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  1. Results that match 1 of 2 words

  2. - 4F13: Machine Learning

    https://mlg.eng.cam.ac.uk/teaching/4f13/0910/lect01.pdf
    19 Nov 2023: Here is a useful statistics / pattern recognition glossary:http://alumni.media.mit.edu/tpminka/statlearn/glossary/glossary.html. Ghahramani & Rasmussen (CUED) Lecture 1: Introduction to Machine Learning January 14th, 2010 26 /
  3. Statistical Causal Inference

    https://mlg.eng.cam.ac.uk/zoubin/SALD/Intro-Causal.pdf
    27 Jan 2023: For example, although poverty may cause crime, we cannot ethically intervene to impoverish people. ... single marginal independence between X1 and X2. This gives many people pause, as it should.
  4. zglactive.dvi

    https://mlg.eng.cam.ac.uk/zoubin/papers/zglactive.pdf
    27 Jan 2023: 1http://www.ai.mit.edu/people/jrennie/20Newsgroups/. 10 20 30 40 500. 100. 200. 300. 400. 500.
  5. Bayesian Structured Prediction using Gaussian Processes Sébastien…

    https://mlg.eng.cam.ac.uk/pub/pdf/BraQuaGha14a.pdf
    13 Feb 2023: 1by Taku Kudo http://crfpp.googlecode.com/svn/trunk/doc/index.html2by Mark Schmidt http://www.di.ens.fr/mschmidt/Software/crfChain.html3by Thorsten Joachims
  6. images/test_user_webdesign.eps

    https://mlg.eng.cam.ac.uk/pub/pdf/IwaShaGha13a.pdf
    13 Feb 2023: zoubin@eng.cam.ac.uk. ABSTRACT. Many people share their activities with others through on-line communities. ... 1. INTRODUCTIONMany people share their activities with others through on-. line communities, such as social sharing, social networking,.
  7. 13 Feb 2023: The first customer takes the first Poisson(α)dishes. The following customers try previously sam-pled dishes with probability mk/n, where mk is thenumber of people who tried dish k
  8. Accelerated sampling for the Indian Buffet Process

    https://mlg.eng.cam.ac.uk/pub/pdf/DosGha09a.pdf
    13 Feb 2023: The first customer takes the first Poisson(α)dishes. The following customers try previously sam-pled dishes with probability mk/n, where mk is thenumber of people who tried dish k
  9. Formatting Instructions for NIPS -8-

    https://mlg.eng.cam.ac.uk/zoubin/papers/JinGha02.pdf
    27 Jan 2023: As will be shown later, this constraint makes it possible for us to build up a purely discriminative approach while for learning problems using unlabeled data people usually take a generative
  10. Variational Inference for Nonparametric Multiple Clustering Yue Guan, …

    https://mlg.eng.cam.ac.uk/pub/pdf/GuaDyNiuetal10.pdf
    13 Feb 2023: For example, face images of people can be grouped basedon their pose or clustered based on the identity of the person. ... 4.2.1 Experiments on Face DataThe face dataset from UCI KDD repository [2] consists of 640 faceimages of 20 people taken at varying
  11. ibpnips4.dvi

    https://mlg.eng.cam.ac.uk/zoubin/papers/ibp-nips05.pdf
    27 Jan 2023: αi1α. Customers areexchangeableunder this process: the probability of a particularseating arrangement depends only on the number of people at each table, and not the orderin which they enter the restaurant.
  12. TCS November 2001, 2nd pages.qxd

    https://mlg.eng.cam.ac.uk/zoubin/papers/WolGhaFla01.pdf
    27 Jan 2023: Movement provides the only means we have to interact with both the worldand other people. ... http://tics.trends.com. 493Review. As stated at the beginning of this article, directinformation transmission between people, such asspeech, arm gestures or
  13. Statistical Models for Partial Membership Katherine A. Heller…

