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pro vyhledávání: '"Baldé IS"'
In this work, we show a fundamental limitation in vocabulary adaptation approaches that use Byte-Pair Encoding (BPE) tokenization scheme for fine-tuning pretrained language models (PLMs) to expert domains. Current approaches trivially append the targ
Externí odkaz:
http://arxiv.org/abs/2410.03258
Autor:
Diallo, Ramata, Camara, Bienvenu S., Sidibé, Tiany, Kourouma, Karifa, Camara, Sadan, Keita, Kaba S., Barry, Fanta, Touré, Madeleine, Baldé, Maimouna, Balde, Mamadou D.
Publikováno v:
African Journal of Reproductive Health / La Revue Africaine de la Santé Reproductive, 2024 Jul 01. 28(7), 47-53.
Externí odkaz:
https://www.jstor.org/stable/27321556
Autor:
Barry, Fanta, Balde, Mamadou D., Toure, Madeleine, Diallo, Ramata, Sidibe, Tiany, Camara, Saran, Keita, Kaba S., Camara, Bienvenu S., Kourouma, Karifa, Balde, Maimouna
Publikováno v:
African Journal of Reproductive Health / La Revue Africaine de la Santé Reproductive, 2024 Jun 01. 28(6), 47-54.
Externí odkaz:
https://www.jstor.org/stable/27315220
Autor:
Marcel, Miracle Chibuzor, Diaby, Kassamba Abdel Aziz, Guennoun, Meryem, Nabifo, Betty Rose, Elattar, Mohamed, Rajaonarivelo, Andoniaina, Pius, Privatus, Kgobathe, Molly Nkamogelang, Luis, Immanuel, Shilunga, Sigrid, Etteyeb, Nejmeddine, Qhomane, Keketso, Nyangi, Samuel, Kalunga, Tresford Chilufya, Assano, Nunes Alfredo, Jequecene, Edson Domingos, Joseph, Mafuka Lusala, Sudum, Esaenwi, Gerald, Jorbedom Leelabari, Gore, Christopher Tombe Louis, Hosny, Kareem Waleed, Yasser, Nagat, Franck, Jocelyn, Kourouma, Mamoudou, Bobb, Baboucarr, Jaiteh, Kebab, Sylla, Salma, Obame, Hans Essone, Kiyeng, Dennis, Ngwanw, Thobekile Sandra, Simon, Tawanda Kelvin, Sulayman, Saja Alhoush, Regaibi, Salma, Yahaya, Souley, Ornela, Tengwi Mogou, Viyuyi, Henry Sanderson, Matambo, Fortune Tatenda, Asare-Darko, Matthias, Gbaba, Christian Kontoa Koussouwa, da Silva, Moisés, Joseph, Ntahompagaze, Gomes, Gilberto, Mkhabela, Bongiwe Portia, Bvumbwe, Bauleni, Nkhowani, Tshombe, Gahou, Mawugnon Axel, Abotsi-Masters, Sarah, Simbizi, René, Mugisha, Salomon, Saeed, Ahmed, Eldaw, Mohammed Yahya Alradi, Thomas, Allen, ridha, Ben Abdallah, kaseha, Dieumerci, Baradei, Sherine Ahmed El, Hussein, Nahla Hazem, Fabrice, Bado, Anekwe, Ngozika Frances, Ramessur, Arvind, Koroma, Mohamed Ali, Safary, Harold, Leonardo, Oosthuizen, Dlamini, Mdumiseni Wisdom Dabulizwe, Djabbi, Mamadou Mahamat, Angela, Nonofo, Jalloh, Mamaja, Balde, Mamadou, Olayiwola, Joy, Ibharalu, Elijah, Tchangole, Thierry Martial, Memberu, Kirubel, Dinsa, Lidia, Ezeakunne, Chidozie Gospel
Citizen science offers an opportunity for ordinary people, known as citizen scientists or citizen astronomers in the context of astronomy, to contribute to scientific research. The Pan-African Citizen Science e-Lab (PACS e-Lab) was founded to promote
Externí odkaz:
http://arxiv.org/abs/2408.11059
Autor:
