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Bayesian Hierarchical Clustering Katherine A. Heller…
https://mlg.eng.cam.ac.uk/zoubin/papers/icml05heller.pdf27 Jan 2023: We show some exam-ples of this in the Results section. 5. -
The Supervised IBP: Neighbourhood PreservingInfinite Latent Feature…
https://mlg.eng.cam.ac.uk/pub/pdf/QuaShaKnoGha13.pdf13 Feb 2023: binary hash. In this setting, we want to extend the ob-served binary representations hn H (for each exam-ple xn) where H{0, 1}D with a latent binary featurezn, -
coverage.eps
https://mlg.eng.cam.ac.uk/pub/pdf/SilHelGhaetal10.pdf13 Feb 2023: 1. Contribution. Many university admission exams, such as the Amer-ican Scholastic Assessment Test (SAT) and Graduate Record Exam (GRE),have historically included a section on analogical reasoning. ... As an illustration, consider an analogical reasoning -
analogy-aistats2007.dvi
https://mlg.eng.cam.ac.uk/zoubin/papers/analogy-aistats2007.pdf27 Jan 2023: In both exam-ples, it is not fully known how to explicitly describeclasses of relations that are believed to exist (and itis a nuisance to select negative examples by hand tolearn ... analogical reasoningquestion from a SAT-like exam where for a given -
BIOINFORMATICS Vol. 20 no. 9 2004, pages 1361–1372DOI:…
https://mlg.eng.cam.ac.uk/pub/pdf/RanAngGha04a.pdf13 Feb 2023: This approach will also allow us to exam-ine the robustness of the inferences with respect to choices inthe prior distribution over parameters and to study differentchoices for the priors. -
Copula-based Kernel Dependency Measures Barnabás Póczos…
https://mlg.eng.cam.ac.uk/pub/pdf/PocGhaSch12.pdf13 Feb 2023: For exam-ple, the bound on the convergence rate of the Rényiand Tsallis information estimator (Pál et al., 2010)suffers from the curse of dimensionality. -
December 8, 2008 5:18 Connection Science connsci Connection…
https://mlg.eng.cam.ac.uk/pub/pdf/DosRoy08.pdf13 Feb 2023: December 8, 2008 5:18 Connection Science connsci. Connection ScienceVol. 00, No. 00, January 2008, 1–21. RESEARCH ARTICLE. Spoken Language Interaction with Model Uncertainty: An. Adaptive Human-Robot Interaction System. Finale Doshia and Nicholas -
Bayesian Knowledge Corroboration with LogicalRules and User Feedback…
https://mlg.eng.cam.ac.uk/pub/pdf/KasVanGraHer10.pdf13 Feb 2023: In: Gamesand Economic Behavior, 56(1), pp. 148–173. Elsevier (2006). 35. Jøsang, A., Marsh, S., Pope, S.: Exploring Different Types of Trust Propagation.In: 4th International Conference on Trust Management -
SiGMa: Simple Greedy Matching for Aligning Large Knowledge Bases
https://mlg.eng.cam.ac.uk/pub/pdf/LacPalDav13a.pdf13 Feb 2023: For exam-ple, the YAGO triple 〈m1, wasCreatedOnDate, 1999-12-11〉forms an entity-property-literal triple. -
Local and global sparse Gaussian process approximations Edward…
https://mlg.eng.cam.ac.uk/zoubin/papers/aistats07localGP.pdf27 Jan 2023: For exam-ple, the NT rectangular covariance matrix between train-ing points and test points is denoted KNT. -
1471-2105-10-242.fm
https://mlg.eng.cam.ac.uk/pub/pdf/SavHelXuetal09.pdf13 Feb 2023: multiple time series. Journal of Business and Economic Statistics2008, 26:78-89. 13. -
TCS November 2001, 2nd pages.qxd
https://mlg.eng.cam.ac.uk/zoubin/papers/WolGhaFla01.pdf27 Jan 2023: Vygotsky thought of as the ‘historicalnature’ of psychological processes – the extent towhich reasoning, memory and categorization areshaped by the social and economic practices of a given. -
PIPPS: Flexible Model-Based Policy Search Robust to the Curse of Chaos
https://mlg.eng.cam.ac.uk/pub/pdf/ParRasPetDoy18.pdf13 Feb 2023: and Pelikan, S. Competitive chaos. Journalof economic theory, 40(1):13–25, 1986. Depeweg, S., Hernández-Lobato, J. -
Gaussian Process Regression Networks Andrew Gordon Wilson∗ David A.…
https://mlg.eng.cam.ac.uk/pub/pdf/WilKnoGha11.pdf13 Feb 2023: Journal of Economic and Social Measurement, 25:59–71. Minka, T. P., Winn, J. -
/users/joe/src/tops/dvips
https://mlg.eng.cam.ac.uk/pub/pdf/GhaHin00a.pdf13 Feb 2023: LETTER Communicated by Volker Tresp. Variational Learning for Switching State-Space Models. Zoubin GhahramaniGeoffrey E. HintonGatsby Computational Neuroscience Unit, University College London, London WC1N3AR, U.K. We introduce a new statistical -
LNAI 3944 - Evaluating Predictive Uncertainty Challenge
https://mlg.eng.cam.ac.uk/pub/pdf/QuiRasSinetal06.pdf13 Feb 2023: 2πvexp. ( ‖y m‖. 2. 2v. ). (2). In some situations more complex predictive densities are appropriate (for exam-ple multi-modal). -
paper.dvi
https://mlg.eng.cam.ac.uk/zoubin/papers/fhmmML.pdf27 Jan 2023: For exam-ple, to represent 30 bits of information about the history of a time sequence, anHMM would need K = 230 distinct states. -
Learning dynamic Bayesian networks
https://mlg.eng.cam.ac.uk/pub/pdf/Gha97a.pdf13 Feb 2023: distribution. For exam p l e, t o represent t h e factoriza- tion (1) we would draw an arc f r o m W to Y b u t n -
LETTER Communicated by Joris Mooij Model Reductions for Inference: ...
