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Orthogonal Estimation of Wasserstein Distances Mark Rowland∗1 Jiri…
https://mlg.eng.cam.ac.uk/adrian/AISTATS19-slicedwasserstein.pdf19 Jun 2024: physics (Jordan et al., 1998) and economics(Galichon, 2016), and are increasingly used in machinelearning (Arjovsky et al., 2017; Gulrajani et al., 2017;Peyré and Cuturi, 2018). ... 5.1 Distance estimation. We begin with a test bed of small-scale -
Methods for Inference in Graphical Models
https://mlg.eng.cam.ac.uk/adrian/phd_FINAL.pdf19 Jun 2024: 91. 7.6.2 Test sets. 93. 7.7 Conclusions. 95. 8 Clamping Variables and Approximate Inference 96. ... cave functions. They have attracted attention in combinatorics (Lovász, 1983), economics (Topkis,. Results that match 1 of 2 words
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https://mlg.eng.cam.ac.uk/index.xml
https://mlg.eng.cam.ac.uk/index.xml10 Apr 2024: Cambridge Machine Learning Group https://mlg.eng.cam.ac.uk/ Cambridge Machine Learning Group Wowchemy (https://wowchemy.com) en-us Wed, 22 Mar 2023 00:00:00 0000 -
TibGM: A Transferable and Information-Based Graphical Model Approach…
https://mlg.eng.cam.ac.uk/adrian/ICML2019-TibGM.pdf19 Jun 2024: Confidence intervals are shown in all the plots. Unlessnoted otherwise, each experiment was repeated 50 timesand significance has been tested via a paired t-test with sig-nificance level at 5%. ... Significance is tested usingthe same paired t-test -
https://mlg.eng.cam.ac.uk/news/index.xml
https://mlg.eng.cam.ac.uk/news/index.xml10 Apr 2024: Latest News | Cambridge Machine Learning Group https://mlg.eng.cam.ac.uk/news/ Latest News Wowchemy (https://wowchemy.com) en-us Wed, 22 Mar 2023 00:00:00 0000 -
Bayesian Deep Learning via Subnetwork Inference · Cambridge MLG Blog
https://mlg.eng.cam.ac.uk/blog/2021/07/21/subnetwork-inference.html12 Apr 2024: Figure 9: Results on the rotated MNIST benchmark, showing the mean $pm$ std of the test error (top) and log-likelihood (bottom) across three different seeds. ... methods. Figure 10: Results on the corrupted CIFAR-10 benchmark, showing the mean $pm$ std -
Understanding the Bethe Approximation: When and How can it go Wrong?
https://mlg.eng.cam.ac.uk/adrian/pabc.pdf19 Jun 2024: Wolfe used for all runs, aftervalidating against smaller test set usingdual decomposition with guaranteed-approx mesh method (Weller andJebara, 2014). -
Characterizing Tightness of LP Relaxations by Forbidding Signed Minors
https://mlg.eng.cam.ac.uk/adrian/pminor.pdf19 Jun 2024: test. REFERENCES. B. Guenin. A characterization of weakly bipartite graphs. Journal of Combinatorial Theory, Series B, 83(1):112–168, 2001. -
Leader Stochastic Gradient Descent (LSGD) for Distributed Training of …
https://mlg.eng.cam.ac.uk/adrian/LSGD_Poster_NeurIPS2019.pdf19 Jun 2024: Test error for the center variable versus wall-clock time. Figure: ResNet20 on CIFAR-10 with 4 workers (on the left) and 16 workers (on the right). ... Test error for the center variable versus wall-clock time. Figure: ResNet20 on CIFAR-10. -
Natural-Gradient Variational Inference 2: ImageNet-scale · Cambridge…
https://mlg.eng.cam.ac.uk/blog/2021/11/24/ngvi-bnns-part-2.html12 Apr 2024: Reducing the prior precision $delta$ results in higher validation accuracy, but also a larger train-test gap, corresponding to more overfitting. ... Continual Learning: I personally think continual learning is a very good way to test approximate Bayesian
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