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Dismissing machine learning because it can't make sense of what it *hasn't* seen before it quite short-sighted. It is immensely valuable to be able to automatically recognize *what you are able to label* -- especially on hard pattern recognition problems, at super-human accuracy.
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Here's the opening lecture I gave on recent developments in deep learning and AI, and hopes for 2020. It's humbling beyond words to have the opportunity to lecture at MIT and to be part of a community that seeks to understand and engineer intelligence: https://www.youtube.com/watch?v=0VH1Lim8gL8 …pic.twitter.com/6BnfznndhS
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It took me a while to recap bc some papers are complex. Key points: - Destructing black box: convergence, generalization, neural tangent kernel - New approaches: Bayesian & uncertainty, graph, convex optimization - Neuroscience & bio-inspired algos - ...https://huyenchip.com/2019/12/18/key-trends-neurips-2019.html …
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Fun fact: More data can hurt in linear regression. https://arxiv.org/abs/1912.07242 (aside: this is about the 3rd time that studying deep learning has taught me something about linear regression).
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graphviz and pydot are fantastic. So I decided to make the most easy-to-use and pythonic library for their functionality that I could. Here is `fastdot`. I hope you like it. https://fastai.github.io/fastdot/ pic.twitter.com/IALMBs2rnV
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DeepRemaster: Temporal Source-Reference Attention Networks for Comprehensive Video Enhancement pdf: http://iizuka.cs.tsukuba.ac.jp/projects/remastering/data/remastering_siggraphasia2019.pdf … project page: http://iizuka.cs.tsukuba.ac.jp/projects/remastering/en/index.html … github: https://github.com/satoshiiizuka/siggraphasia2019_remastering …pic.twitter.com/rt8ID7XbTW
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Want to know how adversaries can game explainability techniques? Our latest research - "How can we fool LIME and SHAP? Adversarial Attacks on Explanation Methods" has answers: http://arxiv.org/abs/1911.02508 . Joint work with the awesome team:
@dylanslack20, Sophie, Emily,@sameer_Prikaži ovu nitHvala. Twitter će to iskoristiti za poboljšanje vaše vremenske crte. PoništiPoništi -
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1/ SciTwitter: I'm very excited to share our new Perspective article out in Nature Neuroscience today!https://www.nature.com/articles/s41593-019-0520-2 …
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Introducing Universal Adversarial Triggers Phrases that cause a specific model prediction when concatenated to 𝘢𝘯𝘺 input. Result - GPT-2 turns racist - SQuAD models predict "to kill american people" for 72% of "why" questions - Classifier acc 90%->1% http://ericswallace.com/triggers pic.twitter.com/a7yLZeXLdX
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How long is a "moment"? Moment was a medieval unit of time. 1 day was divided into 24 hours and 1 h was equal to 12 lengths of the period from sunrise to sunset. 1 h was divided into 4 puncta, 10 minuta, or 40 momenta. Considering an average 12 solar hours 1 moment = 90 secondspic.twitter.com/2LOZZWtSh2
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Wow, this can make documenting easier and fun!https://twitter.com/danijarh/status/1158380178973908997 …
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Pakistanis are the friendliest, most hospitable people on the planet. Ever since I landed everyone keeps telling me “apna mulk waapas jao gora” which means “we love you and welcome to our beautiful land.” So happy right now.
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Dyson's law: If AI systems were simple enough to be understandable, they'd be too simple to be intelligent.
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And there’s still a gender pay gap.pic.twitter.com/2gnauST9ND
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Shivangee proslijedio/la je TweetHvala. Twitter će to iskoristiti za poboljšanje vaše vremenske crte. PoništiPoništi
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Boarding a
@Delta flight and they’re using facial recognition. I had to track down a Delta representative to find out how to opt-out. They did not let travelers know that there was an option to not use it. Again, privacy needs to be the default, we need opt-in systemsPrikaži ovu nitHvala. Twitter će to iskoristiti za poboljšanje vaše vremenske crte. PoništiPoništi -
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Apparently, GANs are used to create fake profile pictures on LinkedIn for international industrial espionage.https://apnews.com/bc2f19097a4c4fffaa00de6770b8a60d …
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The l^p functional is convex and hence a norm for p>=1. It is sparsity-inducing for p<=1. The l^1 norm is the heart of the lasso, aka basis pursuit. https://en.wikipedia.org/wiki/Basis_pursuit_denoising … https://en.wikipedia.org/wiki/Lasso_(statistics) …pic.twitter.com/3oEq414LUD
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