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Prikvačeni tweetHvala. Twitter će to iskoristiti za poboljšanje vaše vremenske crte. PoništiPoništi
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By popular demand, we've extended the L4DC submission deadline until December 20. Enjoy the learning and control conferences between now and then!https://sites.google.com/berkeley.edu/l4dc/home …
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Reminder that submissions for L4DC 2020 are due this Friday! Any exciting results bridging machine learning, dynamics, and control are welcome and encouraged. More info here:https://sites.google.com/berkeley.edu/l4dc/call-for-papers …
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ICYMI: Reminder that submissions for L4DC 2020 are now open. Deadline is December 6. We’re excited to read your contributions!https://sites.google.com/berkeley.edu/l4dc/call-for-papers?authuser=0 …
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The strangest misconception of the current deepRL craze is that sim2real is hard.
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Seems troubling: Many of the images in the CXR-14 chest x-ray data set are post treatment and have chest drains in the images. Once these examples are removed, machine learning performs worse than a first year resident. h/t
@DrLukeOR https://arxiv.org/abs/1909.12475Hvala. Twitter će to iskoristiti za poboljšanje vaše vremenske crte. PoništiPoništi -
Unreasonably excited by the package I received today! I never get anything good in my work mailbox. So cool that this book is out.pic.twitter.com/gEoQ0J1tVe
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Ben Recht proslijedio/la je Tweet
Stich Fix is selling something called pants, a concept from quantum mechanics.https://twitter.com/WIRED/status/1181437300414275584 …
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4 years ago today,
@pinboard called out the perils of big data in a keynote at@strataconf. Worth taking 20 mins to see how prescient he was and how much work is left to do.https://www.youtube.com/watch?v=GAXLHM-1Psk …Hvala. Twitter će to iskoristiti za poboljšanje vaše vremenske crte. PoništiPoništi -
Ben Recht proslijedio/la je Tweet
We're excited to release a draft of the causality chapter at http://fairmlbook.org . There's been lots of interest in the topic and we hope the chapter is a helpful introduction.https://twitter.com/mrtz/status/1019628022897373184 …
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Ben Recht proslijedio/la je Tweet
To better know Media Lab history & context, check out smart & careful work of these 2 women (who I also proudly call friends):
@maximolly on roots of ML money https://medium.com/@maximolly/what-you-make-up-for-in-gall-ca1a221122af …@morgangames on ML design & development ideologies; “Charisma Machine” https://mitpress.mit.edu/books/charisma-machine …Hvala. Twitter će to iskoristiti za poboljšanje vaše vremenske crte. PoništiPoništi -
Thanks to
@froystig for teaching me how to pronounce name of the AI conference we have in Winter.pic.twitter.com/uiSUtOCsqD
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Michael Hiltzik pulls no punches about MIT’s embarrassing Koch problem:https://www.latimes.com/business/story/2019-08-26/how-mit-whitewashed-david-koch …
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It’s infuriating to compare MIT’s plea for forgiveness for taking $800K from Epstein to its fawning, whitewashing eulogy of David Koch who gave them hundreds of millions. These were posted a day apart from each other: http://news.mit.edu/2019/letter-regarding-jeffrey-epstein-and-mit-0822 …http://news.mit.edu/2019/david-koch-prominent-supporter-cancer-research-mit-dies-79-0823 …
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Remember when OpenAI invented the ResNet? Neither do I, because it was developed at Microsoft Research.
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And awesome to see many Berkeley alums thriving here.
@LaurentLessard,@DimitrisPapail, and Shivaram Venkataraman.pic.twitter.com/Q31u2quOKZ
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Was amazing to catch up with my great Madison colleagues,
@lauralak,@JSEllenberg, Rob Nowak,@WillettBecca,@madsjw. Though sad to miss@JeffLinderoth who was building human pyramids in Germany.Hvala. Twitter će to iskoristiti za poboljšanje vaše vremenske crte. PoništiPoništi -
You can check out many more examples here: https://modestyachts.github.io/natural-perturbations-website/results.html … (4/4)
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Surprisingly, detection algorithms were just as vulnerable as classification algorithms to subtle changes in view. The fox becomes a sheep, the airplane becomes a horse, the motorcycle becomes a lizard. All examples occur within 10 frames of each other in the video. (3/4)pic.twitter.com/WYgomoxeiA
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This work follows up on inspirational work by Azulay and Weiss (https://arxiv.org/abs/1805.12177 ) and Gu et al. (https://arxiv.org/abs/1904.10076 ) which highlighted the variability of image classifiers over videos. (2/4)
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Today’s talk features, in particular, some great work by
@Vaishaal, Achal Dave,@BeccaRoelofs, and@lschmidt3 systematically breaking image classifiers using video. Code, paper, and data are here: https://modestyachts.github.io/natural-perturbations-website/ … (1/4)Prikaži ovu nitHvala. Twitter će to iskoristiti za poboljšanje vaše vremenske crte. PoništiPoništi
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