Journal articles on the topic 'Learning from Constraints'
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Cropper, Andrew, and Rolf Morel. "Learning programs by learning from failures." Machine Learning 110, no. 4 (February 19, 2021): 801–56. http://dx.doi.org/10.1007/s10994-020-05934-z.
Full textChou, Glen, Dmitry Berenson, and Necmiye Ozay. "Learning constraints from demonstrations with grid and parametric representations." International Journal of Robotics Research 40, no. 10-11 (August 13, 2021): 1255–83. http://dx.doi.org/10.1177/02783649211035177.
Full textOkabe, Masayuki, and Seiji Yamada. "Learning Similarity Matrix from Constraints of Relational Neighbors." Journal of Advanced Computational Intelligence and Intelligent Informatics 14, no. 4 (May 20, 2010): 402–7. http://dx.doi.org/10.20965/jaciii.2010.p0402.
Full textMueller, Carl L. "Abstract Constraints for Safe and Robust Robot Learning from Demonstration." Proceedings of the AAAI Conference on Artificial Intelligence 34, no. 10 (April 3, 2020): 13728–29. http://dx.doi.org/10.1609/aaai.v34i10.7136.
Full textKato, Tsuyoshi, Wataru Fujibuchi, and Kiyoshi Asai. "Learning Kernels from Distance Constraints." IPSJ Digital Courier 2 (2006): 441–51. http://dx.doi.org/10.2197/ipsjdc.2.441.
Full textFarina, Francesco, Stefano Melacci, Andrea Garulli, and Antonio Giannitrapani. "Asynchronous Distributed Learning From Constraints." IEEE Transactions on Neural Networks and Learning Systems 31, no. 10 (October 2020): 4367–73. http://dx.doi.org/10.1109/tnnls.2019.2947740.
Full textHammer, Rubi, Tomer Hertz, Shaul Hochstein, and Daphna Weinshall. "Category learning from equivalence constraints." Cognitive Processing 10, no. 3 (December 3, 2008): 211–32. http://dx.doi.org/10.1007/s10339-008-0243-x.
Full textArmesto, Leopoldo, João Moura, Vladimir Ivan, Mustafa Suphi Erden, Antonio Sala, and Sethu Vijayakumar. "Constraint-aware learning of policies by demonstration." International Journal of Robotics Research 37, no. 13-14 (July 26, 2018): 1673–89. http://dx.doi.org/10.1177/0278364918784354.
Full textHewing, Lukas, Kim P. Wabersich, Marcel Menner, and Melanie N. Zeilinger. "Learning-Based Model Predictive Control: Toward Safe Learning in Control." Annual Review of Control, Robotics, and Autonomous Systems 3, no. 1 (May 3, 2020): 269–96. http://dx.doi.org/10.1146/annurev-control-090419-075625.
Full textWu, Xintao, and Daniel Barbará. "Learning missing values from summary constraints." ACM SIGKDD Explorations Newsletter 4, no. 1 (June 2002): 21–30. http://dx.doi.org/10.1145/568574.568579.
Full textRen, Hongyu, Russell Stewart, Jiaming Song, Volodymyr Kuleshov, and Stefano Ermon. "Learning with Weak Supervision from Physics and Data-Driven Constraints." AI Magazine 39, no. 1 (March 27, 2018): 27–38. http://dx.doi.org/10.1609/aimag.v39i1.2776.
Full textXu, Haoran, Xianyuan Zhan, and Xiangyu Zhu. "Constraints Penalized Q-learning for Safe Offline Reinforcement Learning." Proceedings of the AAAI Conference on Artificial Intelligence 36, no. 8 (June 28, 2022): 8753–60. http://dx.doi.org/10.1609/aaai.v36i8.20855.
Full textOnishi, K. "Learning phonotactic constraints from brief auditory experience." Cognition 83, no. 1 (February 2002): B13—B23. http://dx.doi.org/10.1016/s0010-0277(01)00165-2.
