Journal articles on the topic 'Kernel Inference'
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Nishiyama, Yu, Motonobu Kanagawa, Arthur Gretton, and Kenji Fukumizu. "Model-based kernel sum rule: kernel Bayesian inference with probabilistic models." Machine Learning 109, no. 5 (January 2, 2020): 939–72. http://dx.doi.org/10.1007/s10994-019-05852-9.
Rogers, Mark F., Colin Campbell, and Yiming Ying. "Probabilistic Inference of Biological Networks via Data Integration." BioMed Research International 2015 (2015): 1–9. http://dx.doi.org/10.1155/2015/707453.
LUGO-MARTINEZ, JOSE, and PREDRAG RADIVOJAC. "Generalized graphlet kernels for probabilistic inference in sparse graphs." Network Science 2, no. 2 (August 2014): 254–76. http://dx.doi.org/10.1017/nws.2014.14.
Lazarus, Eben, Daniel J. Lewis, and James H. Stock. "The Size‐Power Tradeoff in HAR Inference." Econometrica 89, no. 5 (2021): 2497–516. http://dx.doi.org/10.3982/ecta15404.
Billio, M. "Kernel-Based Indirect Inference." Journal of Financial Econometrics 1, no. 3 (September 1, 2003): 297–326. http://dx.doi.org/10.1093/jjfinec/nbg014.
Zhang, Li Lyna, Shihao Han, Jianyu Wei, Ningxin Zheng, Ting Cao, and Yunxin Liu. "nn-METER." GetMobile: Mobile Computing and Communications 25, no. 4 (March 30, 2022): 19–23. http://dx.doi.org/10.1145/3529706.3529712.
Robinson, P. M. "INFERENCE ON NONPARAMETRICALLY TRENDING TIME SERIES WITH FRACTIONAL ERRORS." Econometric Theory 25, no. 6 (December 2009): 1716–33. http://dx.doi.org/10.1017/s0266466609990302.
Yuan, Ao. "Semiparametric inference with kernel likelihood." Journal of Nonparametric Statistics 21, no. 2 (February 2009): 207–28. http://dx.doi.org/10.1080/10485250802553382.
Cheng, Yansong, and Surajit Ray. "Multivariate Modality Inference Using Gaussian Kernel." Open Journal of Statistics 04, no. 05 (2014): 419–34. http://dx.doi.org/10.4236/ojs.2014.45041.
Agbokou, Komi, and Yaogan Mensah. "INFERENCE ON THE REPRODUCING KERNEL HILBERT SPACES." Universal Journal of Mathematics and Mathematical Sciences 15 (October 10, 2021): 11–29. http://dx.doi.org/10.17654/2277141722002.
Memisevic, R., L. Sigal, and D. J. Fleet. "Shared Kernel Information Embedding for Discriminative Inference." IEEE Transactions on Pattern Analysis and Machine Intelligence 34, no. 4 (April 2012): 778–90. http://dx.doi.org/10.1109/tpami.2011.154.
Maswadah, M. "Kernel Inference on the Inverse Weibull Distribution." Communications for Statistical Applications and Methods 13, no. 3 (December 31, 2006): 503–12. http://dx.doi.org/10.5351/ckss.2006.13.3.503.
Racine, Jeffrey S., and James G. MacKinnon. "Inference via kernel smoothing of bootstrap values." Computational Statistics & Data Analysis 51, no. 12 (August 2007): 5949–57. http://dx.doi.org/10.1016/j.csda.2006.11.013.
Sun, Yixiao, and Jingjing Yang. "Testing-optimal kernel choice in HAR inference." Journal of Econometrics 219, no. 1 (November 2020): 123–36. http://dx.doi.org/10.1016/j.jeconom.2020.06.007.
Kondratyev, Dmitry A. "Towards Automatic Deductive Verification of C Programs with Sisal Loops Using the C-lightVer System." Modeling and Analysis of Information Systems 28, no. 4 (December 18, 2021): 372–93. http://dx.doi.org/10.18255/1818-1015-2021-4-372-393.
Lei, Zijian, and Liang Lan. "Memory and Computation-Efficient Kernel SVM via Binary Embedding and Ternary Model Coefficients." Proceedings of the AAAI Conference on Artificial Intelligence 35, no. 9 (May 18, 2021): 8316–23. http://dx.doi.org/10.1609/aaai.v35i9.17011.
Cawley, Gavin C., and Nicola L. C. Talbot. "Kernel learning at the first level of inference." Neural Networks 53 (May 2014): 69–80. http://dx.doi.org/10.1016/j.neunet.2014.01.011.
Wang, Kai. "Conditional asymptotic inference for the kernel association test." Bioinformatics 33, no. 23 (August 14, 2017): 3733–39. http://dx.doi.org/10.1093/bioinformatics/btx511.
