Academic literature on the topic 'Ranking learning'
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Journal articles on the topic "Ranking learning"
Guo, Qianyu, Gong Haotong, Xujun Wei, et al. "RankDNN: Learning to Rank for Few-Shot Learning." Proceedings of the AAAI Conference on Artificial Intelligence 37, no. 1 (2023): 728–36. http://dx.doi.org/10.1609/aaai.v37i1.25150.
Full textDzyuba, Vladimir, Matthijs van Leeuwen, Siegfried Nijssen, and Luc De Raedt. "Interactive Learning of Pattern Rankings." International Journal on Artificial Intelligence Tools 23, no. 06 (2014): 1460026. http://dx.doi.org/10.1142/s0218213014600264.
Full textHiemstra, Djoerd. "Was Fairness in IR Discussed by Cooper and Robertson in the 1970's?" ACM SIGIR Forum 56, no. 2 (2022): 1–5. http://dx.doi.org/10.1145/3582900.3582924.
Full textYu, Hai-Tao, Degen Huang, Fuji Ren, and Lishuang Li. "Diagnostic Evaluation of Policy-Gradient-Based Ranking." Electronics 11, no. 1 (2021): 37. http://dx.doi.org/10.3390/electronics11010037.
Full textPoplavskyi, Mykhailo. "University Ranking As an Education Quality Assessment Tool." Ukrainian Information Space, no. 2(8) (November 15, 2021): 16–38. https://doi.org/10.31866/2616-7948.2(8).2021.245787.
Full textSumanth Reddy, Shiva, Anil Kumar B, Jahnavi S, Manjunath D R, Girish N, and Nandini C. "Enhancing Academic Excellence through Autonomy: A Data-Driven Analysis of NIRF Rankings in South Indian Higher Educational Institutions." Journal of Hacking Techniques, Digital Crime Prevention and Computer Virology 1, no. 3 (2025): 36–49. https://doi.org/10.46610/johtdcpcv.2024.v01i03.004.
Full textPan, Weike, Qiang Yang, Yuchao Duan, Ben Tan, and Zhong Ming. "Transfer Learning for Behavior Ranking." ACM Transactions on Intelligent Systems and Technology 8, no. 5 (2017): 1–23. http://dx.doi.org/10.1145/3057732.
Full textJiang, Liangxiao. "Learning random forests for ranking." Frontiers of Computer Science in China 5, no. 1 (2010): 79–86. http://dx.doi.org/10.1007/s11704-010-0388-5.
Full textGeng, Xiubo, and Xue-Qi Cheng. "Learning multiple metrics for ranking." Frontiers of Computer Science in China 5, no. 3 (2011): 259–67. http://dx.doi.org/10.1007/s11704-011-0152-5.
Full textRahangdale, Ashwini, and Shital Raut. "Machine Learning Methods for Ranking." International Journal of Software Engineering and Knowledge Engineering 29, no. 06 (2019): 729–61. http://dx.doi.org/10.1142/s021819401930001x.
Full textDissertations / Theses on the topic "Ranking learning"
Latham, Andrew C. "Multiple-Instance Feature Ranking." Case Western Reserve University School of Graduate Studies / OhioLINK, 2016. http://rave.ohiolink.edu/etdc/view?acc_num=case1440642294.
Full textSinsel, Erik W. "Ensemble learning for ranking interesting attributes." Morgantown, W. Va. : [West Virginia University Libraries], 2005. https://eidr.wvu.edu/etd/documentdata.eTD?documentid=4400.
Full textMattsson, Fredrik, and Anton Gustafsson. "Optimize Ranking System With Machine Learning." Thesis, Högskolan i Halmstad, Akademin för informationsteknologi, 2018. http://urn.kb.se/resolve?urn=urn:nbn:se:hh:diva-37431.
Full textAchab, Mastane. "Ranking and risk-aware reinforcement learning." Electronic Thesis or Diss., Institut polytechnique de Paris, 2020. http://www.theses.fr/2020IPPAT020.
Full textKorba, Anna. "Learning from ranking data : theory and methods." Thesis, Université Paris-Saclay (ComUE), 2018. http://www.theses.fr/2018SACLT009/document.
Full textKorba, Anna. "Learning from ranking data : theory and methods." Electronic Thesis or Diss., Université Paris-Saclay (ComUE), 2018. http://www.theses.fr/2018SACLT009.
Full textFILHO, FRANCISCO BENJAMIM. "RANKING OF WEB PAGES BY LEARNING MULTIPLE LATENT CATEGORIES." PONTIFÍCIA UNIVERSIDADE CATÓLICA DO RIO DE JANEIRO, 2012. http://www.maxwell.vrac.puc-rio.br/Busca_etds.php?strSecao=resultado&nrSeq=19540@1.
