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Cambridge Machine Learning Group : People : Hong Ge
https://mlg.eng.cam.ac.uk/hong/13 Dec 2023: Hong Ge. Principal Investigator. Senior Research Fellow. atFellow of Darwin college. Email: hg344 [at] cam [dot] ac [dot] uk. I am a Senior Research Fellow in the Department of Engineering at the University of Cambridge. I lead the Turing language -
https://mlg.eng.cam.ac.uk/people/index.xml
https://mlg.eng.cam.ac.uk/people/index.xml3 Jul 2024: Cambridge Machine Learning Group https://mlg.eng.cam.ac.uk/people/ Cambridge Machine Learning Group Wowchemy (https://wowchemy.com) en-us ... 300x300_fit_lanczos_3.png Cambridge Machine Learning Group https://mlg.eng.cam.ac.uk/people/. -
https://mlg.eng.cam.ac.uk/people/hong-ge/index.xml
https://mlg.eng.cam.ac.uk/people/hong-ge/index.xml3 Jul 2024: Hong Ge | Cambridge Machine Learning Group https://mlg.eng.cam.ac.uk/people/hong-ge/ Hong Ge Wowchemy (https://wowchemy.com) en-us ... ge/avatar_huf0bdcbefe50acb86aa6fdef1240269ab_174405_270x270_fill_lanczos_center_3.png Hong Ge -
https://mlg.eng.cam.ac.uk/people/chao-ma/index.xml
https://mlg.eng.cam.ac.uk/people/chao-ma/index.xml3 Jul 2024: Chao Ma | Cambridge Machine Learning Group https://mlg.eng.cam.ac.uk/people/chao-ma/ Chao Ma Wowchemy (https://wowchemy.com) en-us ... ma/avatar_hu78f90294e5b28717599f1f572dc03768_5286_270x270_fill_q75_lanczos_center.jpg Chao Ma -
Cambridge Machine Learning Group Publications
https://mlg.eng.cam.ac.uk/pub/13 Feb 2023: In 16th Bayesian Modelling Applications Workshop at UAI, 2022, 2022. Abstract: The Upper Indus Basin, Himalayas provides water for 270 million people and countless ecosystems. -
Machine Learning Group Publications
https://mlg.eng.cam.ac.uk/pub/topics/13 Feb 2023: In 16th Bayesian Modelling Applications Workshop at UAI, 2022, 2022. Abstract: The Upper Indus Basin, Himalayas provides water for 270 million people and countless ecosystems. -
The Case for Process Fairness in Learning:Feature Selection for ...
https://mlg.eng.cam.ac.uk/adrian/grgic.pdf19 Jun 2024: on their effects on people belonging to certain sensitivedemographic groups (e.g., gender, race). ... Now we compare user judgments of fairness of individual features, fordifferent demographic subgroups of people. -
- IB Paper 7: Probability and Statistics
https://mlg.eng.cam.ac.uk/teaching/1BP7/1819/lect02.pdf19 Nov 2023: Example: What is the probability that two people both have their birthday inJanuary? ... First, work out the probability qn that with n people, none share birthdays. -
Transparency: Motivations and Challenges? Adrian…
https://mlg.eng.cam.ac.uk/adrian/transparency.pdf19 Jun 2024: Yet both concepts are somewhat ambiguous, and can meandifferent things to different people in different contexts. ... People might be experts or not. We list several types and goals of transparency. -
Human Perceptions of Fairness in Algorithmic Decision Making: A Case…
https://mlg.eng.cam.ac.uk/adrian/WWW18-HumanPerceptions.pdf19 Jun 2024: Our Contributions. We collected and analyzed fairness judgmentsfrom a survey of 576 people. ... So our framework for how people judgefeature usage fairness consists of two-parts.
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