Lu, Chi-Ken, and Patrick Shafto. "Conditional Deep Gaussian Processes: Empirical Bayes Hyperdata Learning." Entropy 23, no. 11 (October 23, 2021): 1387. http://dx.doi.org/10.3390/e23111387.
Kumar, Mukesh, and Santanu Kumar Rath. "Classification of Microarray Data Using Kernel Fuzzy Inference System." International Scholarly Research Notices 2014 (August 21, 2014): 1–18. http://dx.doi.org/10.1155/2014/769159.
Massaroppe, Lucas, and Luiz Baccalá. "Kernel Methods for Nonlinear Connectivity Detection." Entropy 21, no. 6 (June 20, 2019): 610. http://dx.doi.org/10.3390/e21060610.
Stordal, Andreas S., Rafael J. Moraes, Patrick N. Raanes, and Geir Evensen. "p-Kernel Stein Variational Gradient Descent for Data Assimilation and History Matching." Mathematical Geosciences 53, no. 3 (March 17, 2021): 375–93. http://dx.doi.org/10.1007/s11004-021-09937-x.
Auzina, Ilze A., and Jakub M. Tomczak. "Approximate Bayesian Computation for Discrete Spaces." Entropy 23, no. 3 (March 6, 2021): 312. http://dx.doi.org/10.3390/e23030312.
Xiao, Chengcheng, Xiaowen Liu, Chi Sun, Zhongyu Liu, and Enjie Ding. "Hierarchical Prototypes Polynomial Softmax Loss Function for Visual Classification." Applied Sciences 12, no. 20 (October 13, 2022): 10336. http://dx.doi.org/10.3390/app122010336.
Liang, Junjie, Yanting Wu, Dongkuan Xu, and Vasant G. Honavar. "Longitudinal Deep Kernel Gaussian Process Regression." Proceedings of the AAAI Conference on Artificial Intelligence 35, no. 10 (May 18, 2021): 8556–64. http://dx.doi.org/10.1609/aaai.v35i10.17038.
Nie, Junlan, Ruibo Gao, and Ye Kang. "Urban Noise Inference Model Based on Multiple Views and Kernel Tensor Decomposition." Fluctuation and Noise Letters 20, no. 03 (January 25, 2021): 2150027. http://dx.doi.org/10.1142/s0219477521500279.
Hou, Yuxin, Ari Heljakka, and Arno Solin. "Gaussian Process Priors for View-Aware Inference." Proceedings of the AAAI Conference on Artificial Intelligence 35, no. 9 (May 18, 2021): 7762–70. http://dx.doi.org/10.1609/aaai.v35i9.16948.
Maswadah, Mohamed, and Seham Mohamed. "Bayesian Inference on the Generalized Exponential Distribution Based on the Kernel Prior." Science Journal of Applied Mathematics and Statistics 12, no. 2 (May 17, 2024): 29–36. http://dx.doi.org/10.11648/j.sjams.20241202.12.
Wang, Qihuan, Haolin Yang, Qianghao He, Dong Yue, Ce Zhang, and Duanyang Geng. "Real-Time Detection System of Broken Corn Kernels Based on BCK-YOLOv7." Agronomy 13, no. 7 (June 28, 2023): 1750. http://dx.doi.org/10.3390/agronomy13071750.
Zhang, Rui, Christian Walder, and Marian-Andrei Rizoiu. "Variational Inference for Sparse Gaussian Process Modulated Hawkes Process." Proceedings of the AAAI Conference on Artificial Intelligence 34, no. 04 (April 3, 2020): 6803–10. http://dx.doi.org/10.1609/aaai.v34i04.6160.
Cui, Chen, Shengyi Jiang, and Bruno C. d. S. Oliveira. "Greedy Implicit Bounded Quantification." Proceedings of the ACM on Programming Languages 7, OOPSLA2 (October 16, 2023): 2083–111. http://dx.doi.org/10.1145/3622871.
Teng, Tong, Jie Chen, Yehong Zhang, and Bryan Kian Hsiang Low. "Scalable Variational Bayesian Kernel Selection for Sparse Gaussian Process Regression." Proceedings of the AAAI Conference on Artificial Intelligence 34, no. 04 (April 3, 2020): 5997–6004. http://dx.doi.org/10.1609/aaai.v34i04.6061.
Gudmundarson, Ragnar L., and Gareth W. Peters. "Assessing portfolio diversification via two-sample graph kernel inference. A case study on the influence of ESG screening." PLOS ONE 19, no. 4 (April 16, 2024): e0301804. http://dx.doi.org/10.1371/journal.pone.0301804.
Rocha, Gustavo H. M. A., Rosangela H. Loschi, and Reinaldo B. Arellano-Valle. "Inference in flexible families of distributions with normal kernel." Statistics 47, no. 6 (December 2013): 1184–206. http://dx.doi.org/10.1080/02331888.2012.688207.
