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Cambridge Machine Learning Group Publications
https://mlg.eng.cam.ac.uk/pub/authors/13 Feb 2023: Finally, the fourth conversion yields an algorithm for synthesising program source code from input-output examples that is able to solve test problems 1-3 orders of magnitude faster than a ... Versa substitutes optimization at test time with forward -
Cambridge Machine Learning Group Publications
https://mlg.eng.cam.ac.uk/pub/13 Feb 2023: In this work, we test how well-automated methods can detect conversational behaviors and replace an expert human annotator. ... Abstract: Domain generalization (DG) seeks predictors which perform well on unseen test distributions by leveraging data drawn -
Machine Learning Group Publications
https://mlg.eng.cam.ac.uk/pub/topics/13 Feb 2023: Publications, Machine Learning Group, Department of Engineering, Cambridge. current group:. [former members:. [by year:. [Gaussian Processes and Kernel Methods. Gaussian processes are non-parametric distributions useful for doing Bayesian inference -
Healing the Relevance Vector Machine through Augmentation Carl Edward …
https://mlg.eng.cam.ac.uk/pub/pdf/RasQui05.pdf13 Feb 2023: may have contained data close to the test in-put, which hadn’t been designated as relevance vectors. ... For the robot arm we use dis-joint test and training sets both of 2000 cases. -
Gaussian Processes for time-marked time-series data John P.…
https://mlg.eng.cam.ac.uk/pub/pdf/CunGhaRas12.pdf13 Feb 2023: 3.2 Evaluation methods and metrics. To test performance in all data sets, we used leave-one-out cross validation (LOOCV). ... LOOCV test error (RMSE). Time from start Clipping Time-marked GP. GP Averaging GP Averaging Acausal Causal. -
Orthogonal Estimation of Wasserstein Distances Mark Rowland∗1 Jiri…
https://mlg.eng.cam.ac.uk/adrian/AISTATS19-slicedwasserstein.pdf16 Jul 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.pdf16 Jul 2024: 91. 7.6.2 Test sets. 93. 7.7 Conclusions. 95. 8 Clamping Variables and Approximate Inference 96. ... 7.2 Log partition function and approximations for ABC triangle. 86. 7.3 Bethe free energy ESB with stationary points highlighted (top), then entropy SB -
thesis.dvi
https://mlg.eng.cam.ac.uk/pub/pdf/Ras96b.pdf13 Feb 2023: test cases can be stored with the same disk requirements. Attempts can be made to further increase the effectiveness (in terms of data) of the tests. ... according to training sets and test cases. Generally paired tests are more powerful than. -
Gaussian Processes forState Space Models andChange Point Detection…
https://mlg.eng.cam.ac.uk/pub/pdf/Tur11.pdf13 Feb 2023: correct character in a test set when novel images are provided to the algorithm. ... However, power willbe the function of a true latent parameter. Only in simple situations will there be a test that isuniformly most powerful: more powerful than other -
Bayesian Learning forData-Efficient Control Rowan McAllister…
https://mlg.eng.cam.ac.uk/pub/pdf/Mca16.pdf13 Feb 2023: We test our method on the cartpole swing-up task, which involvesnonlinear dynamics and requires nonlinear control. ... Learning control of dynamical systems is a broad subject. Applications rangeform industrial (refining, manufacturing, power), Results that match 2 of 3 words
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Discovering Interpretable Representations for Both Deep Generative…
https://mlg.eng.cam.ac.uk/adrian/ICML18-Discovering.pdf16 Jul 2024: Significant re-sults are identified using a paired t-test with p = 0.05. ... The SVHN dataset contains 73,257training digits (instances) and 26,032 test digits. -
TibGM: A Transferable and Information-Based Graphical Model Approach…
https://mlg.eng.cam.ac.uk/adrian/ICML2019-TibGM.pdf16 Jul 2024: Thick linesin the middle of each curve indicate the average performance,while the standard deviations over 50 random seeds are shownby the shaded regions. ... Significance is tested usingthe same paired t-test described above. TibGM ProMP -
From Parity to Preference-based Notionsof Fairness in Classification…
https://mlg.eng.cam.ac.uk/adrian/NeurIPS17-from-parity-to-preference.pdf16 Jul 2024: In this paper, we draw inspiration from the fair-division and envy-freeness literature in economics and game theory and proposepreference-based notions of fairness—given the choice between various sets ... Finally,we train the five classifiers -
Adrian Weller
https://mlg.eng.cam.ac.uk/adrian/16 Jul 2024: Adrian serves on the boards of several organizations. He is a member of the World Economic Forum Global Future Council on the Future of AI, and is co-director of the ... Train and Test Tightness of LP Relaxations in Structured Prediction. -
What should we, Humanity, do about Climate Change?
