Статті в журналах з теми "Probability learning"
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SAEKI, Daisuke. "Probability learning in golden hamsters." Japanese Journal of Animal Psychology 49, no. 1 (1999): 41–47. http://dx.doi.org/10.2502/janip.49.41.
Groth, Randall E., Jennifer A. Bergner, and Jathan W. Austin. "Dimensions of Learning Probability Vocabulary." Journal for Research in Mathematics Education 51, no. 1 (January 2020): 75–104. http://dx.doi.org/10.5951/jresematheduc.2019.0008.
Groth, Randall E., Jennifer A. Bergner, and Jathan W. Austin. "Dimensions of Learning Probability Vocabulary." Journal for Research in Mathematics Education 51, no. 1 (January 2020): 75–104. http://dx.doi.org/10.5951/jresematheduc.51.1.0075.
Rivas, Javier. "Probability matching and reinforcement learning." Journal of Mathematical Economics 49, no. 1 (January 2013): 17–21. http://dx.doi.org/10.1016/j.jmateco.2012.09.004.
West, Bruce J. "Fractal Probability Measures of Learning." Methods 24, no. 4 (August 2001): 395–402. http://dx.doi.org/10.1006/meth.2001.1208.
Malley, J. D., J. Kruppa, A. Dasgupta, K. G. Malley, and A. Ziegler. "Probability Machines." Methods of Information in Medicine 51, no. 01 (2012): 74–81. http://dx.doi.org/10.3414/me00-01-0052.
Dawson, Michael R. W. "Probability Learning by Perceptrons and People." Comparative Cognition & Behavior Reviews 15 (2022): 1–188. http://dx.doi.org/10.3819/ccbr.2019.140011.
HIRASAWA, Kotaro, Masaaki HARADA, Masanao OHBAYASHI, Juuichi MURATA, and Jinglu HU. "Probability and Possibility Automaton Learning Network." IEEJ Transactions on Industry Applications 118, no. 3 (1998): 291–99. http://dx.doi.org/10.1541/ieejias.118.291.
Groth, Randall E., Jaime Butler, and Delmar Nelson. "Overcoming challenges in learning probability vocabulary." Teaching Statistics 38, no. 3 (May 26, 2016): 102–7. http://dx.doi.org/10.1111/test.12109.
Starzyk, J. A., and F. Wang. "Dynamic Probability Estimator for Machine Learning." IEEE Transactions on Neural Networks 15, no. 2 (March 2004): 298–308. http://dx.doi.org/10.1109/tnn.2004.824254.
Kabata, Takashi, Takemasa Yokoyama, Yasuki Noguchi, and Shinichi Kita. "Location Probability Learning Requires Focal Attention." Perception 43, no. 4 (January 2014): 344–50. http://dx.doi.org/10.1068/p7589.
Kreitler, Shulamith, and Edward Zigler. "Motivational Determinants of Children's Probability Learning." Journal of Genetic Psychology 151, no. 3 (September 1990): 301–16. http://dx.doi.org/10.1080/00221325.1990.9914619.
Bialek, William, Curtis G. Callan, and Steven P. Strong. "Field Theories for Learning Probability Distributions." Physical Review Letters 77, no. 23 (December 2, 1996): 4693–97. http://dx.doi.org/10.1103/physrevlett.77.4693.
Husmeier, D. "Learning non-stationary conditional probability distributions." Neural Networks 13, no. 3 (April 2000): 287–90. http://dx.doi.org/10.1016/s0893-6080(00)00018-6.
Lungu, O. V., T. W�chter, T. Liu, D. T. Willingham, and J. Ashe. "Probability detection mechanisms and motor learning." Experimental Brain Research 159, no. 2 (July 16, 2004): 135–50. http://dx.doi.org/10.1007/s00221-004-1945-7.
Tanujaya, Benidiktus, Rully Charitas Indra Prahmana, and Jeinne Mumu. "Designing learning activities on conditional probability." Journal of Physics: Conference Series 1088 (September 2018): 012087. http://dx.doi.org/10.1088/1742-6596/1088/1/012087.
Schumacher, Martin. "Probability estimation and machine learning-Editorial." Biometrical Journal 56, no. 4 (July 2014): 531–33. http://dx.doi.org/10.1002/bimj.201400075.
Rahmi, F., P. D. Sampoerno, and L. Ambarwati. "Probability learning trajectory: Students’ emerging relational understanding of probability through ratio." Journal of Physics: Conference Series 1470 (February 2020): 012067. http://dx.doi.org/10.1088/1742-6596/1470/1/012067.