    https://mlg.eng.cam.ac.uk/zoubin/papers/HelWilGha08.pdf
    27 Jan 2023: is expected to be (Are 100% ofthe people themselves 75% “White British” and 25%“Pakistani”? ... Or are 75% of the people 100% “WhiteBritish” and the rest are 100% “Pakistani”?
  14. Bayesian Knowledge Corroboration with LogicalRules and User Feedback…

    https://mlg.eng.cam.ac.uk/pub/pdf/KasVanGraHer10.pdf
    13 Feb 2023: Such tasks could aim at retrieving relations between companies, people,prices, product types, etc. ... The labeled nodes of an ER graph represent entities (e.g., people, locations,products, dates, etc.).
  15. 13 Feb 2023: Recently, the Netflix Grand Prize, a contest todevelop methods for predicting how much people willenjoy a movie according to their movie preferences,was awarded to a team which combined many
  16. SiGMa: Simple Greedy Matching for Aligning Large Knowledge Bases

    https://mlg.eng.cam.ac.uk/pub/pdf/LacPalDav13a.pdf
    13 Feb 2023: We use these categories to construct a list of triplescontaining facts about movies and people. ... wildly inconsistent birthdates for people), indicating that SiGMa could be used tohighlight data inconsistencies between databases.
  17. nips2007-final.dvi

    https://mlg.eng.cam.ac.uk/zoubin/papers/SilChuGha08.pdf
    27 Jan 2023: available at http://people.scs.fsu.edu/burkardt/msrc/rcm/rcm.html. Table 1: The averaged AUC scores of citation prediction on test cases of the Cora database arerecorded along with
  18. griffiths11a.dvi

    https://mlg.eng.cam.ac.uk/pub/pdf/GriGha11.pdf
    13 Feb 2023: 2α. This processcontinues until all customers have seats, defining a distribution over allocations of people to tables,and, more generally, objects to classes.
  19. Bayesian Modelling Zoubin Ghahramani Department of…

    https://mlg.eng.cam.ac.uk/zoubin/talks/lect1bayes.pdf
    27 Jan 2023: If people want to applyit to problems A, B, C, D.
  20. Gaussian Process Regression Networks Andrew Gordon Wilson∗ David A.…

    https://mlg.eng.cam.ac.uk/pub/pdf/WilKnoGha11.pdf
    13 Feb 2023: These datasets can be found in NeilLawrence’s GPSIM toolbox: http://staffwww.dcs.shef.ac.uk/people/N.Lawrence/gpsim/. Typical GPRN (VB) runtimes for the 50D and 1000D datasets were
  21. A Nonparametric Bayesian Model for Multiple Clustering…

    https://mlg.eng.cam.ac.uk/pub/pdf/NiuDyGha12.pdf
    13 Feb 2023: Theface dataset from UCI KDD repository [2] consists of640 face images of 20 people taken at varying poses(straight, left, right, up).
  22. The IBP Compound Dirichlet Process and its Application to Focused…

    https://mlg.eng.cam.ac.uk/pub/pdf/WilWanHelBle10.pdf
    13 Feb 2023: 3Matlab code is available from the authors4http://people.csail.mit.edu/jrennie/20Newsgroups/5http://kdd.ics.uci.edu/databases/reuters21578/. 0 5 10 15 20 25 30 350.
  23. Beyond Dataset Bias: Multi-task UnalignedShared Knowledge Transfer…

    https://mlg.eng.cam.ac.uk/pub/pdf/TomQuaCapLam12.pdf
    13 Feb 2023: 3 From http://www.vision.ee.ethz.ch/pgehler/projects/iccv09/4 DenseHueV3H1 from http://lear.inrialpes.fr/people/guillaumin/data.php5 From http://attributes.kyb.tuebingen.mpg.de/. 12 T.
  24. paper.dvi

    https://mlg.eng.cam.ac.uk/zoubin/papers/GhaGriSol06.pdf
    27 Jan 2023: 6.5. Extracting features from similarity judgments. One of the goals of cognitive psychology is to determine the kinds of representationsthat underlie people’s judgments. ... In particular, a method called “additive cluster-ing” has been used to
  25. ibp6.dvi

