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  1. Results that match 1 of 2 words

  2. zglactive.dvi

    https://mlg.eng.cam.ac.uk/zoubin/papers/zglactive.pdf
    27 Jan 2023: Combining Active Learning and Semi-Supervised LearningUsing Gaussian Fields and Harmonic Functions. Xiaojin Zhu. ZHUXJ@CS.CMU.EDUJohn Lafferty. LAFFERTY@CS.CMU.EDU. Zoubin Ghahramani. ZOUBIN@GATSBY.UCL.AC.UKSchool of Computer Science, Carnegie
  3. The Infinite Hidden Markov Model Matthew J. Beal Zoubin ...

    https://mlg.eng.cam.ac.uk/pub/pdf/BeaGhaRas02.pdf
    13 Feb 2023: The Infinite Hidden Markov Model. Matthew J. Beal Zoubin Ghahramani Carl Edward Rasmussen. Gatsby Computational Neuroscience UnitUniversity College London. 17 Queen Square, London WC1N 3AR, Englandhttp://www.gatsby.ucl.ac.uk. {m.beal,zoubin,edward
  4. Methods for Inference in Graphical Models

    https://mlg.eng.cam.ac.uk/adrian/phd_FINAL.pdf
    16 Jul 2024: 3 Additional Background 24. 3.1 MAP Inference and Tractable Cases. 24.
  5. 13 Feb 2023: 0897 1.0720 0.0855Sugar process 7 268 571 4 0.3323 0.0010 0.3303 0.0009 0.2242 0.0009Dorrit 27 551 24 5 0.5556 0.0075 ... In this experimentwith about 2.24 million training points, it took about0.5 hour to complete 100 iterations of the EM algo-rithm on
  6. doi:10.1016/j.patrec.2005.09.027

    https://mlg.eng.cam.ac.uk/pub/pdf/KimKimGha06a.pdf
    13 Feb 2023: Martinez, A., Benavente, R., 1998. The ar face database. CVC TechnicalReport #24. ... Pattern Anal. Mach. Intell. 24 (5), 707–711. Neal, R., 1997. Monte Carlo implementation of Gaussian process modelsfor Bayesian regression and classification.
  7. A Brief Overview of Nonparametric Bayesian Models NIPS 2009 ...

    https://mlg.eng.cam.ac.uk/zoubin/talks/nips09npb.pdf
    27 Jan 2023: 21). Given s, the distribution of Z becomes:. p( Z | x , s, µ ( 1 : ) ) p( Z | x , µ ( 1 : ) ) 1µ I (0 s µ ) (24).
  8. PowerPoint Presentation

    https://mlg.eng.cam.ac.uk/capp-workshop/slides/chris.pdf
    23 Nov 2022: Slide Number 21. Slide Number 22. Slide Number 23. Slide Number 24.
  9. Bayesian Hierarchical Clustering Katherine A. Heller…

    https://mlg.eng.cam.ac.uk/zoubin/papers/icml05heller.pdf
    27 Jan 2023: 1 2 3 4 5 6 8 9 10 7 11 12 13 14 15 16 18 20 19 17 21 22 23 24 25 26 270. ... 0.2231.24. 3.6. 59.9. 0 1 2 3 4 5 6 74.
  10. Encyclopedia of Cognitive Science—Author Stylesheet ©Copyright…

    https://mlg.eng.cam.ac.uk/zoubin/papers/ECS-infotheory02.pdf
    27 Jan 2023: After the neighbour tells you that he lives on the top floor, the probability of X drops to 0 for 24 of the 32 values and becomes 1/8 for the
  11. G:\bioinformatics\ISMB\btq210.dvi

    https://mlg.eng.cam.ac.uk/pub/pdf/SavGhaGrietal10.pdf
    13 Feb 2023: 5634 2 2.6108 22/23 15/84 Nucleus32991 2 7.9105 18/23 24/84 Macromolecular complex. ... BMC Bioinformatics, 8,283. i165. by on July 24, 2010 http://bioinform. atics.oxfordjournals.orgDownloaded from.
  12. Augmented Attribute Representations Viktoriia Sharmanska1, Novi…

    https://mlg.eng.cam.ac.uk/pub/pdf/ShaQuaLam12.pdf
    13 Feb 2023: There are 50 animals classesin this dataset. The dataset also contains semantic information in the form of an85-dimensional Osherson’s [24] attribute vector for each animal class. ... In: CVPR. (2010) 3027–3034. 24. Osherson, D.N., Stern, J., Wilkie,
  13. From Parity to Preference-based Notionsof Fairness in Classification…

