Search results for "Pseudo-likelihood"

Hits ?▲	Authors	Title	Venue	Year	Link	Author keywords
51	Clare A. McGrory, D. M. Titterington, R. Reeves, Anthony N. Pettitt	Variational Bayes for estimating the parameters of a hidden Potts model.	Stat. Comput.	2009	DBLP DOI BibTeX RDF	Potts/Ising model, Hidden Markov random field, Variational approximation, Pseudo-likelihood, Reduced dependence approximation, Bayesian inference
51	Filip Korc, Wolfgang Förstner	Approximate Parameter Learning in Conditional Random Fields: An Empirical Investigation.	DAGM-Symposium	2008	DBLP DOI BibTeX RDF	Approximate parameter learning, pseudo-likelihood, Markov Random Field, Conditional Random Field
50	Alexandre L. M. Levada, Nelson D. A. Mascarenhas, Alberto Tannús, Denis H. P. Salvadeo	Spatially non-homogeneous potts model parameter estimation on higher-order neighborhood systems by maximum pseudo-likelihood.	SAC	2008	DBLP DOI BibTeX RDF	contextual classification, maximum pseudo-likelihood, spatially non-homogeneous potts model, Markov random fields
47	Alexandre L. M. Levada, Nelson D. A. Mascarenhas, Alberto Tannús	Improving Potts MRF Model Parameter Estimation in Image Analysis.	CSE	2008	DBLP DOI BibTeX RDF	Maximum Pseudo-Likelihood Estimation, Markov Random Fields, Image Analysis, Potts model
40	Shuyang Sun, Jianzhong Chen, Dayou Liu, Chengmin Sun	A Posterior-Based Method for Markov Logic Networks Parameters Learning.	IEEE ICCI	2006	DBLP DOI BibTeX RDF
36	Antonino Freno, Edmondo Trentin, Marco Gori	Scalable pseudo-likelihood estimation in hybrid random fields.	KDD	2009	DBLP DOI BibTeX RDF	hybrid random fields, scalability, bayesian networks, modularity, markov random fields
36	Alexandre L. M. Levada, Nelson D. A. Mascarenhas, Alberto Tannús	A novel pseudo-likelihood equation for Potts MRF model parameter estimation in image analysis.	ICIP	2008	DBLP DOI BibTeX RDF
33	Matthew Richardson, Pedro M. Domingos	Markov logic networks.	Mach. Learn.	2006	DBLP DOI BibTeX RDF	Knowledge-based model construction, Pseudo-likelihood, Markov random fields, Satisfiability, First-order logic, Graphical models, Markov chain Monte Carlo, Inductive logic programming, Link prediction, Statistical relational learning, Markov networks, Log-linear models
29	Sunho Park, Seungjin Choi	Gaussian processes for source separation.	ICASSP	2008	DBLP DOI BibTeX RDF
27	Cédric Herzet	On the convergence of the iterative "pseudo likelihood" maximization algorithm.	ICASSP	2008	DBLP DOI BibTeX RDF
25	Jianwen Xu, Jiamao Zhang, Liya Fu	Variable selection in generalized estimating equations via empirical likelihood and Gaussian pseudo-likelihood.	Commun. Stat. Simul. Comput.	2019	DBLP DOI BibTeX RDF
25	Marijtje A. J. Van Duijn, Krista Gile, Mark S. Handcock	A framework for the comparison of maximum pseudo-likelihood and maximum likelihood estimation of exponential family random graph models.	Soc. Networks	2009	DBLP DOI BibTeX RDF
25	Erning Li, Daowen Zhang, Marie Davidian	Likelihood and pseudo-likelihood methods for semiparametric joint models for a primary endpoint and longitudinal data.	Comput. Stat. Data Anal.	2007	DBLP DOI BibTeX RDF