Marcel, Miracle Chibuzor, Diaby, Kassamba Abdel Aziz, Guennoun, Meryem, Nabifo, Betty Rose, Elattar, Mohamed, Rajaonarivelo, Andoniaina, Pius, Privatus, Kgobathe, Molly Nkamogelang, Luis, Immanuel, Shilunga, Sigrid, Etteyeb, Nejmeddine, Qhomane, Keketso, Nyangi, Samuel, Kalunga, Tresford Chilufya, Assano, Nunes Alfredo, Jequecene, Edson Domingos, Joseph, Mafuka Lusala, Sudum, Esaenwi, Gerald, Jorbedom Leelabari, Gore, Christopher Tombe Louis, Hosny, Kareem Waleed, Yasser, Nagat, Franck, Jocelyn, Kourouma, Mamoudou, Bobb, Baboucarr, Jaiteh, Kebab, Sylla, Salma, Obame, Hans Essone, Kiyeng, Dennis, Ngwanw, Thobekile Sandra, Simon, Tawanda Kelvin, Sulayman, Saja Alhoush, Regaibi, Salma, Yahaya, Souley, Ornela, Tengwi Mogou, Viyuyi, Henry Sanderson, Matambo, Fortune Tatenda, Asare-Darko, Matthias, Gbaba, Christian Kontoa Koussouwa, da Silva, Moisés, Joseph, Ntahompagaze, Gomes, Gilberto, Mkhabela, Bongiwe Portia, Bvumbwe, Bauleni, Nkhowani, Tshombe, Gahou, Mawugnon Axel, Abotsi-Masters, Sarah, Simbizi, René, Mugisha, Salomon, Saeed, Ahmed, Eldaw, Mohammed Yahya Alradi, Thomas, Allen, ridha, Ben Abdallah, kaseha, Dieumerci, Baradei, Sherine Ahmed El, Hussein, Nahla Hazem, Fabrice, Bado, Anekwe, Ngozika Frances, Ramessur, Arvind, Koroma, Mohamed Ali, Safary, Harold, Leonardo, Oosthuizen, Dlamini, Mdumiseni Wisdom Dabulizwe, Djabbi, Mamadou Mahamat, Angela, Nonofo, Jalloh, Mamaja, Balde, Mamadou, Olayiwola, Joy, Ibharalu, Elijah, Tchangole, Thierry Martial, Memberu, Kirubel, Dinsa, Lidia, Ezeakunne, Chidozie Gospel
Asteroid search is a global effort for planetary defense. The International Astronomical Search Collaboration (IASC) is the leading global educational outreach program that provides high-quality astronomical datasets to citizen scientists to discover
Externí odkaz:
http://arxiv.org/abs/2408.03385
We introduce the novel class $(E_\alpha)_{\alpha \in [-\infty,1)}$ of reverse map projection embeddings, each one defining a unique new method of encoding classical data into quantum states. Inspired by well-known map projections from the unit sphere
Externí odkaz:
http://arxiv.org/abs/2407.19906
Publikováno v:
Proceedings of the Thirty-Third International Joint Conference on Artificial Intelligence Main Track (IJCAI 2024). Pages 6180-6188
This work presents a dynamic vocabulary adaptation strategy, MEDVOC, for fine-tuning pre-trained language models (PLMs) like BertSumAbs, BART, and PEGASUS for improved medical text summarization. In contrast to existing domain adaptation approaches i
Externí odkaz:
http://arxiv.org/abs/2405.04163
This work will study an optimal control problem describing the two-strain SEIR epidemic model. The studied model is in the form of six nonlinear differential equations illustrating the dynamics of the susceptibles and the exposed, the infected, and t
Externí odkaz:
http://arxiv.org/abs/2404.17305
Ultra-high dimensional confounder selection algorithms comparison with application to radiomics data
Autor:
Baldé, Ismaïla, Ghosh, Debashis
Radiomics is an emerging area of medical imaging data analysis particularly for cancer. It involves the conversion of digital medical images into mineable ultra-high dimensional data. Machine learning algorithms are widely used in radiomics data anal
Externí odkaz:
http://arxiv.org/abs/2310.06315
Autor:
Baldé, Ismaila
The generalized outcome-adaptive lasso (GOAL) is a variable selection for high-dimensional causal inference proposed by Bald\'e et al. [2023, {\em Biometrics} {\bfseries 79(1)}, 514--520]. When the dimension is high, it is now well established that a
Externí odkaz:
http://arxiv.org/abs/2310.00250