    https://mlg.eng.cam.ac.uk/adrian/NeurIPS17-from-parity-to-preference.pdf
    16 Jul 2024: decisionoutcomes. A number of learning mechanisms have been proposed to achieve parity in treatment [24],. ... Angwin. https://github.com/propublica/compas-analysis, 2016. [24] B. T. Luong, S. Ruggieri, and F.
  14. The Indian Buffet Process and Extensions Zoubin Ghahramani University …

    https://mlg.eng.cam.ac.uk/zoubin/talks/turin09.pdf
    27 Jan 2023: 21). Given s, the distribution of Z becomes:. p( Z | x , s, µ ( 1 : ) ) p( Z | x , µ ( 1 : ) ) 1µ I (0 s µ ) (24).
  15. Tree-Structured Stick Breaking for Hierarchical Data Ryan Prescott…

    https://mlg.eng.cam.ac.uk/pub/pdf/AdaGhaJor10.pdf
    13 Feb 2023: To efficiently learn thenode parameters, we used Hamiltonian (hybrid) Monte Carlo (HMC) [24], taking 25 leapfrog HMCsteps, with a randomized step size. ... 24] Radford M. Neal. MCMC using Hamiltonian dynamics. In Handbook of Markov chain Monte
  16. Split and Merge EM Algorithm for Improving Gaussian Mixture Density…

    https://mlg.eng.cam.ac.uk/pub/pdf/UedNakGha00b.pdf
    13 Feb 2023: Table 1. Log-likelihood/sample size. Initial value EM DAEM SMEM. Training. Mean 159.1 148.2 147.9 145.1Std 1.77 0.24 0.04 0.08.
  17. Gender Classification with Bayesian Kernel Methods [IJCNN1261]

    https://mlg.eng.cam.ac.uk/pub/pdf/KimKimGha06b.pdf
    13 Feb 2023: 24, no. 5, pp. 707–711, 2002. [6] A. Jain and J.
  18. newroyftp.dvi

    https://mlg.eng.cam.ac.uk/pub/pdf/HinGha97a.pdf
    13 Feb 2023: A factor analyzer with 24 hidden units discoversglobal features with both excitatory and inhibitory components (gure 9a). ... a) Weights from the top layer hidden unit to the 24 middle-layer hidden units.
  19. A Systematic Bayesian Treatment of the IBM Alignment Models ...

    https://mlg.eng.cam.ac.uk/pub/pdf/GalBlu13.pdf
    13 Feb 2023: HMM Model Model 420. 21. 22. 23. 24. 25. 26. 27.
  20. Beyond Dataset Bias: Multi-task UnalignedShared Knowledge Transfer…

    https://mlg.eng.cam.ac.uk/pub/pdf/TomQuaCapLam12.pdf
    13 Feb 2023: 15 85.38 3.42 80.66 2.12MSRCORID 45.80 4.26 51.79 2.73 52.59 2.93 40.24 3.11. ... In:. NIPS. (2010)24. Leen, G.: Context assisted information extraction. PhD thesis, University of the.
  21. Variational Inference for Nonparametric Multiple Clustering Yue Guan, …

    https://mlg.eng.cam.ac.uk/pub/pdf/GuaDyNiuetal10.pdf
    13 Feb 2023: The first 100 eigenvectors retains a total of 99.24% ofthe overall variance. ... Journalon Machine Learning Research, 3:583–617, 2002. [24] M. Turk and A.
  22. Sequential Decisions

    https://mlg.eng.cam.ac.uk/zoubin/SALD/week13sequential.pdf
    27 Jan 2023: solutions – the latter relating to “improper” priors! 24. Appendix: Background on the Von Neumann - Morgenstern theory of cardinal.
  23. A Nonparametric Bayesian Model for Multiple Clustering…

    https://mlg.eng.cam.ac.uk/pub/pdf/NiuDyGha12.pdf
    13 Feb 2023: 65CRP-CRP 0.87 0.66 0.34 0.87DP-Gauss 0.24 0.27 0.23 0.016. ... on Data Mining,pages 530–539, 2008. [24] A. Strehl and J. Ghosh.
  24. Factored Contextual Policy Search with Bayesian Optimization Robert…

    https://mlg.eng.cam.ac.uk/pub/pdf/PinKarKupetal19.pdf
    13 Feb 2023: For the Gym tasks, weemploy an extension [24] of the DMP framework [12] toefficiently generate goal-directed trajectories. ... 16, no. 5, pp. 1190–1208, 1995. [24] J. Kober, K. Mülling, O.
  25. Prediction at an Uncertain Input for GaussianProcesses and Relevance…

    https://mlg.eng.cam.ac.uk/pub/pdf/QuiGirRas03.pdf
    13 Feb 2023: Ex[σ2(x)] varx(µ(x. )) (24). where Ex indicates the expectation under x.
  26. newroyftp.dvi

