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Discovering Interpretable Representations for Both Deep Generative…
https://mlg.eng.cam.ac.uk/adrian/ICML18-Discovering.pdf16 May 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. -
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 -
From Parity to Preference-based Notionsof Fairness in Classification…
https://mlg.eng.cam.ac.uk/adrian/NeurIPS17-from-parity-to-preference.pdf16 May 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 May 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. -
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 -
Transparency: Motivations and Challenges? Adrian…
https://mlg.eng.cam.ac.uk/adrian/transparency.pdf16 May 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). -
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 -
A Generative Model of Vector Space Semantics
https://mlg.eng.cam.ac.uk/pub/pdf/AndGha13a.pdf13 Feb 2023: It is also able to cor-rectly map the vector associated with “economic. ... Test vector economic development(“economic development”) economic development. economic development. Random vector vital turningfurther obligationsbad negotiations. -
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. -
A Unified Approach to Quantifying Algorithmic Unfairness: Measuring…
https://mlg.eng.cam.ac.uk/adrian/KDD2018_inequality_indices.pdf16 May 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
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