Shi-Ming Huang, Shi-Ming Huang, Yu-Ting Huang Shi-Ming Huang, and Li-Kuan Wang Yu-Ting Huang. "Teaching Case – Predicting the Probability of Company Bankruptcy with CAATs." International Journal of Computer Auditing 2, no. 1 (December 2020): 005–22. http://dx.doi.org/10.53106/256299802020120201002.
Chung, Heewon, and Jinseok Lee. "Iterative Semi-Supervised Learning Using Softmax Probability." Computers, Materials & Continua 72, no. 3 (2022): 5607–28. http://dx.doi.org/10.32604/cmc.2022.028154.
Rastogi (nee Khemchandani), Reshma, and Sambhav Jain. "Multi-label learning via minimax probability machine." International Journal of Approximate Reasoning 145 (June 2022): 1–17. http://dx.doi.org/10.1016/j.ijar.2022.02.002.
White, Chris M., and Derek J. Koehler. "Missing information in multiple-cue probability learning." Memory & Cognition 32, no. 6 (September 2004): 1007–18. http://dx.doi.org/10.3758/bf03196877.
Munro, D. J., O. K. Ersoy, M. R. Bell, and J. S. Sadowsky. "Neural network learning of low-probability events." IEEE Transactions on Aerospace and Electronic Systems 32, no. 3 (July 1996): 898–910. http://dx.doi.org/10.1109/7.532251.
White, Chris M., and Derek J. Koehler. "Choice strategies in multiple-cue probability learning." Journal of Experimental Psychology: Learning, Memory, and Cognition 33, no. 4 (2007): 757–68. http://dx.doi.org/10.1037/0278-7393.33.4.757.
Koehler, Derek J. "Probability judgment in three-category classification learning." Journal of Experimental Psychology: Learning, Memory, and Cognition 26, no. 1 (2000): 28–52. http://dx.doi.org/10.1037/0278-7393.26.1.28.
Braga-Neto, Ulisses M., and Edward R. Dougherty. "Machine Learning Requires Probability and Statistics [Perspectives]." IEEE Signal Processing Magazine 37, no. 4 (July 2020): 118–22. http://dx.doi.org/10.1109/msp.2020.2985385.
Cano, Andrés, Manuel Gómez-Olmedo, Serafín Moral, Cora B. Pérez-Ariza, and Antonio Salmerón. "Learning recursive probability trees from probabilistic potentials." International Journal of Approximate Reasoning 53, no. 9 (December 2012): 1367–87. http://dx.doi.org/10.1016/j.ijar.2012.06.026.
FIORI, SIMONE. "PROBABILITY DENSITY FUNCTION LEARNING BY UNSUPERVISED NEURONS." International Journal of Neural Systems 11, no. 05 (October 2001): 399–417. http://dx.doi.org/10.1142/s0129065701000898.
Yang, Hongkang. "A Mathematical Framework for Learning Probability Distributions." Journal of Machine Learning 1, no. 4 (June 2022): 373–431. http://dx.doi.org/10.4208/jml.221202.
Storkel, Holly L. "Learning New Words." Journal of Speech, Language, and Hearing Research 44, no. 6 (December 2001): 1321–37. http://dx.doi.org/10.1044/1092-4388(2001/103).
Wijaya, Ariyadi, Elmaini Elmaini, and Michiel Doorman. "A LEARNING TRAJECTORY FOR PROBABILITY: A CASE OF GAME-BASED LEARNING." Journal on Mathematics Education 12, no. 1 (January 1, 2021): 1–16. http://dx.doi.org/10.22342/jme.12.1.12836.1-16.
Gnanasagaran, Durga, and Abdul Halim Amat @ Kamaruddin. "The effectiveness of mobile learning in the teaching and learning of probability." Jurnal Pendidikan Sains Dan Matematik Malaysia 9, no. 2 (December 6, 2019): 9–15. http://dx.doi.org/10.37134/jpsmm.vol9.2.2.2019.
Don, Hilary J., A. Ross Otto, Astin C. Cornwall, Tyler Davis, and Darrell A. Worthy. "Learning reward frequency over reward probability: A tale of two learning rules." Cognition 193 (December 2019): 104042. http://dx.doi.org/10.1016/j.cognition.2019.104042.
CHERNOFF, EGAN J., EFI PAPARISTODEMOU, DIONYSIA BAKOGIANNI, and PETER PETOCZ. "RESEARCH ON LEARNING AND TEACHING PROBABILITY WITHIN STATISTICS." STATISTICS EDUCATION RESEARCH JOURNAL 15, no. 2 (November 30, 2016): 6–10. http://dx.doi.org/10.52041/serj.v15i2.600.