https://mlg.eng.cam.ac.uk/carl/climate/do.html14 Jul 2024: Note, that both the low emitters and the large emitters will feel an economic pressure to emit less. ... Next year's price is the median (the middle value) of all the price votes. -
Who owns the atmosphere?
https://mlg.eng.cam.ac.uk/carl/climate/eacc.html14 Jul 2024: Such a scheme would immediately put economic pressure on all users to reduce their utilisation of the common atmospheric resource. ... In the following years, low per capita emitters will gain immediate economic benefit from joining. -
https://mlg.eng.cam.ac.uk/zoubin/misc/karna.txt
https://mlg.eng.cam.ac.uk/zoubin/misc/karna.txt27 Jan 2023: This could take time and test our patience. Q. Once the enemy is defined, is violence the proper response? ... It may require education. It will require time and may test our patience. -
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 -
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: Top middle plot: VOGN is about twice as slow (total time) compared to SGD and Adam. ... Reducing the prior precision $delta$ results in higher validation accuracy, but also a larger train-test gap, corresponding to more overfitting. -
Transparency: Motivations and Challenges? Adrian…
https://mlg.eng.cam.ac.uk/adrian/transparency.pdf16 Jul 2024: truth.”. Defining criteria and tests for practical faithfulness are important open pro-blems. ... 53. Prat, A.: The wrong kind of transparency. American Economic Review 95(3),862–877 (2005). -
Exploring Properties of the Deep Image Prior Andreas…
https://mlg.eng.cam.ac.uk/adrian/NeurIPS_2019_DIP7.pdf16 Jul 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. -
https://mlg.eng.cam.ac.uk/blog/feed.xml
https://mlg.eng.cam.ac.uk/blog/feed.xml12 Apr 2024: middle-ground between expressivity and efficient determinant estimation. -
Understanding the Bethe Approximation: When and How can it ...
https://mlg.eng.cam.ac.uk/adrian/abc.pdf16 Jul 2024: Ex-periments are described in 6, where we examine test cases.Conclusions are discussed in 7. ... Given this performance, we used FW for all Bethe opti-mizations on the test cases. -
erice.dvi
https://mlg.eng.cam.ac.uk/zoubin/papers/erice.pdf27 Jan 2023: d) Weights from the toplayer binary logistic unit to the 24 middle layer binary logistic units. ... a) Weights from the top layer linear-Gaussian unit tothe 24 middle layer linear-Gaussian units. -
arXiv:0906.4032v1 [cs.LG] 22 Jun 2009
https://mlg.eng.cam.ac.uk/pub/pdf/BorGha09a.pdf13 Feb 2023: An associated test is called a two-sample test. Such tests are encountered invarious disciplines from the life sciences to the social sciences:. • ... 3. 3 Concept of Bayesian two-sample tests. 3.1 Bayes factor as test criterion. -
The Geometry of Random Features Krzysztof Choromanski∗1 Mark…
https://mlg.eng.cam.ac.uk/adrian/geometry.pdf16 Jul 2024: On the left: Gaussian kernel, inthe middle: kernel defined by the PD function φ(‖z‖) =(1 ‖z‖2. ... pre-dictive distribution obtained by an exactly-trained GP, and(ii) predictive RMSE on test sets. -
The Case for Process Fairness in Learning:Feature Selection for ...
