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3F3: Signal and Pattern Processing Lecture 1: Introduction to ...
https://mlg.eng.cam.ac.uk/teaching/3f3/1011/lect1.pdf19 Nov 2023: Computer Science: Artificial Intelligence, computer vision, information retrieval,. • Statistics: learning theory, data mining, learning and inference from data,. • ... Computational Neuroscience: neuronal networks, neural information processing,. -
Unsupervised Learning Week 1: Introduction, Statistical Basics,and a…
https://mlg.eng.cam.ac.uk/zoubin/course05/lect1.pdf27 Jan 2023: Unsupervised Learning. Week 1: Introduction, Statistical Basics,and a bit of Information Theory. ... Cognitive Science: computational linguistics, philosophy of mind,. • Economics: decision theory, game theory, operational research. • -
Transparency: Motivations and Challenges? Adrian…
https://mlg.eng.cam.ac.uk/adrian/transparency.pdf16 Jul 2024: 2 A. Weller. (D) In some settings, more transparency can lead to less efficiency (Section 4 re-views related work in economics, multi-agent game theory and network routing),fairness (Section ... 4 Economics and Multi-Agent Game Theory. In an economy, -
Cambridge Machine Learning Group Publications
https://mlg.eng.cam.ac.uk/pub/authors/13 Feb 2023: We develop new supporting theory for PVI, demonstrating a number of properties that make it an attractive choice for practitioners; use PVI to unify a wealth of fragmented, yet related literature; ... optimization problem using the theory of Reproducing -
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 ... In this work, we introduce, formalize and -
Cambridge Machine Learning Group Publications
https://mlg.eng.cam.ac.uk/pub/13 Feb 2023: This begets competition for the finite user attention pool. We formalize these dynamics in what we call an exposure game, a model of incentives induced by algorithms including modern factorization and ... Bayesian neural networks have a simple weight -
Machine Learning Group Publications
https://mlg.eng.cam.ac.uk/pub/topics/13 Feb 2023: The theory we develop is based on interpreting activation functions as interdomain inducing features through a rigorous analysis of the interplay between activation functions and kernels. ... To provide evidence that our method can be beneficial not only
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