Kosiashvili, D. "Probability of poverty: PPI analysis by machine learning." 101, no. 101 (December 30, 2021): 141–47. http://dx.doi.org/10.26565/2311-2379-2021-101-14.
Kertész, Gábor. "Deep Metric Learning Using Negative Sampling Probability Annealing." Sensors 22, no. 19 (October 6, 2022): 7579. http://dx.doi.org/10.3390/s22197579.
González-Santander, Juan Luis. "A probability problem suitable for Problem-Based Learning." Nereis. Interdisciplinary Ibero-American Journal of Methods, Modelling and Simulation., no. 13 (November 15, 2021): 165–72. http://dx.doi.org/10.46583/nereis_2021.13.782.
Yeh, Wei-Chang, Edward Lin, and Chia-Ling Huang. "Predicting Spread Probability of Learning-Effect Computer Virus." Complexity 2021 (July 10, 2021): 1–17. http://dx.doi.org/10.1155/2021/6672630.
Catrambone, Richard, and Keith J. Holyoak. "Learning subgoals and methods for solving probability problems." Memory & Cognition 18, no. 6 (November 1990): 593–603. http://dx.doi.org/10.3758/bf03197102.
Kaizhu Huang, Haiqin Yang, Irwin King, and M. R. Lyu. "Imbalanced learning with a biased minimax probability machine." IEEE Transactions on Systems, Man and Cybernetics, Part B (Cybernetics) 36, no. 4 (August 2006): 913–23. http://dx.doi.org/10.1109/tsmcb.2006.870610.
Jović, Srđan, Milica Miljković, Miljan Ivanović, Milena Šaranović, and Milena Arsić. "Prostate Cancer Probability Prediction By Machine Learning Technique." Cancer Investigation 35, no. 10 (November 26, 2017): 647–51. http://dx.doi.org/10.1080/07357907.2017.1406496.
Movellan, Javier R., and James L. McClelland. "Learning Continuous Probability Distributions with Symmetric Diffusion Networks." Cognitive Science 17, no. 4 (October 1993): 463–96. http://dx.doi.org/10.1207/s15516709cog1704_1.
Meade, R., B. Backus, and Q. Haijiang. "Cue probability learning by the human perceptual system." Journal of Vision 9, no. 8 (March 23, 2010): 42. http://dx.doi.org/10.1167/9.8.42.
Delgado, M. R., M. M. Miller, S. Inati, and E. A. Phelps. "An fMRI study of reward-related probability learning." NeuroImage 24, no. 3 (February 2005): 862–73. http://dx.doi.org/10.1016/j.neuroimage.2004.10.002.
Cozman, Fabio Gagliardi. "Learning imprecise probability models: Conceptual and practical challenges." International Journal of Approximate Reasoning 55, no. 7 (October 2014): 1594–96. http://dx.doi.org/10.1016/j.ijar.2014.04.016.
Gaál, Zsófia Anna, Roland Boha, Brigitta Tóth, and Márk Molnár. "Aging effect in an emotional probability learning task." International Journal of Psychophysiology 77, no. 3 (September 2010): 257–58. http://dx.doi.org/10.1016/j.ijpsycho.2010.06.079.
Balata, Alessandro, Michael Ludkovski, Aditya Maheshwari, and Jan Palczewski. "Statistical learning for probability-constrained stochastic optimal control." European Journal of Operational Research 290, no. 2 (April 2021): 640–56. http://dx.doi.org/10.1016/j.ejor.2020.08.041.
T. Henry de Frahan, Marc, Shashank Yellapantula, Ryan King, Marc S. Day, and Ray W. Grout. "Deep learning for presumed probability density function models." Combustion and Flame 208 (October 2019): 436–50. http://dx.doi.org/10.1016/j.combustflame.2019.07.015.
Xue, Di, Jingmei Li, Tu Lv, Weifei Wu, and Jiaxiang Wang. "Malware Classification Using Probability Scoring and Machine Learning." IEEE Access 7 (2019): 91641–56. http://dx.doi.org/10.1109/access.2019.2927552.
Rojarath, Artitayapron, and Wararat Songpan. "Probability-Weighted Voting Ensemble Learning for Classification Model." Journal of Advances in Information Technology 11, no. 4 (2020): 217–27. http://dx.doi.org/10.12720/jait.11.4.217-227.