https://mlg.eng.cam.ac.uk/adrian/grgic.pdf16 Jul 2024: 3. Prior literature in social, economic, legal, and political sciences distinguishing between directdiscrimination and indirect discrimination makes similar observations as we do in this paper. ... For each of the classifiers, we also compute -
A Unified Approach to Quantifying Algorithmic Unfairness: Measuring…
https://mlg.eng.cam.ac.uk/adrian/KDD2018_inequality_indices.pdf16 Jul 2024: In this paper, we propose to quantify unfairness using inequal-ity indices that have been extensively studied in economics andsocial welfare [3, 10, 19]. ... For all experiments, we repeatedly split the data into 70%-30%train-test sets 10 times and -
Human Perceptions of Fairness in Algorithmic Decision Making: A Case…
https://mlg.eng.cam.ac.uk/adrian/WWW18-HumanPerceptions.pdf16 Jul 2024: We draw these latentproperties from the existing literature in social-economic-political-moral sciences, philosophy, and the law, as detailed below.I. ... To evaluate the model, we randomly split thedata into 50%/50% train/test folds five times, and -
PILCO: A Model-Based and Data-Efficient Approach to Policy Search
https://mlg.eng.cam.ac.uk/pub/pdf/DeiRas11.pdf13 Feb 2023: 3)–(5). Doing this properlyrequires mapping uncertain test inputs through theGP dynamics model. ... b) Histogram (after 1,000 test runs)of the distances of the flywheel frombeing upright. -
The Infinite Hidden Markov Model Matthew J. Beal Zoubin ...
https://mlg.eng.cam.ac.uk/zoubin/papers/ihmm.pdf27 Jan 2023: We propose estimating the likelihood of a test sequence given a learned model using particlefiltering. ... 6Different particle initialisations apply if we do not assume that the test sequence immediatelyfollows the training sequence. -
Bayesian HC research talk
https://mlg.eng.cam.ac.uk/zoubin/p8-07/lect4s.ppt27 Jan 2023: Unlabelled Test Images: 22,000 images. For each training and test image we can store a vector of 240 binary color and texture features. ... about 0.2 sec on this laptop to query 22,000 test images. -
You Shouldn’t Trust Me: Learning Models WhichConceal Unfairness From…
https://mlg.eng.cam.ac.uk/adrian/ECAI20-You_Shouldn%E2%80%99t_Trust_Me.pdf16 Jul 2024: Each histogramrepresents the ranking across the test set assigned by the designated feature importance method. ... These results suggest that ourattack is successful in generalising across unseen test points. -
Gaussian Process Training with Input Noise Andrew McHutchonDepartment …
https://mlg.eng.cam.ac.uk/pub/pdf/MchRas11.pdf13 Feb 2023: However,it gives proper consideration to the uncertainty surrounding the test point and exactly computes themoments of the correct posterior distribution. ... 0.5log(x2(sin(2x)2)1). Figure 3: Comparison of models for suite of 6 test functions. -
FAST ONLINE ANOMALY DETECTION USING SCAN STATISTICS Ryan Turner ...
https://mlg.eng.cam.ac.uk/pub/pdf/TurBotGha10.pdf13 Feb 2023: The compu-tational burden is small since the routine only needs to berun when configuring the test. ... We compareit to the CUSUM method, linear trend methods, and uni-formity tests. -
Bayesian Active Learning for Classification and Preference Learning…
https://mlg.eng.cam.ac.uk/pub/pdf/HouHusGha11a.pdf13 Feb 2023: open,hard problem as it would require expensive integration over possible test datadistributions. ... Acc. ura. cy. (l) pref: cpu. Figure 4: Test set classification accuracy on classification and preference learningdatasets. -
ency02.dvi
https://mlg.eng.cam.ac.uk/zoubin/course04/hbtnn2e-III.pdf27 Jan 2023: statistical tests are performed on the data to determine independence and dependence re-. ... be considered for a xed amount computation, because the results of some statistical tests. -
ency02.dvi
https://mlg.eng.cam.ac.uk/zoubin/course03/hbtnn2e-III.pdf27 Jan 2023: statistical tests are performed on the data to determine independence and dependence re-. ... be considered for a xed amount computation, because the results of some statistical tests. -
Inferring a measure of physiological age frommultiple ageing related…
https://mlg.eng.cam.ac.uk/pub/pdf/KnoParGlaWin11.pdf13 Feb 2023: Table 2: Hold out test. Values are log10(p) where p is the p-value for the Spearman rank correlationhypothesis test. ... The results are shown in Figure 2.2, where we are also able to include binary variables unlikefor the Spearman test. -
Archipelago: Nonparametric Bayesian Semi-Supervised Learning Ryan…
https://mlg.eng.cam.ac.uk/pub/pdf/AdaGha09.pdf13 Feb 2023: The top row has three classes, the middle row hasfour classes and the bottom has five. ... In almost all of our tests, Archipelagohad lower test classification error than the NCNM. -
The Infinite Hidden Markov Model Matthew J. Beal Zoubin ...
