Zobrazeno 1 - 10
of 2 204
pro vyhledávání: '"P. Okolo"'
Autor:
O'Neill, Jacki, Marivate, Vukosi, Glover, Barbara, Karanu, Winnie, Tadesse, Girmaw Abebe, Gyekye, Akua, Makena, Anne, Rosslyn-Smith, Wesley, Grollnek, Matthew, Wayua, Charity, Baguma, Rehema, Maduke, Angel, Spencer, Sarah, Kandie, Daniel, Maari, Dennis Ndege, Mutangana, Natasha, Axmed, Maxamed, Kamau, Nyambura, Adamu, Muhammad, Swaniker, Frank, Gatuguti, Brian, Donner, Jonathan, Graham, Mark, Mumo, Janet, Mbindyo, Caroline, N'Guessan, Charlette, Githinji, Irene, Makhafola, Lesego, Kruger, Sean, Etyang, Olivia, Onando, Mulang, Sevilla, Joe, Sambuli, Nanjira, Mbaya, Martin, Breloff, Paul, Anapey, Gideon M., Mogaleemang, Tebogo L., Nghonyama, Tiyani, Wanyoike, Muthoni, Mbuli, Bhekani, Nderu, Lawrence, Nyabero, Wambui, Alam, Uzma, Olaleye, Kayode, Njenga, Caroline, Sellen, Abigail, Kairo, David, Chabikwa, Rutendo, Abdulhamid, Najeeb G., Kubasu, Ketry, Okolo, Chinasa T., Akpo, Eugenia, Budu, Joel, Karambal, Issa, Berkoh, Joseph, Wasswa, William, Njagwi, Muchai, Burnet, Rob, Ochanda, Loise, de Bod, Hanlie, Ankrah, Elizabeth, Kinyunyu, Selemani, Kariuki, Mutembei, Kiyimba, Kizito, Eleshin, Farida, Madeje, Lillian Secelela, Muraga, Catherine, Nganga, Ida, Gichoya, Judy, Maina, Tabbz, Maina, Samuel, Mercy, Muchai, Ochieng, Millicent, Nyairo, Stephanie
This white paper is the output of a multidisciplinary workshop in Nairobi (Nov 2023). Led by a cross-organisational team including Microsoft Research, NEPAD, Lelapa AI, and University of Oxford. The workshop brought together diverse thought-leaders f
Externí odkaz:
http://arxiv.org/abs/2411.10091
Autor:
Lin, Hongjin, Karusala, Naveena, Okolo, Chinasa T., D'Ignazio, Catherine, Gajos, Krzysztof Z.
Artificial Intelligence for Social Good (AI4SG) has emerged as a growing body of research and practice exploring the potential of AI technologies to tackle social issues. This area emphasizes interdisciplinary partnerships with community organization
Externí odkaz:
http://arxiv.org/abs/2409.06814
Autor:
Okolo, Chinasa T.
In light of prominent discourse around the negative implications of generative AI, an emerging area of research is investigating the current and estimated impacts of AI-generated propaganda on African citizens participating in elections. Throughout A
Externí odkaz:
http://arxiv.org/abs/2407.07695
Autor:
Neu, Gergely, Okolo, Nneka
We study offline Reinforcement Learning in large infinite-horizon discounted Markov Decision Processes (MDPs) when the reward and transition models are linearly realizable under a known feature map. Starting from the classic linear-program formulatio
Externí odkaz:
http://arxiv.org/abs/2405.13755
Autor:
Jeong, Hyewon, Jabbour, Sarah, Yang, Yuzhe, Thapta, Rahul, Mozannar, Hussein, Han, William Jongwon, Mehandru, Nikita, Wornow, Michael, Lialin, Vladislav, Liu, Xin, Lozano, Alejandro, Zhu, Jiacheng, Kocielnik, Rafal Dariusz, Harrigian, Keith, Zhang, Haoran, Lee, Edward, Vukadinovic, Milos, Balagopalan, Aparna, Jeanselme, Vincent, Matton, Katherine, Demirel, Ilker, Fries, Jason, Rashidi, Parisa, Beaulieu-Jones, Brett, Xu, Xuhai Orson, McDermott, Matthew, Naumann, Tristan, Agrawal, Monica, Zitnik, Marinka, Ustun, Berk, Choi, Edward, Yeom, Kristen, Gursoy, Gamze, Ghassemi, Marzyeh, Pierson, Emma, Chen, George, Kanjilal, Sanjat, Oberst, Michael, Zhang, Linying, Singh, Harvineet, Hartvigsen, Tom, Zhou, Helen, Okolo, Chinasa T.
The third ML4H symposium was held in person on December 10, 2023, in New Orleans, Louisiana, USA. The symposium included research roundtable sessions to foster discussions between participants and senior researchers on timely and relevant topics for
Externí odkaz:
http://arxiv.org/abs/2403.01628
Autor:
Diallo, Kadijatou, Smith, Jonathan, Okolo, Chinasa T., Nyamwaya, Dorcas, Kgomo, Jonas, Ngamita, Richard
Artificial Intelligence (AI) requires new ways of evaluating national technology use and strategy for African nations. We conduct a survey of existing 'readiness' assessments both for general digital adoption and for AI policy in particular. We concl
Externí odkaz:
http://arxiv.org/abs/2403.14662
Autor:
Neu, Gergely, Okolo, Nneka
We study the performance of stochastic first-order methods for finding saddle points of convex-concave functions. A notorious challenge faced by such methods is that the gradients can grow arbitrarily large during optimization, which may result in in
Externí odkaz:
http://arxiv.org/abs/2402.13903
Autor:
Benjamin Chukwunonso Okonkwo, Nkiru Nwamaka Ezeama, Gabriel Chidera Edeh, Shadrach Arinze Okolo, Chinonuju Franklin Chiekezie, Chidindu Prince Anagwu, Michael Chukwuebuka Awugosi
Publikováno v:
Current Medicine Research and Practice, Vol 14, Iss 5, Pp 200-207 (2024)
Background Intimate partner violence (IPV) has emerged as a global phenomenon, with pregnant women being particularly vulnerable, especially in developing countries. Despite its diverse manifestations and severe impacts, IPV is sometimes perceived as
Externí odkaz:
https://doaj.org/article/7ce52fbf47dd43788d29eda13e1b16ce
Publikováno v:
Nigerian Journal of Paediatrics, Vol 36, Iss 1 & 2, Pp 29-32 (2024)
Background: Diarrhoea is one of the major causes of morbidity and mortality among infants and young children in developing countries. More than half of the deaths due to diarrhoea results from dehydration and/or excessive loss of essential nutrients
Externí odkaz:
https://doaj.org/article/0e341d7fa1e94d4fb5845b8922031b79
Offline Reinforcement Learning (RL) aims to learn a near-optimal policy from a fixed dataset of transitions collected by another policy. This problem has attracted a lot of attention recently, but most existing methods with strong theoretical guarant
Externí odkaz:
http://arxiv.org/abs/2305.12944