    https://mlg.eng.cam.ac.uk/zoubin/papers/ibptr.pdf
    27 Jan 2023: This assumption seems appropriate when describing our friend theRed Sox fan: it is possible to imagine an arbitrarily large set of features that could be used todescribe people, and which subset ... 2α , andthe third table with probabililty α2α. This
  26. OP-CBIO120293 3290..3297

    https://mlg.eng.cam.ac.uk/pub/pdf/KirGriSav12a.pdf
    13 Feb 2023: dances) to be routinely measured for large numbers of people. The development of novel statistical and computational method-.
  27. 27 Jan 2023: 2016. NIPS Royal Society Workshop, People and Machines, Barcelona, SPAIN. Keynote, Bayesian Deep Learning Workshop, NIPS, Barcelona, SPAIN.
  28. Proc. Valencia / ISBA 8th World Meeting on Bayesian ...

    https://mlg.eng.cam.ac.uk/pub/pdf/GhaGriSol07.pdf
    13 Feb 2023: 6.5. Extracting features from similarity judgments. One of the goals of cognitive psychology is to determine the kinds of representationsthat underlie people’s judgments. ... In particular, a method called “additive cluster-ing” has been used to
  29. Bayesian Gaussian Process Classificationwith the EM-EP…

    https://mlg.eng.cam.ac.uk/pub/pdf/KimGha06a.pdf
    13 Feb 2023: 7. The optimization procedure is described in Appendix B in [10] and thecode is available from http://www.kyb.tuebingen.mpg.de/bs/people/carl/code/minimize/.
  30. chu05a.dvi

    https://mlg.eng.cam.ac.uk/pub/pdf/ChuGha05a.pdf
    13 Feb 2023: The goalis to predict a person’s rating on new items given the person’s past ratings on similar items and theratings of other people on all the items (including the
  31. Practical Probabilistic Programming with Monads

    https://mlg.eng.cam.ac.uk/pub/pdf/SciGhaGor15.pdf
    13 Feb 2023: For this reason we include in thepaper some material that may be difficult to read for people with-out deep knowledge of Bayesian statistics.
  32. chu05a.dvi

    https://mlg.eng.cam.ac.uk/zoubin/papers/chu05a.pdf
    27 Jan 2023: The goalis to predict a person’s rating on new items given the person’s past ratings on similar items and theratings of other people on all the items (including the
  33. Bayesian correlated clustering to integrate multiple datasetsPaul…

    https://mlg.eng.cam.ac.uk/pub/pdf/KirGriSavGhaetal12.pdf
    13 Feb 2023: large numbers of people. The development of novel statistical andcomputational methodology for integrating diverse data sources istherefore essential, and it is with this that the present work isconcerned.
  34. 13 Feb 2023: 2006). When applied to a data set where people are asked to choose celebrities. ... of people who sampled dish k before customer n. Each customer also tries.
  35. 27 Jan 2023: Some people prefer tocall this a system or agent. The same mathematical theory of learning applies regardless of what we choose to call the learner,whether it is artificial or biological.
  36. Unsupervised Learning∗ Zoubin Ghahramani† Gatsby Computational…

    https://mlg.eng.cam.ac.uk/zoubin/course05/ul.pdf
    27 Jan 2023: Some people prefer tocall this a system or agent. The same mathematical theory of learning applies regardless of what we choose to call the learner,whether it is artificial or biological.
  37. Bayesian Gaussian Process Classificationwith the EM-EP…

    https://mlg.eng.cam.ac.uk/zoubin/papers/KimGha06-PAMI.pdf
    27 Jan 2023: 7. The optimization procedure is described in Appendix B in [10] and thecode is available from http://www.kyb.tuebingen.mpg.de/bs/people/carl/code/minimize/.
  38. coverage.eps

    https://mlg.eng.cam.ac.uk/pub/pdf/SilHelGhaetal10.pdf
    13 Feb 2023: In their paper, one isinitially given a set of pairwise distances between objects (say, by the sub-jective judgement of a group of people).
  39. manual.dvi