Full textCheung, Chi-Wai. "Probabilistic rank aggregation for multiple SVM ranking /." View abstract or full-text, 2009. http://library.ust.hk/cgi/db/thesis.pl?CSED%202009%20CHEUNG.
Full textVogel, Robin. "Similarity ranking for biometrics : theory and practice." Electronic Thesis or Diss., Institut polytechnique de Paris, 2020. http://www.theses.fr/2020IPPAT031.
Full textZacharia, Giorgos 1974. "Regularized algorithms for ranking, and manifold learning for related tasks." Thesis, Massachusetts Institute of Technology, 2009. http://hdl.handle.net/1721.1/47753.
Full textBooks on the topic "Ranking learning"
Hawkins, John N., Aki Yamada, Reiko Yamada, and W. James Jacob, eds. New Directions of STEM Research and Learning in the World Ranking Movement. Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-98666-1.
Full textUnited States. Government Accountability Office. Military education: DOD needs to develop performance goals and metrics for advanced distributed learning in professional military education : report to the Ranking Minority Member, Committee on Armed Services, House of Representatives. U.S. Government Accountability Office, 2004.
Find full textOffice, General Accounting. Student financial aid: Federal aid awarded to students taking remedial courses : report to the ranking minority member, Subcommittee on Postsecondary Education, Training, and Life-Long Learning, Committee on Education and the Workforce, House of Representatives. The Office, 1997.
Find full textOffice, General Accounting. Student financial aid: Federal aid awarded to students taking remedial courses : report to the ranking minority member, Subcommittee on Postsecondary Education, Training, and Life-Long Learning, Committee on Education and the Workforce, House of Representatives. The Office, 1997.
Find full textXia, Lirong, Ronald Brachman, Francesca Rossi, and Peter Stone. Learning and Decision-Making from Rank Data. Morgan & Claypool Publishers, 2019.
Find full textXia, Lirong, Ronald Brachman, Francesca Rossi, and Peter Stone. Learning and Decision-Making from Rank Data. Morgan & Claypool Publishers, 2019.
Find full textXia, Lirong, Ronald Brachman, Francesca Rossi, and Peter Stone. Learning and Decision-Making from Rank Data. Morgan & Claypool Publishers, 2019.
Find full textJarosz, Gaja. Learning with Violable Constraints. Edited by Jeffrey L. Lidz, William Snyder, and Joe Pater. Oxford University Press, 2016. http://dx.doi.org/10.1093/oxfordhb/9780199601264.013.30.
Full textHawkins, John N., W. James Jacob, Reiko Yamada, and Aki Yamada. New Directions of STEM Research and Learning in the World Ranking Movement: A Comparative Perspective. Palgrave Macmillan, 2019.
Find full textHawkins, John N., W. James Jacob, Reiko Yamada, and Aki Yamada. New Directions of STEM Research and Learning in the World Ranking Movement: A Comparative Perspective. Palgrave Macmillan, 2018.
Find full textBook chapters on the topic "Ranking learning"
Joshi, Ameet V. "Ranking." In Machine Learning and Artificial Intelligence. Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-26622-6_20.
Full textJoshi, Ameet V. "Ranking." In Machine Learning and Artificial Intelligence. Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-031-12282-8_20.
Full textCossock, David, and Tong Zhang. "Subset Ranking Using Regression." In Learning Theory. Springer Berlin Heidelberg, 2006. http://dx.doi.org/10.1007/11776420_44.
Full textLiu, Tie-Yan. "Relational Ranking." In Learning to Rank for Information Retrieval. Springer Berlin Heidelberg, 2011. http://dx.doi.org/10.1007/978-3-642-14267-3_6.
Full textLiu, Tie-Yan. "Transfer Ranking." In Learning to Rank for Information Retrieval. Springer Berlin Heidelberg, 2011. http://dx.doi.org/10.1007/978-3-642-14267-3_9.
Full textKamishima, Toshihiro, and Shotaro Akaho. "Dimension Reduction for Object Ranking." In Preference Learning. Springer Berlin Heidelberg, 2010. http://dx.doi.org/10.1007/978-3-642-14125-6_10.
Full textVembu, Shankar, and Thomas Gärtner. "Label Ranking Algorithms: A Survey." In Preference Learning. Springer Berlin Heidelberg, 2010. http://dx.doi.org/10.1007/978-3-642-14125-6_3.
Full textZhang, Jianping, Jerzy W. Bala, Ali Hadjarian, and Brent Han. "Ranking Cases with Classification Rules." In Preference Learning. Springer Berlin Heidelberg, 2010. http://dx.doi.org/10.1007/978-3-642-14125-6_8.