https://mlg.eng.cam.ac.uk/pub/pdf/EatGha13a.pdf13 Feb 2023: For exam-ple, given binary variables taking values in {0, 1}, we can use an auxiliaryvariable to turn a degree 3 term into four terms of degree 1 or 2:. -
Max–Planck–Institut f ür biologische KybernetikMax Planck Institute…
https://mlg.eng.cam.ac.uk/pub/pdf/KusPfiCsaRas05.pdf13 Feb 2023: Max–Planck–Institut f ür biologische KybernetikMax Planck Institute for Biological Cybernetics. Technical Report No. 136. Approximate Inference forRobust Gaussian Process. Regression. Malte Kuss1, Tobias Pfingsten1,2, Lehel Csató1,Carl E. -
Gaussian Processes forState Space Models andChange Point Detection…
https://mlg.eng.cam.ac.uk/pub/pdf/Tur11.pdf13 Feb 2023: Gaussian Processes forState Space Models andChange Point Detection. Ryan Darby Turner. Department of Engineering. University of Cambridge. A thesis submitted for the degree of. Doctor of Philosophy. July 17, 2011. b. Acknowledgements. I would like -
Efficient Reinforcement Learning using Gaussian Processes
https://mlg.eng.cam.ac.uk/pub/pdf/Dei10.pdf13 Feb 2023: Faculty of InformaticsInstitute for AnthropomaticsIntelligent Sensor-Actuator-Systems Laboratory (ISAS)Prof. Dr.-Ing. Uwe D. Hanebeck Sensor-Actuator-Systems. Intelligent. Efficient Reinforcement Learningusing Gaussian Processes. Marc Peter -
BIOINFORMATICS Vol. 20 no. 9 2004, pages 1361–1372DOI:…
https://mlg.eng.cam.ac.uk/zoubin/papers/Bioinformatics04rangel.pdf27 Jan 2023: This approach will also allow us to exam-ine the robustness of the inferences with respect to choices inthe prior distribution over parameters and to study differentchoices for the priors. -
Generalised Bayesian Matrix Factorisation Models Shakir Mohamed St…
https://mlg.eng.cam.ac.uk/pub/pdf/Moh11.pdf13 Feb 2023: 1.1 The Ubiquitous Latent Variable. Models with latent variables hold a central role in in the analysis of data in a diverseset of research areas spanning machine learning, statistics, economics, -
erice-top.dvi
https://mlg.eng.cam.ac.uk/zoubin/papers/varintro.pdf27 Jan 2023: particular exam-ples, but we are not as yet able to provide assurance that the frameworkwill transfer easily to other examples.We begin in Section 2 with a brief overview of -
Scalable Inference for StructuredGaussian Process Models Yunus…
https://mlg.eng.cam.ac.uk/pub/pdf/Saa11.pdf13 Feb 2023: Scalable Inference for StructuredGaussian Process Models. Yunus Saatçi. St. Edmund’s College. University of Cambridge. This dissertation is submitted for the degree of. Doctor of Philosophy. December 15, 2011. Preface. This thesis contributes to -
Bayesian Learning forData-Efficient Control Rowan McAllister…
https://mlg.eng.cam.ac.uk/pub/pdf/Mca16.pdf13 Feb 2023: Learning control of dynamical systems is a broad subject. Applications rangeform industrial (refining, manufacturing, power), transportation, logistics, electron-ics, robotics, computer science, to economics. ... There is themathematics community -
thesis.dvi
https://mlg.eng.cam.ac.uk/pub/pdf/Ras96b.pdf13 Feb 2023: EVALUATION OF GAUSSIAN PROCESSES AND. OTHER METHODS FOR NON-LINEAR REGRESSION. Carl Edward Rasmussen. A thesis submitted in conformity with the requirements. for the degree of Doctor of Philosophy,. Graduate Department of Computer Science,. in the
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