Full textSuraweera, Pramuditha, Geoffrey I. Webb, Ian Evans, and Mark Wallace. "Learning crew scheduling constraints from historical schedules." Transportation Research Part C: Emerging Technologies 26 (January 2013): 214–32. http://dx.doi.org/10.1016/j.trc.2012.08.002.
Full textMoon, In-Ho, and Kevin Harer. "Learning from Constraints for Formal Property Checking." Journal of Electronic Testing 26, no. 2 (February 5, 2010): 243–59. http://dx.doi.org/10.1007/s10836-010-5143-1.
Full textCiravegna, Gabriele, Francesco Giannini, Stefano Melacci, Marco Maggini, and Marco Gori. "A Constraint-Based Approach to Learning and Explanation." Proceedings of the AAAI Conference on Artificial Intelligence 34, no. 04 (April 3, 2020): 3658–65. http://dx.doi.org/10.1609/aaai.v34i04.5774.
Full textGuo, Yufan, Roi Reichart, and Anna Korhonen. "Unsupervised Declarative Knowledge Induction for Constraint-Based Learning of Information Structure in Scientific Documents." Transactions of the Association for Computational Linguistics 3 (December 2015): 131–43. http://dx.doi.org/10.1162/tacl_a_00128.
Full textAlderete, John, Paul Tupper, and Stefan A. Frisch. "Phonological constraint induction in a connectionist network: learning OCP-Place constraints from data." Language Sciences 37 (May 2013): 52–69. http://dx.doi.org/10.1016/j.langsci.2012.10.002.
Full textAhmed, Kareem, Tao Li, Thy Ton, Quan Guo, Kai-Wei Chang, Parisa Kordjamshidi, Vivek Srikumar, Guy Van den Broeck, and Sameer Singh. "PYLON: A PyTorch Framework for Learning with Constraints." Proceedings of the AAAI Conference on Artificial Intelligence 36, no. 11 (June 28, 2022): 13152–54. http://dx.doi.org/10.1609/aaai.v36i11.21711.
Full textGnecco, Giorgio, Marco Gori, Stefano Melacci, and Marcello Sanguineti. "Foundations of Support Constraint Machines." Neural Computation 27, no. 2 (February 2015): 388–480. http://dx.doi.org/10.1162/neco_a_00686.
Full textJi, Chuanyi, Robert R. Snapp, and Demetri Psaltis. "Generalizing Smoothness Constraints from Discrete Samples." Neural Computation 2, no. 2 (June 1990): 188–97. http://dx.doi.org/10.1162/neco.1990.2.2.188.
Full textHoward, Matthew, Stefan Klanke, Michael Gienger, Christian Goerick, and Sethu Vijayakumar. "Behaviour Generation in Humanoids by Learning Potential-Based Policies from Constrained Motion." Applied Bionics and Biomechanics 5, no. 4 (2008): 195–211. http://dx.doi.org/10.1155/2008/316371.
Full textMaggini, Marco, Stefano Melacci, and Lorenzo Sarti. "Learning from pairwise constraints by Similarity Neural Networks." Neural Networks 26 (February 2012): 141–58. http://dx.doi.org/10.1016/j.neunet.2011.10.009.
Full textHüllermeier, Eyke. "Flexible constraints for regularization in learning from data." International Journal of Intelligent Systems 19, no. 6 (April 23, 2004): 525–41. http://dx.doi.org/10.1002/int.20010.
Full textYang, Qisong, Thiago D. Simão, Simon H. Tindemans, and Matthijs T. J. Spaan. "WCSAC: Worst-Case Soft Actor Critic for Safety-Constrained Reinforcement Learning." Proceedings of the AAAI Conference on Artificial Intelligence 35, no. 12 (May 18, 2021): 10639–46. http://dx.doi.org/10.1609/aaai.v35i12.17272.
