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Human Perceptions of Fairness in Algorithmic Decision Making: A Case…
https://mlg.eng.cam.ac.uk/adrian/WWW18-HumanPerceptions.pdf19 Jun 2024: ACM, New York, NY, USA,10 pages. https://doi.org/10.1145/3178876.3186138. 1 INTRODUCTIONAlgorithms trained over data about past decisions are increasinglyused to assist or replace human decision making ... We conducted cognitive interviews with -
Tightness of LP Relaxations for Almost Balanced Models Adrian ...
https://mlg.eng.cam.ac.uk/adrian/tricam.pdf19 Jun 2024: 3.2 New Results for LOC, Fixing One Variable andOptimizing Over the Others. ... qij qi. Flipping Xi and applying the above constraint to the new model yields. -
A Unified Approach to Quantifying Algorithmic Unfairness: Measuring…
https://mlg.eng.cam.ac.uk/adrian/KDD2018_inequality_indices.pdf19 Jun 2024: The goal of a learning algorithm is to use the training datato fit a model (or hypothesis) that accurately predicts the labelfor a new instance. ... A model θ : X Y receives the featurevector corresponding to a new individual and makes a predictionabout -
Bethe and Related Pairwise Entropy Approximations Adrian…
https://mlg.eng.cam.ac.uk/adrian/Weller_UAI15_BetheAndRelated.pdf19 Jun 2024: If all variables are flipped (i.e.R = V), new parameters are given by. ... ISSN 1931-9193. doi: 10.1002/nav.3800030109. A. Goldberg and R. Tarjan. A new approach to the maximum flowproblem. -
Working Draft 1 Accountability of AI Under the Law: ...
https://mlg.eng.cam.ac.uk/adrian/SSRN-id3064761-Dec19.pdf19 Jun 2024: 26 David Leake. Evaluating Explanations: A Content Theory. New York: Psychology Press, 1992. ... statement in deciding whether to grant a new trial.48. -
The Geometry of Random Features Krzysztof Choromanski∗1 Mark…
https://mlg.eng.cam.ac.uk/adrian/geometry.pdf19 Jun 2024: 2017). Inthe first subsection we give an overview and in the next one,present our new results. ... Cheng. New bounds for circulant Johnson-Lindenstrauss embeddings. CoRR, abs/1308.6339, 2013. Y. -
Geometrically Coupled Monte Carlo Sampling Mark Rowland∗University of …
https://mlg.eng.cam.ac.uk/adrian/NeurIPS18-gcmc.pdf19 Jun 2024: We compare our new strategies against prior methods for improvingsample efficiency, including quasi-Monte Carlo, by studying discrepancy. ... A new Monte Carlo technique: antithetic variates. Mathemat-ical Proceedings of the Cambridge Philosophical -
Uprooting and Rerooting Higher-Order GraphicalModels Mark…
https://mlg.eng.cam.ac.uk/adrian/uprooting-higher-order.pdf19 Jun 2024: Master’s thesis, MIT,EECS, 2007. [13] D. Sontag and T. Jaakkola. New outer bounds on the marginal polytope. ... 16] M. Wainwright, T. Jaakkola, and A. Willsky. A new class of upper bounds on the log partition function.IEEE Transactions on Information -
From Parity to Preference-based Notionsof Fairness in Classification…
https://mlg.eng.cam.ac.uk/adrian/NeurIPS17-from-parity-to-preference.pdf19 Jun 2024: learning repository [2], and the New York Police Department (NYPD) Stop-question-and-frisk (SQF) dataset made publicly available by NYPD [1]. ... Rao. Precinct or Prejudice? Understanding Racial Disparities in New YorkCity’s Stop-and-Frisk Policy. -
Leader Stochastic Gradient Descent for DistributedTraining of Deep…
https://mlg.eng.cam.ac.uk/adrian/NeurIPS2019_LSGD_preprint.pdf19 Jun 2024: We propose a new algorithm, whose parameter updatesrely on two forces: a regular gradient step, and a corrective direction dictatedby the currently best-performing worker (leader). ... days). 5 Conclusion. In this paper we propose a new algorithm called -
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.pdf19 Jun 2024: 1. Model similarity: the new model has similar performance. i, fθδ(x(i)) fθ(x(i)). ... We apply the Lp norm.5 We define a new objective that. -
Methods for Inference in Graphical Models
https://mlg.eng.cam.ac.uk/adrian/phd_FINAL.pdf19 Jun 2024: from being completely understood. We derive new formulations and properties of the derivatives. ... 2012), including. a new characterization of the Hessian matrix of second partial derivatives. -
The Unreasonable Effectiveness of StructuredRandom Orthogonal…
https://mlg.eng.cam.ac.uk/adrian/NeurIPS17-unreasonable-effectiveness.pdf19 Jun 2024: The new space might have more or fewer dimensions depending on the goal. ... Training linear svms in linear time. In Proceedings of the 12th ACM SIGKDD InternationalConference on Knowledge Discovery and Data Mining, KDD ’06, pages 217–226, New York,
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