    https://mlg.eng.cam.ac.uk/pub/pdf/RasNeaHinetal96.pdf
    13 Feb 2023: These sections may be of someinterest to all users, but are primarily intended for people who wish to include new datasetsin DELVE, or who wish to create new prototasks and tasks
  40. Bayesian Time Series Learning with Gaussian Processes Roger…

    https://mlg.eng.cam.ac.uk/pub/pdf/Fri15.pdf
    13 Feb 2023: interact with so many talented people.
  41. 13 Feb 2023: iv. Acknowledgements. My time at the University of Cambridge has been filled with a wealth of memorableexperiences and I have been privileged to be surrounded by a multitude of trulyinspirational people. ... Foremost amongst these people has been my
  42. fit-epinions-svec.eps

    https://mlg.eng.cam.ac.uk/pub/pdf/LesChaKleetal10.pdf
    13 Feb 2023: Journal of Machine Learning Research 11 (2010) 985-1042 Submitted 12/08; Revised 8/09; Published 2/10. Kronecker Graphs: An Approach to Modeling Networks. Jure Leskovec JURE@CS.STANFORD.EDUComputer Science DepartmentStanford UniversityStanford, CA
  43. - IB Paper 7: Probability and Statistics

    https://mlg.eng.cam.ac.uk/teaching/1BP7/1819/lect04.pdf
    19 Nov 2023: Waiting times. The bus arrives on average every 15 minutes. Compare the average waiting timefor people arriving randomly if buses 1) arrive regularly, 2) arrive randomly.
  44. 13 Feb 2023: amazing people!
  45. Bayesian Learning forData-Efficient Control Rowan McAllister…

    https://mlg.eng.cam.ac.uk/pub/pdf/Mca16.pdf
    13 Feb 2023: Bayesian Learning forData-Efficient Control. Rowan McAllister. Supervisor: Prof. C.E. Rasmussen. Advisor: Prof. Z. Ghahramani. Department of EngineeringUniversity of Cambridge. This dissertation is submitted for the degree ofDoctor of Philosophy.
  46. 13 Feb 2023: We take a more bold approach. 2 The term nonparametric causes quite a deal of confusion as it often leads people to believewe are working with models with zero parameters when
  47. Computation and Psychophysics ofSensorimotor IntegrationbyZoubin…

    https://mlg.eng.cam.ac.uk/zoubin/papers/thesis.pdf
    27 Jan 2023: Computation and Psychophysics ofSensorimotor IntegrationbyZoubin GhahramaniB.S.E., Computer Science, University of Pennsylvania (1990)B.A., Cognitive Science, University of Pennsylvania (1990)Submitted to the Department of Brain and Cognitive
  48. - IB Paper 7: Probability and Statistics

    https://mlg.eng.cam.ac.uk/teaching/1BP7/1819/lect03.pdf
    19 Nov 2023: The averageincome is very different from the median, since a few people have very largeincomes.
  49. Graph-based Semi-supervised Learning Zoubin Ghahramani Department of…

    https://mlg.eng.cam.ac.uk/zoubin/talks/lect3ssl.pdf
    27 Jan 2023: data, using webcam im-ages of ten people that were collected over a period of sev-eral months. ... People changed. 2Instructions for obtaining the dataset can be found at http://www.cs.cmu.edu/˜zhuxj/freefoodcam.
  50. Variational Inference for the IndianBuffet Process Finale…

    https://mlg.eng.cam.ac.uk/pub/pdf/DosMilVanTeh09b.pdf
    13 Feb 2023: 2. The ith customer then takes dishes that have been previously sampled with probabilitymk/i, where mk is the number of people who have already sampled dish k. ... The Yale Faces (Georghiades et al., 2001)dataset consisted of 721 32x32 pixel frontal-face
  51. Unsupervised Learning∗ Zoubin Ghahramani† Gatsby Computational…

    https://mlg.eng.cam.ac.uk/zoubin/course04/ul.pdf
    27 Jan 2023: Some people prefer tocall this a system or agent. The same mathematical theory of learning applies regardless of what we choose to call the learner,whether it is artificial or biological.

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