Gao, Junbin, Paul W. Kwan, and Daming Shi. "Sparse kernel learning with LASSO and Bayesian inference algorithm." Neural Networks 23, no. 2 (March 2010): 257–64. http://dx.doi.org/10.1016/j.neunet.2009.07.001.
Capobianco, Enrico. "Kernel methods and flexible inference for complex stochastic dynamics." Physica A: Statistical Mechanics and its Applications 387, no. 16-17 (July 2008): 4077–98. http://dx.doi.org/10.1016/j.physa.2008.03.003.
Lam, Clifford, and Jianqing Fan. "Profile-kernel likelihood inference with diverging number of parameters." Annals of Statistics 36, no. 5 (October 2008): 2232–60. http://dx.doi.org/10.1214/07-aos544.
Li, Bochong, and Lingchong You. "Stochastic Sensitivity Analysis and Kernel Inference via Distributional Data." Biophysical Journal 107, no. 5 (September 2014): 1247–55. http://dx.doi.org/10.1016/j.bpj.2014.07.025.
Li, Degui, Peter C. B. Phillips, and Jiti Gao. "Kernel-based Inference in Time-Varying Coefficient Cointegrating Regression." Journal of Econometrics 215, no. 2 (April 2020): 607–32. http://dx.doi.org/10.1016/j.jeconom.2019.10.005.
Patel, Zeel B., Palak Purohit, Harsh M. Patel, Shivam Sahni, and Nipun Batra. "Accurate and Scalable Gaussian Processes for Fine-Grained Air Quality Inference." Proceedings of the AAAI Conference on Artificial Intelligence 36, no. 11 (June 28, 2022): 12080–88. http://dx.doi.org/10.1609/aaai.v36i11.21467.
Ren, Ming, Chi Cheung, and Gao Xiao. "Gaussian Process Based Bayesian Inference System for Intelligent Surface Measurement." Sensors 18, no. 11 (November 21, 2018): 4069. http://dx.doi.org/10.3390/s18114069.
Song, Le, Kenji Fukumizu, and Arthur Gretton. "Kernel Embeddings of Conditional Distributions: A Unified Kernel Framework for Nonparametric Inference in Graphical Models." IEEE Signal Processing Magazine 30, no. 4 (July 2013): 98–111. http://dx.doi.org/10.1109/msp.2013.2252713.
González-Vanegas, Wilson, Andrés Álvarez-Meza, José Hernández-Muriel, and Álvaro Orozco-Gutiérrez. "AKL-ABC: An Automatic Approximate Bayesian Computation Approach Based on Kernel Learning." Entropy 21, no. 10 (September 24, 2019): 932. http://dx.doi.org/10.3390/e21100932.
Huh, Jaeseok, Jonghun Park, Dongmin Shin, and Yerim Choi. "A Hierarchical SVM Based Behavior Inference of Human Operators Using a Hybrid Sequence Kernel." Sustainability 11, no. 18 (September 4, 2019): 4836. http://dx.doi.org/10.3390/su11184836.
Lee, Dong-Yeong, Hayotjon Aliev, Muhammad Junaid, Sang-Bo Park, Hyung-Won Kim, Keon-Myung Lee, and Sang-Hoon Sim. "High-Speed CNN Accelerator SoC Design Based on a Flexible Diagonal Cyclic Array." Electronics 13, no. 8 (April 19, 2024): 1564. http://dx.doi.org/10.3390/electronics13081564.
Mohanty, Pete, and Robert Shaffer. "Messy Data, Robust Inference? Navigating Obstacles to Inference with bigKRLS." Political Analysis 27, no. 2 (September 26, 2018): 127–44. http://dx.doi.org/10.1017/pan.2018.33.
Dixit, Purushottam D. "Introducing User-Prescribed Constraints in Markov Chains for Nonlinear Dimensionality Reduction." Neural Computation 31, no. 5 (May 2019): 980–97. http://dx.doi.org/10.1162/neco_a_01184.
Ueda, K. "Design of the Kernel Language for the Parallel Inference Machine." Computer Journal 33, no. 6 (June 1, 1990): 494–500. http://dx.doi.org/10.1093/comjnl/33.6.494.
Tsionas, Efthymios G. "Bayesian inference in time series models using kernel quasi likelihoods." Statistica Neerlandica 56, no. 3 (August 2002): 285–94. http://dx.doi.org/10.1111/1467-9574.04800.
Cai, Qianfeng, Zhifeng Hao, and Xiaowei Yang. "Gaussian kernel-based fuzzy inference systems for high dimensional regression." Neurocomputing 77, no. 1 (February 2012): 197–204. http://dx.doi.org/10.1016/j.neucom.2011.09.005.