18	Marenglen Biba, Stefano Ferilli, Floriana Esposito	Towards Multistrategic Statistical Relational Learning.	Advances in Machine Learning II	2010	DBLP DOI BibTeX RDF
17	Sacha Morin, Robin Legault, Zsuzsa Bakk, Charles-Édouard Giguère, Roxane de la Sablonnière, Éric Lacourse	StepMix: A Python Package for Pseudo-Likelihood Estimation of Generalized Mixture Models with External Variables.	CoRR	2023	DBLP DOI BibTeX RDF
17	Theo Gruner, Boris Belousov, Fabio Muratore, Daniel Palenicek, Jan Peters 0001	Pseudo-Likelihood Inference.	CoRR	2023	DBLP DOI BibTeX RDF
17	Theo Gruner, Boris Belousov, Fabio Muratore, Daniel Palenicek, Jan R. Peters	Pseudo-Likelihood Inference.	NeurIPS	2023	DBLP BibTeX RDF
17	Kimmo Suotsalo, Yingying Xu, Jukka Corander, Johan Pensar	High-dimensional structure learning of sparse vector autoregressive models using fractional marginal pseudo-likelihood.	Stat. Comput.	2021	DBLP DOI BibTeX RDF
17	Martin Slawski, Guoqing Diao, Emanuel Ben-David	A Pseudo-Likelihood Approach to Linear Regression With Partially Shuffled Data.	J. Comput. Graph. Stat.	2021	DBLP DOI BibTeX RDF
17	Jun Zhao 0018, Renzhou Gui, Xudong Dong 0001	PHD Filtering for Multi-Source DOA Tracking With Extended Co-Prime Array: An Improved MUSIC Pseudo-Likelihood.	IEEE Commun. Lett.	2021	DBLP DOI BibTeX RDF
17	Avni Rajpal, M. V. Achuth Rao, Chiranjeevi Yarra, Ritu Aggarwal, Prasanta Kumar Ghosh	Pseudo Likelihood Correction Technique for Low Resource Accented ASR.	ICASSP	2020	DBLP DOI BibTeX RDF
17	Amit More, Subhasis Chaudhuri	A Pseudo-likelihood Approach for Geo-localization of Events from Crowd-sourced Sensor-Metadata.	ACM Trans. Multim. Comput. Commun. Appl.	2019	DBLP DOI BibTeX RDF
17	Martin Slawski, Guoqing Diao, Emanuel Ben-David	A Pseudo-Likelihood Approach to Linear Regression with Partially Shuffled Data.	CoRR	2019	DBLP BibTeX RDF
17	Chunpeng Fan	A pseudo likelihood approach to analyze rate difference of binary response data in longitudinal factorial studies.	Commun. Stat. Simul. Comput.	2018	DBLP DOI BibTeX RDF
17	Jiafan Zhu, Luay Nakhleh	Inference of species phylogenies from bi-allelic markers using pseudo-likelihood.	Bioinform.	2018	DBLP DOI BibTeX RDF
17	Janne Leppä-aho, Johan Pensar, Teemu Roos, Jukka Corander	Learning Gaussian graphical models with fractional marginal pseudo-likelihood.	Int. J. Approx. Reason.	2017	DBLP DOI BibTeX RDF
17	Cinzia Daraio, Francesco Fabbri, Giulia Gavazzi, Maria Grazia Izzo, Luca Leuzzi, Giammarco Quaglia, Giancarlo Ruocco	Assessing the Interdependencies between Scientific Disciplinary Profiles at the Country Level: a Pseudo-Likelihood Approach.	ISSI	2017	DBLP BibTeX RDF
17	Liu-Cang Wu, Zhongzhan Zhang, Guo-Liang Tian, Dengke Xu	A Robust Variable Selection to t-type Joint Generalized Linear Models via Penalized t-type Pseudo-likelihood.	Commun. Stat. Simul. Comput.	2016	DBLP DOI BibTeX RDF