    https://mlg.eng.cam.ac.uk/zoubin/papers/RGBN.pdf
    27 Jan 2023: A factor analyzer with 24 hidden units discoversglobal features with both excitatory and inhibitory components (gure 9a). ... a) Weights from the top layer hidden unit to the 24 middle-layer hidden units.
  27. images/test_user_webdesign.eps

    https://mlg.eng.cam.ac.uk/pub/pdf/IwaShaGha13a.pdf
    13 Feb 2023: We estimate the Dirichlet parameter β by using the fixed-point iteration method described in [24]. ... γW. EnX. n′=1. αun exp(γtn)! , (24). where W () is the Lambert W function, which solves theequation x = W (x) exp(W (x)), and.
  28. Reinforcement Learning with Reference Tracking Controlin Continuous…

    https://mlg.eng.cam.ac.uk/pub/pdf/HalRasMac11.pdf
    13 Feb 2023: 3] M. P. Deisenroth. Efficient Reinforcement Learning using GaussianProcesses. PhD thesis, Cambridge University, November 24 2009.
  29. 13 Feb 2023: 14 15 16 17 18 19 20 21 22 23 24 25 26 270. ... 2004) (N = 24,D = 100,3000 MCMC iterations). 5.3. Biological data: E.
  30. 1 Graph Kernels by Spectral Transforms Xiaojin Zhu Jaz ...

    https://mlg.eng.cam.ac.uk/zoubin/papers/ssl-book.pdf
    27 Jan 2023: maxµ vec(T )>M µ (1.24). subject to ||M µ|| 1 (1.25). ... 0.27 (86) 0.24 (92) 0.15 0.18 0.40 (85) 0.02 0.12 0.09.
  31. Bayesian Knowledge Corroboration with LogicalRules and User Feedback…

    https://mlg.eng.cam.ac.uk/pub/pdf/KasVanGraHer10.pdf
    13 Feb 2023: While [23, 24] represent the formalism of first-orderlogic by factor graph models, [27] and [29] deal with Bayesian networks appliedto first-order logic. ... 1094–1099. AAAI Press(2008). 24. Domingos, P., Richardson, M.: Markov Logic Networks.
  32. 1 Robust Filtering and Smoothing with Gaussian Processes Marc ...

    https://mlg.eng.cam.ac.uk/pub/pdf/DeiTurHubetal12.pdf
    13 Feb 2023: Using the definition of S in (24), the productof the two Gaussians in (36) results in a new (unnormalized) Gaussianc14 N(xt1 |ψi, Ψ) with. ... 24] J. Kocijan, R. Murray-Smith, C. E. Rasmussen, and B. Likar, “PredictiveControl with Gaussian Process
  33. Cambridge Machine Learning Group Publications

    https://mlg.eng.cam.ac.uk/pub/authors/
    13 Feb 2023: Publications, Machine Learning Group, Department of Engineering, Cambridge. current group:. [former members:. [by year:. [Tameem Adel. George Nicholson, Marta Blangiardo, Mark Briers, Peter J Diggle, Tor Erlend Fjelde, Hong Ge, Robert J B Goudie,
  34. analogy-aistats2007.dvi

    https://mlg.eng.cam.ac.uk/pub/pdf/SilHelGha07a.pdf
    13 Feb 2023: C1 C2 RB SB1 SB2 C1 C2 RB SB1 SB2. student course f aculty projectcornell 0.87 0.61 0.87 0.84 0.80 0.19 0.04 0.24 ... 0.18 0.18texas 0.55 0.54 0.77 0.62 0.48 0.24 0.07 0.29 0.07 0.12.
  35. Graph-based Semi-supervised Learning Zoubin Ghahramani Department of…

    https://mlg.eng.cam.ac.uk/zoubin/talks/lect3ssl.pdf
    27 Jan 2023: Background Extraction. date 10/24 11/13 1/6 1/14 1/20 1/21 1/271 128 193 153 4742 256 193 4483 288 305 5934 204 190 3945 266
  36. Predictive Automatic Relevance Determinationby Expectation…

    https://mlg.eng.cam.ac.uk/pub/pdf/QiMinPic04a.pdf
    13 Feb 2023: PredictiveARDEPPredictiveProbARDEP. EvidenceARDEPAllFeaturesEPlinear. SVMQP_RegAdaBoostLP_RegAdaBoost. AdaBoost_RegAdaBoost. RBF. 23.5 24.5 25.5 26.5. Test error rate.
  37. Yarin Gal awarded Research Fellowship at St Catherine’s College,…

    https://mlg.eng.cam.ac.uk/news/yarin-gal-awarded-research-fellowship-at-st-catherine-college-cambridge/
    3 Jul 2024: Mar 24, 2016. Well done to Yarin Gal who has been awarded the Michael and Morven Heller Research Fellowship at St Catherine’s College, Cambridge.
  38. Blind Justice: Fairness with Encrypted Sensitive Attributes

