not adequately captured in simplified research formulations. A social choice formulation of the fairness problem, operating within a multi-agent architecture of fair
Externí odkaz:
http://arxiv.org/abs/2309.08621
Autor:
Aird, Amanda, Farastu, Paresha, Sun, Joshua, Štefancová, Elena, All, Cassidy, Voida, Amy, Mattei, Nicholas, Burke, Robin
Algorithmic fairness in the context of personalized recommendation presents significantly different challenges to those commonly encountered in classification tasks. Researchers studying classification have generally considered fairness to be a matte
Externí odkaz:
http://arxiv.org/abs/2303.00968
Fairness-aware recommender systems that have a provider-side fairness concern seek to ensure that protected group(s) of providers have a fair opportunity to promote their items or products. There is a ``cost of fairness'' borne by the consumer side o
Externí odkaz:
http://arxiv.org/abs/2209.04043
Autor:
Saad, Fardin, Mahmud, Hasan, Kabir, Mohammad Ridwan, Shaheen, Md. Alamin, Farastu, Paresha, Hasan, Md. Kamrul
A language agnostic approach to recognizing emotions from speech remains an incomplete and challenging task. In this paper, we performed a step-by-step comparative analysis of Speech Emotion Recognition (SER) using Bangla and English languages to ass
Externí odkaz:
http://arxiv.org/abs/2111.10776