17	Hien Duy Nguyen, Ian A. Wood	A Block Successive Lower-Bound Maximization Algorithm for the Maximum Pseudo-Likelihood Estimation of Fully Visible Boltzmann Machines.	Neural Comput.	2016	DBLP DOI BibTeX RDF
17	Janne Leppä-aho, Johan Pensar, Teemu Roos, Jukka Corander	Learning Gaussian Graphical Models With Fractional Marginal Pseudo-likelihood.	CoRR	2016	DBLP BibTeX RDF
17	P. K. Srijith, Balamurugan Palaniappan, Shirish K. Shevade	Gaussian Process Pseudo-Likelihood Models for Sequence Labeling.	ECML/PKDD (1)	2016	DBLP DOI BibTeX RDF
17	Wei Liu, Bo Zhang, Zhiwei Zhang, Baojiang Chen, Xiao-Hua Zhou	A pseudo-likelihood approach for estimating diagnostic accuracy of multiple binary medical tests.	Comput. Stat. Data Anal.	2015	DBLP DOI BibTeX RDF
17	Sang-Yun Oh, Onkar Dalal, Kshitij Khare, Bala Rajaratnam	Optimization Methods for Sparse Pseudo-Likelihood Graphical Model Selection.	CoRR	2014	DBLP BibTeX RDF
17	P. K. Srijith, Balamurugan P., Shirish K. Shevade	Gaussian Process Pseudo-Likelihood Models for Sequence Labeling.	CoRR	2014	DBLP BibTeX RDF
17	Teemu Ruokolainen, Miikka Silfverberg, Mikko Kurimo, Krister Lindén	Accelerated Estimation of Conditional Random Fields using a Pseudo-Likelihood-inspired Perceptron Variant.	EACL	2014	DBLP DOI BibTeX RDF
17	Sang-Yun Oh, Onkar Dalal, Kshitij Khare, Bala Rajaratnam	Optimization Methods for Sparse Pseudo-Likelihood Graphical Model Selection.	NIPS	2014	DBLP BibTeX RDF
17	Praveen Babu Choppala, Paul D. Teal, Marcus R. Frean	Adapting the multi-Bernoulli filter to phased array observations using MUSIC as pseudo-likelihood.	FUSION	2014	DBLP BibTeX RDF
17	Antonino Freno	Semiparametric Pseudo-Likelihood Estimation in Markov Random Fields.	AISTATS	2012	DBLP BibTeX RDF
17	Gaolei Fei, Guangmin Hu	Temporal dependence network loss tomography using maximum pseudo likelihood method.	ICOIN	2012	DBLP DOI BibTeX RDF
17	Qiang Liu 0001, Alexander Ihler	Distributed Parameter Estimation via Pseudo-likelihood .	ICML	2012	DBLP BibTeX RDF
17	Oliver Schulte	A Tractable Pseudo-Likelihood Function for Bayes Nets Applied to Relational Data.	SDM	2011	DBLP DOI BibTeX RDF
17	Wenhui Wang, Juan Nunez-Iglesias, Yihui Luan, Fengzhu Sun	Usefulness and limitations of dK random graph models to predict interactions and functional homogeneity in biological networks under a pseudo-likelihood parameter estimation approach.	BMC Bioinform.	2009	DBLP DOI BibTeX RDF
17	Ana Luísa Dine Martins, Alexandre L. M. Levada, Murillo R. P. Homem, Nelson D. A. Mascarenhas	Map-MRF Super-Resolution Image Reconstruction using Maximum Pseudo-Likelihood parameter estimation.	ICIP	2009	DBLP DOI BibTeX RDF
17	Ole F. Christensen, Asger Hobolth, Jens Ledet Jensen	Pseudo-Likelihood Analysis of Codon Substitution Models with Neighbor-Dependent Rates.	J. Comput. Biol.	2005	DBLP DOI BibTeX RDF
17	Annibale Biggeri, Emanuela Dreassi, Corrado Lagazio, Dankmar Böhning	A transitional non-parametric maximum pseudo-likelihood estimator for disease mapping.	Comput. Stat. Data Anal.	2003	DBLP DOI BibTeX RDF
17	Gang Liang, Bin Yu 0001	Maximum pseudo likelihood estimation in network tomography.	IEEE Trans. Signal Process.	2003	DBLP DOI BibTeX RDF
