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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. -
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. -
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. -
https://mlg.eng.cam.ac.uk/people/jiri-hron/index.xml
https://mlg.eng.cam.ac.uk/people/jiri-hron/index.xml3 Jul 2024: Jiri Hron | Cambridge Machine Learning Group https://mlg.eng.cam.ac.uk/people/jiri-hron/ Jiri Hron Wowchemy (https://wowchemy.com) en-us ... hron/avatar_hu78f90294e5b28717599f1f572dc03768_5286_270x270_fill_q75_lanczos_center.jpg Jiri Hron -
- 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. -
paper8-lect0-13
https://mlg.eng.cam.ac.uk/zoubin/p8-07/lect0.pdf27 Jan 2023: your preferences to other people’s preferences • online shopping: searching for products by giving a few examples • online dating services / social networks: searching for people based on profiles • finance: finding similar ... Appendix. Movie -
4F13: Machine Learninghttp://learning.eng.cam.ac.uk/zoubin/ml06/…
https://mlg.eng.cam.ac.uk/zoubin/ml06/lecture8.pdf27 Jan 2023: Statistical samplingWhat is the average height h of people p in Cambridge C? ... EpC[h(p)] 1|C|. pC. h(p). 1S. Ss=1. h(p(s). ), for random survey of S people {p(s)} C. -
2018 Formatting Instructions for Authors Using LaTeX
https://mlg.eng.cam.ac.uk/adrian/AIES18-crowd_signals.pdf19 Jun 2024: 2017),and might help to promote greater understanding and cohe-sion among people. ... CNN You mean, like the UNFOUNDED claims of Russiancollusion? You people are typically selective in your bias pro?https://t.co/CESkVpIZOk@nytimes His actions were -
Beyond Distributive Fairness in Algorithmic Decision Making: Feature…
https://mlg.eng.cam.ac.uk/adrian/AAAI18-BeyondDistributiveFairness.pdf19 Jun 2024: However, we note that such judgments can begathered from any other group of people, ranging fromcrowd workers to domain experts. ... people) more likelyto be falsely predicted as having a higher risk of recidivismthan another group of people (e.g., white -
Bounding the Integrality Distance ofLP Relaxations for Structured…
https://mlg.eng.cam.ac.uk/adrian/OPT2016_paper_3.pdf19 Jun 2024: That is, max-margin training with approximateinference—which is something people do anyway to learn graphical models—reduces not only theprediction error, but also the inference approximation error. -
ML-IRL: Machine Learning in Real Life Workshop at ICLR ...
https://mlg.eng.cam.ac.uk/adrian/ML_IRL_2020-CLUE.pdf19 Jun 2024: SampleSize” denotes how many people received this variant. The next two columns contain the proportionof correct answers when identifying epistemic or aleatoric uncertainty for LSAT, respectively. -
Blind Justice: Fairness with Encrypted Sensitive Attributes
https://mlg.eng.cam.ac.uk/adrian/ICML18-BlindJustice.pdf19 Jun 2024: 2.2. Fairness Criteria. In large part, works that formalize fairness in machine learn-ing do so by balancing a certain condition between groupsof people with different sensitive attributes, z versus ... Figure 3. The fraction of people with z = 0 -
10 | UNIVERSITY OF CAMBRIDGE NEWSLETTER | FEBRUARY / ...
https://mlg.eng.cam.ac.uk/zoubin/misc/KarstenMalariaNewsletter.pdf27 Jan 2023: According to the World Health Organisation, more than 1 million people die from its effects every 12 months. ... Near-missesWhy do people gamble if they know that the house always wins? -
Mind Reading by Machine Learning
https://mlg.eng.cam.ac.uk/pub/pdf/HusNopLen10.pdf13 Feb 2023: Finally, we also implemented as an alternative methoda previously published algorithm (‘MCMC with people’)to infer subjective distributions (Sanborn & Griffiths,2008). ... Notably, it outperformedthe ‘MCMC with people’ method even in the case -
Network Ranking With Bethe Pseudomarginals Kui TangColumbia…
https://mlg.eng.cam.ac.uk/adrian/2013_NeurIPS_DiscML_Network.pdf19 Jun 2024: 1 Introduction. Many important data-sets involve networks: people belong to social networks, webpages are joined in a linkgraph, and power utilities are connected in a grid. -
Adversarial Graph Embeddings for Fair Influence Maximization over…
https://mlg.eng.cam.ac.uk/adrian/IJCAI20_AdversarialGraphEmbeddings.pdf19 Jun 2024: in terms of thetotal number of people influenced, and the fraction of peopleinfluenced from both A and B communities. ... maximizing the to-tal number of influenced people, while also significantly de-creasing disparity.
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