Full textSmith, Jennifer L. "From experiment results to a constraint hierarchy with the ‘Rank Centrality’ algorithm." Proceedings of the Linguistic Society of America 5, no. 1 (March 23, 2020): 144. http://dx.doi.org/10.3765/plsa.v51.4694.
Full textSmith, Jennifer L. "From experiment results to a constraint hierarchy with the ‘Rank Centrality’ algorithm." Proceedings of the Linguistic Society of America 5, no. 1 (March 23, 2020): 144. http://dx.doi.org/10.3765/plsa.v5i1.4694.
Full textDiallo, Aïssatou, and Johannes Fürnkranz. "Learning Ordinal Embedding from Sets." Entropy 23, no. 8 (July 27, 2021): 964. http://dx.doi.org/10.3390/e23080964.
Full textWah, B. W. "Population-based learning: a method for learning from examples under resource constraints." IEEE Transactions on Knowledge and Data Engineering 4, no. 5 (1992): 454–74. http://dx.doi.org/10.1109/69.166988.
Full textNEUMANN, KLAUS, MATTHIAS ROLF, and JOCHEN JAKOB STEIL. "RELIABLE INTEGRATION OF CONTINUOUS CONSTRAINTS INTO EXTREME LEARNING MACHINES." International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems 21, supp02 (October 31, 2013): 35–50. http://dx.doi.org/10.1142/s021848851340014x.
Full textWarker, Jill A., Gary S. Dell, Christine A. Whalen, and Samantha Gereg. "Limits on learning phonotactic constraints from recent production experience." Journal of Experimental Psychology: Learning, Memory, and Cognition 34, no. 5 (2008): 1289–95. http://dx.doi.org/10.1037/a0013033.
Full textO'Toole, Alice J. "Structure from Stereo by Associative Learning of the Constraints." Perception 18, no. 6 (December 1989): 767–82. http://dx.doi.org/10.1068/p180767.
Full textGao, Shan, Chen Zu, and Daoqiang Zhang. "Learning mid-perpendicular hyperplane similarity from cannot-link constraints." Neurocomputing 113 (August 2013): 195–203. http://dx.doi.org/10.1016/j.neucom.2013.01.002.
Full textEgilmez, Hilmi E., Eduardo Pavez, and Antonio Ortega. "Graph Learning From Data Under Laplacian and Structural Constraints." IEEE Journal of Selected Topics in Signal Processing 11, no. 6 (September 2017): 825–41. http://dx.doi.org/10.1109/jstsp.2017.2726975.
Full textPuchkov, N. P. "Digital Didactics under Distance Learning Constraints." Voprosy sovremennoj nauki i praktiki. Universitet imeni V.I. Vernadskogo, no. 4(82) (2021): 154–64. http://dx.doi.org/10.17277/voprosy.2021.04.pp.154-164.
Full textHayes, Bruce, and Colin Wilson. "A Maximum Entropy Model of Phonotactics and Phonotactic Learning." Linguistic Inquiry 39, no. 3 (July 2008): 379–440. http://dx.doi.org/10.1162/ling.2008.39.3.379.
Full textQin, Xingli, Lingli Zhao, Jie Yang, Pingxiang Li, Bingfang Wu, Kaimin Sun, and Yubin Xu. "Active Pairwise Constraint Learning in Constrained Time-Series Clustering for Crop Mapping from Airborne SAR Imagery." Remote Sensing 14, no. 23 (November 30, 2022): 6073. http://dx.doi.org/10.3390/rs14236073.
Full textBurness, Phillip, and Kevin McMullin. "Post-nasal voicing in Japanese classifiers as exceptional triggering: implications for Indexed Constraint Theory." Canadian Journal of Linguistics/Revue canadienne de linguistique 65, no. 4 (November 9, 2020): 471–95. http://dx.doi.org/10.1017/cnj.2020.26.