https://mlg.eng.cam.ac.uk/pub/pdf/BeaGhaRas02.pdf13 Feb 2023: We propose estimating the likelihood of a test sequence given a learned model using particlefiltering. ... 6Different particle initialisations apply if we do not assume that the test sequence immediatelyfollows the training sequence. -
Statistical Models for Partial Membership Katherine A. Heller…
https://mlg.eng.cam.ac.uk/pub/pdf/HelWilGha08.pdf13 Feb 2023: for πn in the middle of the range, versus at the ex-tremes. ... tower” cluster, and the middle row arethe images which have the most even membership in bothclusters. -
PROPAGATION OF UNCERTAINTY IN BAYESIAN KERNEL MODELS— APPLICATION TO…
https://mlg.eng.cam.ac.uk/pub/pdf/QuiGirLarRas03.pdf13 Feb 2023: Thiscorresponds to using the model in recall/test phase under uncer-tain input. ... which we draw 100 samples (dots under it).In the middle of the figure, the solid line represents the true under-lying function. -
Scalingin a Hierar chical Unsupervised Network 1 Zoubin Ghahramani,2…
https://mlg.eng.cam.ac.uk/pub/pdf/GhaKorHin99a.pdf13 Feb 2023: b Sampleoutputsgeneratedbythemodelafter learning. a b c. Figure4: Generative weightsof a three-layeredRGBN after beingtrainedon thestereodisparityproblem.a Weightsfrom thetop layerhidden unit to the 24 middle-layerhidden units. ... Eachof the 24 -
Scalingin a Hierar chical Unsupervised Network 1 Zoubin Ghahramani,2…
https://mlg.eng.cam.ac.uk/zoubin/papers/scaling.pdf27 Jan 2023: b Sampleoutputsgeneratedbythemodelafter learning. a b c. Figure4: Generative weightsof a three-layeredRGBN after beingtrainedon thestereodisparityproblem.a Weightsfrom thetop layerhidden unit to the 24 middle-layerhidden units. ... Eachof the 24 -
LNAI 7524 - Modelling Input Varying Correlations between Multiple…
https://mlg.eng.cam.ac.uk/pub/pdf/WilGha12a.pdf13 Feb 2023: modeling through spatially varying coregionalization. Test 13(2), 263–312 (2004)Gouriéroux, C.: ARCH models and financial applications. ... The Re-. view of Economic Studies 61(2), 247–264 (1994)Murray, I., Adams, R.P., MacKay, D.J.: Elliptical -
Statistical Models for Partial Membership Katherine A. Heller…
https://mlg.eng.cam.ac.uk/zoubin/papers/HelWilGha08.pdf27 Jan 2023: for πn in the middle of the range, versus at the ex-tremes. ... tower” cluster, and the middle row arethe images which have the most even membership in bothclusters. -
Variational Inference for BayesianMixtures of Factor Analysers Zoubin …
https://mlg.eng.cam.ac.uk/zoubin/papers/nips99.pdf27 Jan 2023: Thick lines are accepted attempts, thin lines arerejected attempts. (middle) Exp 3: Means of the factor loading matrices. ... The variational Bayesian approachcorrectly inferred both the number of Gaussians and their intrinsic dimensionalities(Figure 3, -
Gaussian Process Change Point Models
https://mlg.eng.cam.ac.uk/pub/pdf/SaaTurRas10.pdf13 Feb 2023: Weevaluated the models’ ability to predict next day snow-fall using 35 years of test data. ... Method Negative Log Likelihood p-value MSE p-valueNile Data (200 Training Points, 462 Test Points). -
Learning to Parse Images
https://mlg.eng.cam.ac.uk/pub/pdf/HinGhaTeh99a.pdf13 Feb 2023: Then the learning. 2,3. 2,4. 2,5. 3,4. 3,5. 4,5. Figure 1: Sample images from the test set. ... The 64 middle layer units are meantto encode low level features, while each of the 4 top level units are meant to encodea digit class.
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