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UK Climate Change Act and actual Greenhouse Gas emissions
https://mlg.eng.cam.ac.uk/carl/words/cca.html28 Jun 2024: For example, a reduction of 100 MtCO2e would be a very different objective in 2010 when emissions were >600 MtCO2e per year than in 2035 when emissions are (hopefully) <200 MtCO2e -
preferential_fairness_nips_2017.pages
https://mlg.eng.cam.ac.uk/adrian/preferential_fairness_nips_2017.pdf19 Jun 2024: 4. New notions of fairness. M (100). W (100)M (200) W (200). ... Benefit: 0% (M), 67% (W). M (100). W (100)M (200) W (200). -
./cca08.eps
https://mlg.eng.cam.ac.uk/carl/words/cca08.pdf25 Jun 2024: 1990 2000 2010 2020 2030 2040 2050. time, calendar years. 200. -
Exploring Properties of the Deep Image Prior Andreas…
https://mlg.eng.cam.ac.uk/adrian/NeurIPS_2019_DIP7.pdf19 Jun 2024: This is confirmed by the confidenceof the DIP output, which increased to > 0:5 after just 200 iterations. ... 2. (a) 100 iterationsConf.: 0.004. (b) 200 iterationsConf.: 0.52. (c) 300 iterationsConf.: 0.72. -
Who owns the atmosphere?
https://mlg.eng.cam.ac.uk/carl/climate/eacc.html28 Jun 2024: In a world composed of 200 very different nations, simple transparent principles are required. -
ML-IRL: Machine Learning in Real Life Workshop at ICLR ...
https://mlg.eng.cam.ac.uk/adrian/ML_IRL_2020-CLUE.pdf19 Jun 2024: MNIST 2 1200 6 -LSAT 2 200 3 300. COMPAS 2 200 3 300. -
Network Ranking With Bethe Pseudomarginals Kui TangColumbia…
https://mlg.eng.cam.ac.uk/adrian/2013_NeurIPS_DiscML_Network.pdf19 Jun 2024: We drew independent nodescores from a mixture of Gaussians and a scale free network (100 nodes, 200 edges) from the Barabsi-Albertmodel [12]. -
TibGM: A Transferable and Information-Based Graphical Model Approach…
https://mlg.eng.cam.ac.uk/adrian/ICML2019-TibGM.pdf19 Jun 2024: 0 100 200 300 400 500. 103 steps0. 50. 100. 150. ... 200. 250. 300. 350. retu. rn. (a) Swimmer (rllab). 0 250 500 750 1000 1250 1500 1750 2000. -
From Parity to Preference-based Notionsof Fairness in Classification…
https://mlg.eng.cam.ac.uk/adrian/NeurIPS17-from-parity-to-preference.pdf19 Jun 2024: W (100)M (200) W (200). f2. f1Acc: 0.83. Benefit: 0% (M), 67% (W). ... M (100). W (100)M (200) W (200). f2. f1Acc: 0.72. Benefit: 22% (M), 22% (W)Acc: 1.00. -
Understanding the Bethe Approximation: When and How can it ...
https://mlg.eng.cam.ac.uk/adrian/abc.pdf19 Jun 2024: Understanding the Bethe Approximation: When and How can it go Wrong? Adrian WellerColumbia UniversityNew York NY 10027. adrian@cs.columbia.edu. Kui TangColumbia UniversityNew York NY 10027. kt2384@cs.columbia.edu. David SontagNew York UniversityNew
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