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Prikvačeni tweet
Thanks to everyone who attended our
#ICML2018 tutorial on Machine Learning for Personalised Health given by@konstantina_pll, Lamiae Azizi and myself. A copy of our slides can be found on the tutorial website here: https://mlhealthtutorial.files.wordpress.com/2018/07/tutorial-ml-for-health.pdf …Prikaži ovu nitHvala. Twitter će to iskoristiti za poboljšanje vaše vremenske crte. PoništiPoništi -
Danielle Belgrave proslijedio/la je Tweet
We are planning to hold
#WiML events, big and small, for#ICLR2020 in Ethiopia,#ICML2020 in Austria,#CoRL2020 in Boston,#NeurIPS2020 in Vancouver, and more! Apply to be an organizer if you'd like to be more involved.https://twitter.com/WiMLworkshop/status/1222691891692625923 …Hvala. Twitter će to iskoristiti za poboljšanje vaše vremenske crte. PoništiPoništi -
Danielle Belgrave proslijedio/la je Tweet
Are you excited for an opportunity to organize
#WiML related events in 2020? It is a great opportunity to get involved and support the community of women in machine learning! We are opening applications on January 31st, please look out for the announcement on our social media.Hvala. Twitter će to iskoristiti za poboljšanje vaše vremenske crte. PoništiPoništi -
Danielle Belgrave proslijedio/la je Tweet
Watch my awesome mentor
@jennwvaughan talk about why it’s important to include people in the ML lifecycle. Her views on human-centered approaches and evaluation of interpretability are exactly how this field should move forward!https://twitter.com/MSFTResearch/status/1220463686914994178 …Hvala. Twitter će to iskoristiti za poboljšanje vaše vremenske crte. PoništiPoništi -
Danielle Belgrave proslijedio/la je Tweet
Want to sponsor AISTATS 2020? Check our sponsorhsip details. This year, funding will go towards supporting diversity and inclusion efforts and the families attending! https://www.aistats.org/sponsors.html
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Danielle Belgrave proslijedio/la je Tweet
Save the date for our 4th annual
@idsai_uom Advances in Data Science conference on June 22nd and 23rd, co-organised with@DaniCMBelg@maalvarezl and@SAnaniadou. Great speaker line-up to follow soon, keep an eye on the website https://www.ds-advances.org/ for more newsHvala. Twitter će to iskoristiti za poboljšanje vaše vremenske crte. PoništiPoništi -
Danielle Belgrave proslijedio/la je Tweet
We are keen to provide participants with children with personalized solutions to be able to comfortably attend AISTATS. Please fill out https://ferenchuszar1.typeform.com/to/qDR0Fi We
family-friendly ML conferences! 

@NeurIPSConf@icmlconf@iclr_confHvala. Twitter će to iskoristiti za poboljšanje vaše vremenske crte. PoništiPoništi -
Danielle Belgrave proslijedio/la je Tweet
This is your 10 day reminder! Send your work at the interface of machine learning and healthcare to CHIL 2020 by January 13th. We have four tracks spanning machine learning, health policy, and practice. For more details, check out: http://chilconference.org/call-for-papers/ …
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Danielle Belgrave proslijedio/la je Tweet
Are you a late-stage PhD student or a brand new postdoc? Consider submitting your best work to the Doctoral Consortium of ACM CHIL 2020 and get valuable feedback or collaborations going! Submission Deadline - February 3, 2020! Check out details here - http://www.chilconference.org/doctoral-consortium-call-for-phd-students/ …
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The Confidence Code. So much love for this book. So much resonates. So much truth. A must read for all women. Thank you
@FeryalMP for introducing me to this book.#changetheworld#changeyourworld#trainreadingsortedpic.twitter.com/6AjZaFQd23
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Danielle Belgrave proslijedio/la je Tweet
Earlier this month, I went to
#ML4H2019 at NeurIPS. The talks were recorded, which is amazing. But I know you aren't going to watch 6 hours of video. Maybe you'll read 40 minutes of summary, though!#MachineLearning#healthcarehttps://willieboag.wordpress.com/2019/12/27/ml4h-2019-machine-learning-for-health/ …Hvala. Twitter će to iskoristiti za poboljšanje vaše vremenske crte. PoništiPoništi -
Danielle Belgrave proslijedio/la je Tweet
Just wrapped
#NeurIPS2019! Notes here: https://david-abel.github.io/notes/neurips_2019.pdf …pic.twitter.com/xZgDmIfT67
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Danielle Belgrave proslijedio/la je Tweet
I’m honored to have won the best paper award for the public policy track of the AI for Social Good workshop! Thanks to all the organizers and reviewers for putting this great day together!https://twitter.com/benzevgreen/status/1201890071680626688 …
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Nyalleng
@nunuska wrap up#AIforsocialgood panel. She says that we need to take account of skills of local communities in solving local problems, even if those solutions are not AI. Also problems in local communities are not "their" problems, but these are "our" problemshttps://twitter.com/_hylandSL/status/1206031154647711744 …Hvala. Twitter će to iskoristiti za poboljšanje vaše vremenske crte. PoništiPoništi -
Danielle Belgrave proslijedio/la je Tweet
"Our field has hubris, we think because we can recommend kitten videos that we can save the world." - paraphrasing
@JCornebise#NeurIPS2019Prikaži ovu nitHvala. Twitter će to iskoristiti za poboljšanje vaše vremenske crte. PoništiPoništi -
Ben Green
@benzevgreen at the#Neurips2019 workshop on#AIforsocialgood. We need to be as rigorous about the question of what is good as we are with regards to what is AIpic.twitter.com/5V0WJlasmR
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Danielle Belgrave proslijedio/la je Tweet
Quite a somber discussion at ML4D today. My most important take away is: in development work, often that data point is a person and that person is probably not one of the powerful stakeholders. Handle with care.https://twitter.com/mariadearteaga/status/1205648187601473536 …
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Excellent work by Ying-Qi Zhao on estimating uncertainty measurements and causal effects in the context of observational datapic.twitter.com/qVBqu1qQsv
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A powerhouse of speakers at the
#NeurIPS2019 workshop on “Do the right thing”: machine learning and causal inference for improved decision making http://tripods.cis.cornell.edu/neurips19_causalml/ … Listening to Susan Murphy Challenges in Developing Learning Algorithms to Personalize Treatment in Real Timepic.twitter.com/iQeJ7ygqVJ
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The story has a happy ending where the authors of the paper worked with the manufacturers of the algorithm who retrained their models to reduce bias.pic.twitter.com/pl2IayiHoF
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Possible mechanisms for why this bias arises: disparity in access to treatment, but also disparity in how people are treated based on ethnographic studies, leading to a lack of trust in the healthcare systempic.twitter.com/mfvJYhtmnK
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