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chuesann.dvi
https://mlg.eng.cam.ac.uk/pub/pdf/ChuGhaWil04b.pdf13 Feb 2023: H70.13% 70.77% 72.28% 71.70%. QobsE. 46.51% 24.69% 46.86% 23.96%Qobs. C73.29% 70.52% 72.64% 70.86%. -
nips.dvi
https://mlg.eng.cam.ac.uk/pub/pdf/Ras96.pdf13 Feb 2023: 0.2. 0.3. 0.4. 0.5. 0.6. House. 24 48 96 1920. 0.05. -
paper.dvi
https://mlg.eng.cam.ac.uk/pub/pdf/KimGha08.pdf13 Feb 2023: GPC log-ev -24.40.6 -41.80.8 -51.81.1 -60.21.0error(%) 3.700.36 4.900.77 7.500.88 8.151.42. robust log-ev ... MS-robust- log-ev -24.40.6 -41.00.7 -50.50.7 -58.60.8GPC error(%) 3.700.36 4.540.62 6.760.76 6.850.73. -
Inferring a measure of physiological age frommultiple ageing related…
https://mlg.eng.cam.ac.uk/pub/pdf/KnoParGlaWin11.pdf13 Feb 2023: 2. Figure 1: An intuitive explanation of our model. This 55 year old individual has the cataracts of a79 year old, implying = 24 years. -
The Rendezvous Algorithm: Multiclass Semi-Supervised Learningwith…
https://mlg.eng.cam.ac.uk/pub/pdf/Azr07.pdf13 Feb 2023: Low Density Separation (Chapelle. Appearing in Proceedings of the 24 th International Confer-ence on Machine Learning, Corvallis, OR, 2007. ... 42.72 13.49 4.95 3.79 9.68 21.99 35.17 24.38Data dep. -
https://mlg.eng.cam.ac.uk/teaching/4f13/1112/cw/mauna.txt
https://mlg.eng.cam.ac.uk/teaching/4f13/1112/cw/mauna.txt19 Nov 2023: 875 316.69 1962.958 317.70 1963.042 318.74 1963.125 319.08 1963.208 319.86 1963.292 321.39 1963.375 322.24 1963.458 321.47 ... 24 1964.458 321.89 1964.542 320.44 1964.625 318.70 1964.708 316.70 1964.792 316.79 1964.875 317.79 1964.958 318.71 1965.042 -
Blind Justice: Fairness with Encrypted Sensitive Attributes
https://mlg.eng.cam.ac.uk/adrian/ICML18-BlindJustice.pdf16 May 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. -
book
https://mlg.eng.cam.ac.uk/pub/pdf/PerGhaPon07.pdf13 Feb 2023: 1.23). subject to:. wt φt(xn, ynt) wt φt(xn, yt) Mynt,yt ξnt n, t, yt (1.24). ... We end up having a significant reduction in the number ofconstraints2 in our optimisation formulation for CGMs in (1.23)-(1.24). -
An Introduction to LP Relaxations for MAP Inference
https://mlg.eng.cam.ac.uk/adrian/2018-MLSALT4-AW2-LP.pdf16 May 2024: x3. x4. x5. x6. s. balanced almost balanced(attractive up to flipping) 24 / 41. -
Bayesian Classifier Combination Hyun-Chul Kim Zoubin GhahramaniKorea…
https://mlg.eng.cam.ac.uk/pub/pdf/KimGha12.pdf13 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.
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