    https://mlg.eng.cam.ac.uk/adrian/poster_ICML18_BlindJustice.pdf
    16 Jul 2024: Bank. Datasets and Feasibility. Adult Bank COMPAS German SQFn training examples 214 215 212 29 216d features 51 62 7 24 23p sensitive attributes 1 1 7 1 1certification 802 ms
  39. Clamping Variables and Approximate Inference

    https://mlg.eng.cam.ac.uk/adrian/newsclamp.pdf
    16 Jul 2024: 0.1. 0.2. 0.3. 0.4. max interaction strength W 24 / 19.
  40. Gaussian Process

    https://mlg.eng.cam.ac.uk/teaching/4f13/1718/gaussian%20process.pdf
    19 Nov 2023: 64. 20. 24. 6. 6. 4. 2. 0. 2. 4. 6.
  41. - 4F13: Machine Learning

    https://mlg.eng.cam.ac.uk/teaching/4f13/0910/lect01.pdf
    19 Nov 2023: Ghahramani & Rasmussen (CUED) Lecture 1: Introduction to Machine Learning January 14th, 2010 24 / 26.
  42. ENGINEERING TRIPOS PART IIA EXAMPLES PAPER - PATTERN PROCESSING ...

    https://mlg.eng.cam.ac.uk/teaching/3f3/1011/examplespaper0910.pdf
    19 Nov 2023: 1. 4 2a 8a 24 18a = 0therefore a = 1.
  43. - Machine Learning 4F13, Spring 2014

    https://mlg.eng.cam.ac.uk/teaching/4f13/1314/lect0102.pdf
    19 Nov 2023: 4. 3. 2. 1. 0. 1. 2. 3. Rasmussen and Ghahramani Lecture 1 and 2: Probabilistic Regression 24 / 36.
  44. - Machine Learning 4F13, Spring 2015

    https://mlg.eng.cam.ac.uk/teaching/4f13/1415/lect0102.pdf
    19 Nov 2023: 1. 0. 1. 2. 3. Samples from the posteriorRasmussen and Ghahramani Lecture 1 and 2: Probabilistic Regression 24 / 37.
  45. 13 Feb 2023: Bagging predictors. Ma-chine Learning 24, 123–140. Breiman, L., October 2001. Random forests. ... Vol. 24. pp. 791–798. Takács, G., Pilászy, I., Németh, B., Tikk, D., 2007.
  46. Continuous Relaxations for Discrete Hamiltonian Monte Carlo

    https://mlg.eng.cam.ac.uk/pub/pdf/ZhaSutSto12a.pdf
    13 Feb 2023: 1 Introduction. Discrete undirected graphical models have seen wide use in natural language processing [11, 24] andcomputer vision [19]. ... Weinberger, editors,Advances in Neural Information Processing Systems 24, pages 2744–2752. 2011.
  47. You Shouldn’t Trust Me: Learning Models WhichConceal Unfairness From…

    https://mlg.eng.cam.ac.uk/adrian/ECAI20-You_Shouldn%E2%80%99t_Trust_Me.pdf
    16 Jul 2024: mostimportant feature) in 2D reduced input space (scikit-learn [24]’s PCA imple-mentation). ... 4765–4774, (2017). [24] F. Pedregosa, G. Varoquaux, A. Gramfort, V. Michel, B.
  48. - Machine Learning 4F13, Michaelmas 2015

    https://mlg.eng.cam.ac.uk/teaching/4f13/1516/lect0102.pdf
    19 Nov 2023: 1. 0. 1. 2. 3. Samples from the posteriorGhahramani Lecture 1 and 2: Probabilistic Regression 24 / 38.
  49. A robust Bayesian two-sample test for detecting intervals of ...

    https://mlg.eng.cam.ac.uk/pub/pdf/SteDenWiletal09.pdf
    13 Feb 2023: a total of 24 time points). B.cinerea spores (suspended in half-strength grape juice) germinate, penetrate theleaf and cause expanding necrotic lesions. ... This model is related to mixtures of Gaussian process experts, whichhave been studied previously
  50. Discovering temporal patterns of differential geneexpression in…

    https://mlg.eng.cam.ac.uk/pub/pdf/SteDenMcHetal09.pdf
    13 Feb 2023: cinerea spore suspension (or mock-inoculated) and harvested every 2 hr upto 48 hr post-inoculation for a total of 24 time points.
  51. Learning with Multiple Labels

    https://mlg.eng.cam.ac.uk/pub/pdf/JinGha02a.pdf
    13 Feb 2023: Class Name ecoli wine pendigit iris glass. 1 extra label Naive 17.3% 10% 14.2% 18.5% 24.9% by random.

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