Full textO'Sullivan, Barry. "Automated Modelling and Solving in Constraint Programming." Proceedings of the AAAI Conference on Artificial Intelligence 24, no. 1 (July 5, 2010): 1493–97. http://dx.doi.org/10.1609/aaai.v24i1.7530.
Full textMa, Yecheng Jason, Andrew Shen, Osbert Bastani, and Jayaraman Dinesh. "Conservative and Adaptive Penalty for Model-Based Safe Reinforcement Learning." Proceedings of the AAAI Conference on Artificial Intelligence 36, no. 5 (June 28, 2022): 5404–12. http://dx.doi.org/10.1609/aaai.v36i5.20478.
Full textBai, Wenjun, Changqin Quan, and Zhi-Wei Luo. "Improving Generative and Discriminative Modelling Performance by Implementing Learning Constraints in Encapsulated Variational Autoencoders." Applied Sciences 9, no. 12 (June 21, 2019): 2551. http://dx.doi.org/10.3390/app9122551.
Full textDODARO, CARMINE, THOMAS EITER, PAUL OGRIS, and KONSTANTIN SCHEKOTIHIN. "Managing caching strategies for stream reasoning with reinforcement learning." Theory and Practice of Logic Programming 20, no. 5 (September 2020): 625–40. http://dx.doi.org/10.1017/s147106842000037x.
Full textHong, Junyuan, Haotao Wang, Zhangyang Wang, and Jiayu Zhou. "Learning Model-Based Privacy Protection under Budget Constraints." Proceedings of the AAAI Conference on Artificial Intelligence 35, no. 9 (May 18, 2021): 7702–10. http://dx.doi.org/10.1609/aaai.v35i9.16941.
Full textVU, XUAN-HA, and BARRY O'SULLIVAN. "A UNIFYING FRAMEWORK FOR GENERALIZED CONSTRAINT ACQUISITION." International Journal on Artificial Intelligence Tools 17, no. 05 (October 2008): 803–33. http://dx.doi.org/10.1142/s0218213008004175.
Full textAbed Alabaddi, Zaid Ahmad, Arwa Hisham Rahahleh, and Majd Mohammad Al-Omoush. "Blended E-Learning Constraints from the Viewpoint of Faculty Members." International Journal of Business and Management 11, no. 7 (June 21, 2016): 180. http://dx.doi.org/10.5539/ijbm.v11n7p180.
Full textChou, Glen, Necmiye Ozay, and Dmitry Berenson. "Learning Constraints From Locally-Optimal Demonstrations Under Cost Function Uncertainty." IEEE Robotics and Automation Letters 5, no. 2 (April 2020): 3682–90. http://dx.doi.org/10.1109/lra.2020.2974427.
Full textSalih, Majid Mohammed, Usra Ahmed Jarjis, and Nidal Ali Suleiman. "E-learning, application constraints and remedies." Journal of University of Human Development 2, no. 4 (December 31, 2016): 290. http://dx.doi.org/10.21928/juhd.v2n4y2016.pp290-317.
Full textZhan, Shanhua, Weijun Sun, and Peipei Kang. "Robust Latent Common Subspace Learning for Transferable Feature Representation." Electronics 11, no. 5 (March 4, 2022): 810. http://dx.doi.org/10.3390/electronics11050810.
Full textXue, Hansheng, Vijini Mallawaarachchi, Yujia Zhang, Vaibhav Rajan, and Yu Lin. "RepBin: Constraint-Based Graph Representation Learning for Metagenomic Binning." Proceedings of the AAAI Conference on Artificial Intelligence 36, no. 4 (June 28, 2022): 4637–45. http://dx.doi.org/10.1609/aaai.v36i4.20388.
Full textWassermann, Gilbert, and Mark Glickman. "Automated Harmonization of Bass Lines from Bach Chorales: A Hybrid Approach." Computer Music Journal 43, no. 2-3 (June 2020): 142–57. http://dx.doi.org/10.1162/comj_a_00523.
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