Full textAgarwal, Shivani, and Dan Roth. "Learnability of Bipartite Ranking Functions." In Learning Theory. Springer Berlin Heidelberg, 2005. http://dx.doi.org/10.1007/11503415_2.
Full textRendle, Steffen. "Learning Context-Aware Ranking." In Context-Aware Ranking with Factorization Models. Springer Berlin Heidelberg, 2010. http://dx.doi.org/10.1007/978-3-642-16898-7_4.
Full textConference papers on the topic "Ranking learning"
Huang, Hailin, Liuwen Cao, Jiexin Wang, Tianchen Yu, and Yi Cai. "Code Ranking with Structure Awareness Contrastive Learning." In 2025 IEEE/ACM 33rd International Conference on Program Comprehension (ICPC). IEEE, 2025. https://doi.org/10.1109/icpc66645.2025.00053.
Full textHijazi, Sherin, Mahmoud Moshref, and Samer Mohammed Arqawi. "Evaluating Factors Influencing University Ranking Based on QS Ranking 2023-2024 Using Machine Learning Algorithms." In 2025 1st International Conference on Computational Intelligence Approaches and Applications (ICCIAA). IEEE, 2025. https://doi.org/10.1109/icciaa65327.2025.11013585.
Full textChew, Min Min, Sourav S. Bhowmick, and Adam Jatowt. "Ranking Without Learning." In SIGIR '18: The 41st International ACM SIGIR conference on research and development in Information Retrieval. ACM, 2018. http://dx.doi.org/10.1145/3209978.3210100.
Full textOuyang, Hua, and Alex Gray. "Learning dissimilarities by ranking." In the 25th international conference. ACM Press, 2008. http://dx.doi.org/10.1145/1390156.1390248.
Full textFALKOWSKI, BERND-JÜRGEN. "RANKING AND PERCEPTRON LEARNING." In Proceedings of the 9th International FLINS Conference. WORLD SCIENTIFIC, 2010. http://dx.doi.org/10.1142/9789814324700_0077.
Full textClémençon, Stéphan, Marine Depecker, and Nicolas Vayatis. "Bagging Ranking Trees." In 2009 International Conference on Machine Learning and Applications (ICMLA). IEEE, 2009. http://dx.doi.org/10.1109/icmla.2009.14.
Full textRoussinov, D., and Weiguo Fan. "Learning Ranking vs. Modeling Relevance." In Proceedings of the 39th Annual Hawaii International Conference on System Sciences (HICSS'06). IEEE, 2006. http://dx.doi.org/10.1109/hicss.2006.252.
Full textCosta, Miguel, Francisco Couto, and Mário Silva. "Learning temporal-dependent ranking models." In SIGIR '14: The 37th International ACM SIGIR Conference on Research and Development in Information Retrieval. ACM, 2014. http://dx.doi.org/10.1145/2600428.2609619.
Full textLyubchyk, Leonid, and Galyna Grinberg. "Online Ranking Learning on Clusters." In 2018 IEEE Second International Conference on Data Stream Mining & Processing (DSMP). IEEE, 2018. http://dx.doi.org/10.1109/dsmp.2018.8478520.
Full textChang, Xiao, and Qinghua Zheng. "Sparse Bayesian learning for ranking." In 2009 IEEE International Conference on Granular Computing (GRC). IEEE, 2009. http://dx.doi.org/10.1109/grc.2009.5255164.
Full textReports on the topic "Ranking learning"
Berkhout, Emilie, Goldy Dharmawan, Amanda Beatty, Daniel Suryadarma, and Menno Pradhan. Who Benefits and Loses from Large Changes to Student Composition? Assessing Impacts of Lowering School Admissions Standards in Indonesia. Research on Improving Systems of Education (RISE), 2022. http://dx.doi.org/10.35489/bsg-risewp_2022/094.
Full textBerkhout, Emilie, Goldy Dharmawan, Amanda Beatty, Daniel Suryadarma, and Menno Pradhan. Who Benefits and Loses from Large Changes to Student Composition? Assessing Impacts of Lowering School Admissions Standards in Indonesia. Research on Improving Systems of Education (RISE), 2022. http://dx.doi.org/10.35489/bsg-risewp_2022/094.
Full textSchiefelbein, Ernesto, Paulina Schiefelbein, and Laurence Wolff. Cost-Effectiveness of Education Policies in Latin America: A Survey of Expert Opinion. Inter-American Development Bank, 1998. http://dx.doi.org/10.18235/0008789.
Full textSandford, Robert, Vladimir Smakhtin, Colin Mayfield, et al. Canada in the Global Water World: Analysis of Capabilities. United Nations University Institute for Water, Environment and Health, 2018. http://dx.doi.org/10.53328/vsgg2030.
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