17	Gang Liang, Bin Yu 0001	Pseudo Likelihood Estimation in Network Tomography.	INFOCOM	2003	DBLP DOI BibTeX RDF
17	Jan-Olof Johansson	Parameter-estimation in the auto-binomial model using the coding- and pseudo-likelihood method approached with simulated annealing and numerical optimization.	Pattern Recognit. Lett.	2001	DBLP DOI BibTeX RDF
17	Peter S. Craig, Allan H. Seheult	Pseudo-likelihood estimation for a class of spatial Markov chains.	Stat. Comput.	1996	DBLP DOI BibTeX RDF
14	Francesco Lagona	Adjacency selection in Markov Random Fields for high spatial resolution hyperspectral data.	J. Geogr. Syst.	2002	DBLP DOI BibTeX RDF
10	Stanley Kok, Pedro M. Domingos	Learning Markov logic network structure via hypergraph lifting.	ICML	2009	DBLP DOI BibTeX RDF
10	Pedro M. Domingos, Daniel Lowd, Stanley Kok, Hoifung Poon, Matthew Richardson, Parag Singla	Just Add Weights: Markov Logic for the Semantic Web.	URSW (LNCS Vol.)	2008	DBLP DOI BibTeX RDF
10	Alexandre L. M. Levada, Nelson D. A. Mascarenhas, Alberto Tannús	On the asymptotic variances of Gaussian Markov Random Field model hyperparameters in stochastic image modeling.	ICPR	2008	DBLP DOI BibTeX RDF
10	Pedro M. Domingos, Stanley Kok, Daniel Lowd, Hoifung Poon, Matthew Richardson, Parag Singla	Markov Logic.	Probabilistic Inductive Logic Programming	2008	DBLP DOI BibTeX RDF
10	Tijmen Tieleman	Training restricted Boltzmann machines using approximations to the likelihood gradient.	ICML	2008	DBLP DOI BibTeX RDF
10	François Destrempes, Max Mignotte, Jean-François Angers	Localization of Shapes Using Statistical Models and Stochastic Optimization.	IEEE Trans. Pattern Anal. Mach. Intell.	2007	DBLP DOI BibTeX RDF	Shape localization, Exploration/Selection (E/S) algorithm, statistical model, stochastic optimization, Probabilistic Principal Component Analysis (PPCA)
10	Pedro M. Domingos	Learning, Logic, and Probability: A Unified View.	PRICAI	2006	DBLP DOI BibTeX RDF
10	Pedro M. Domingos	Learning, Logic, and Probability: A Unified View.	EKAW	2006	DBLP DOI BibTeX RDF
10	Zhuowen Tu, Xiang Sean Zhou, Dorin Comaniciu, Luca Bogoni	A Learning Based Approach for 3D Segmentation and Colon Detagging.	ECCV (3)	2006	DBLP DOI BibTeX RDF
10	Pedro M. Domingos	Learning, Logic, and Probability: A Unified View.	IBERAMIA-SBIA	2006	DBLP DOI BibTeX RDF
10	M. Sabry Hassouna, Aly A. Farag	Stochastic segmentation of blood vessels from time-of-flight.	ICIP (1)	2005	DBLP DOI BibTeX RDF
10	Stanley Kok, Pedro M. Domingos	Learning the structure of Markov logic networks.	ICML	2005	DBLP DOI BibTeX RDF
10	Pedro M. Domingos	Learning, Logic, and Probability: A Unified View.	ALT	2004	DBLP DOI BibTeX RDF
10	Pedro M. Domingos	Learning, Logic, and Probability: A Unified View.	ILP	2004	DBLP DOI BibTeX RDF
10	Peter Carbonetto, Nando de Freitas, Kobus Barnard	A Statistical Model for General Contextual Object Recognition.	ECCV (1)	2004	DBLP DOI BibTeX RDF
10	Michal Haindl	Recursive Square-Root Filters.	ICPR	2000	DBLP DOI BibTeX RDF