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  2. The Geometry of Random Features Krzysztof Choromanski∗1 Mark…

    https://mlg.eng.cam.ac.uk/adrian/geometry.pdf
    19 Jun 2024: The Geometry of Random Features. Krzysztof Choromanski1 Mark Rowland2 Tamas Sarlos1 Vikas Sindhwani1 Richard E. Turner2 Adrian Weller231Google Brain, NY 2University of Cambridge, UK 3The Alan Turing Institute, UK. Abstract. We present an in-depth
  3. ML-IRL: Machine Learning in Real Life Workshop at ICLR ...

    https://mlg.eng.cam.ac.uk/adrian/ML_IRL_2020-CLUE.pdf
    19 Jun 2024: 6). LSATAl. (7). COMPASEp. (6). COMPASAl. (5) Total (24). Prolific Unc.
  4. Scalable Gaussian Process Structured Prediction for Grid Factor Graph …

    https://mlg.eng.cam.ac.uk/pub/pdf/BraQuaNowGha14.pdf
    13 Feb 2023: 24.6. 24.7. 24.8. 24.9. 25.0err. or. rate. GPstruct. CRF LBMO bag. ... 2013. http://arxiv.org/abs/1307.3846. Breiman, Leo. Bagging predictors. Machine Learning, 24(2):123–140, 1996. Domke, Justin.
  5. Gaussian Process

    https://mlg.eng.cam.ac.uk/teaching/4f13/2122/gaussian%20process.pdf
    19 Nov 2023: 64. 20. 24. 6. 6. 4. 2. 0. 2. 4. 6.
  6. Gaussian Process

    https://mlg.eng.cam.ac.uk/teaching/4f13/1819/gaussian%20process.pdf
    19 Nov 2023: 64. 20. 24. 6. 6. 4. 2. 0. 2. 4. 6.
  7. Blind Justice: Fairness with Encrypted Sensitive Attributes

    https://mlg.eng.cam.ac.uk/adrian/ICML18-BlindJustice.pdf
    19 Jun 2024: d features 51 62 7 24 23p sensitive attr. 1 1 7 1 1certification 802 ms 827 ms 288 ms 250 ms 765 mstraining 43 min 51 min 7 min 1 ... Bennett Capers, I. Blind justice. Yale Journal of Law &Humanities, 24:179, 2012.
  8. G:\bioinformatics\Bioinfo-26(7)issue\btq053.dvi

    https://mlg.eng.cam.ac.uk/pub/pdf/LipGhaBor10.pdf
    13 Feb 2023: 915. at Cam. bridge University Library on July 24, 2010. http://bioinformatics.oxfordjournals.org. ... 916. at Cam. bridge University Library on July 24, 2010. http://bioinformatics.oxfordjournals.org.
  9. linsys-new.dvi

    https://mlg.eng.cam.ac.uk/zoubin/papers/tr-96-2.pdf
    27 Jan 2023: Initial state covariance:@Q@V 11 = 12V1 12(P1 x̂101 1x̂01 101) (23)V new1 = P1 x̂1x̂01 (24)The above equations can be readily generalized to multiple observation sequences, withone subtlety
  10. - Machine Learning 4F13, Michaelmas 2015

    https://mlg.eng.cam.ac.uk/teaching/4f13/1516/lect0304.pdf
    19 Nov 2023: 1 0 1 22. 1. 0. 1. 2M=0. 1 0 1 24. ... 1. 2M=0. 1 0 1 24. 2. 0. 2. 4. M=1.
  11. 3F3: Signal and Pattern Processing Lecture 1: Introduction to ...

    https://mlg.eng.cam.ac.uk/teaching/3f3/1011/lect1.pdf
    19 Nov 2023: Dataset Data dim. Sample size MLE Regression Corr. dim.Swiss roll 3 1000 2.1(0.02) 1.8(0.03) 2.0(0.24)Faces 64 64 698 4.3

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