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Geometrically Coupled Monte Carlo Sampling Mark Rowland∗University of …
https://mlg.eng.cam.ac.uk/adrian/NeurIPS18-gcmc.pdf19 Jun 2024: 5.2 Variance-reduced ELBO estimation for deep generative models. In this section, we test GCMC sampling strategies on a deep generative modelling application. ... 10. Arthur Gretton, Karsten M. Borgwardt, Malte J. Rasch, Bernhard Schölkopf, and -
Unifying Orthogonal Monte Carlo Methods
https://mlg.eng.cam.ac.uk/adrian/ICML2019-unified.pdf19 Jun 2024: 3, 4. Approximating kernel matrices: We test the relative er-ror of kernel matrix estimation for the above estimators forthe Gaussian kernel (following the setting of Choromanski& Sindhwani, 2016). ... A kernel two-sample test. J. Mach. Learn.Res., -
Tightness of LP Relaxations for Almost Balanced Models Adrian ...
https://mlg.eng.cam.ac.uk/adrian/tricam.pdf19 Jun 2024: Tightness of LP Relaxations for Almost Balanced Models. Adrian Weller Mark Rowland David SontagUniversity of Cambridge University of Cambridge New York University. Abstract. Linear programming (LP) relaxations are widelyused to attempt to identify a -
THIS VERSION FIXES A TYPO IN THE STATEMENT OF ...
https://mlg.eng.cam.ac.uk/adrian/Weller15_revisit_fixed.pdf19 Jun 2024: We shall first prove sufficiency then necessity of the condi-tion. In order to test whether a derived NMRF is perfect, weuse Theorem 1, hence must check for possible odd holes -
Structured Evolution with Compact Architectures for Scalable Policy…
https://mlg.eng.cam.ac.uk/adrian/structured_icml_full.pdf19 Jun 2024: Monte Carlo gradient estimators. We test all three vari-ants of the Monte Carlo gradient estimator discussed in thepaper, namely: antithetic ES, forward finite-difference ESand vanilla ES. -
Ode to an ODE Krzysztof Choromanski ∗Robotics at Google ...
https://mlg.eng.cam.ac.uk/adrian/NeurIPS20-ODEtoODE.pdf19 Jun 2024: Table 1: Test accuracy comparison of different methods. Postfix terms refer to hidden depth for Dense,trigonometric polynomial degree for NANODE, and number of gates for HyperNet and ODEtoODE. -
Conditions Beyond Treewidth for Tightness of Higher-order LP…
https://mlg.eng.cam.ac.uk/adrian/conditions.pdf19 Jun 2024: To detect if a graphis almost balanced, and if so then to find a distinguishedvertex, may be performed efficiently (simply hold out onevariable at a time and test the remainder to -
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. -
Structured Prediction Models for Chord Transcription of Music Audio…
https://mlg.eng.cam.ac.uk/adrian/icmla09adrian.pdf19 Jun 2024: Table 2 shows p-values for paired t-tests examining outperformance of each model compared to the baseline HMMv approach. ... Figure 2 shows the TOM test accuracies for all the models trained using Hamming distance as before. -
ML-IRL: Machine Learning in Real Life Workshop at ICLR ...
https://mlg.eng.cam.ac.uk/adrian/ML_IRL_2020-CLUE.pdf19 Jun 2024: We evaluate the test set of fours, sevens, and nines with our BNN. ... This group was able to reach an accuracyof 88% on unseen test points. -
Exploring Properties of the Deep Image Prior Andreas…
https://mlg.eng.cam.ac.uk/adrian/NeurIPS_2019_DIP7.pdf19 Jun 2024: To test the nature of these outputs we introduce a novel saliencymap approach, termed MIG-SG. ... To test this, we evaluated the sensitivity of DIP to changes innetwork architecture.
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