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Portugal's government now wants to restrict "golden visa" incentives for foreign property buyers to purchases outside Lisbon and the northern city of Oporto https://trib.al/w06OF8A via
@bpoliticsHvala. Twitter će to iskoristiti za poboljšanje vaše vremenske crte. PoništiPoništi -
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For perspective, since China first reported it Dec. 30, the coronavirus has killed 305 people worldwide while car crashes have killed about 125,000.https://twitter.com/business/status/1223829695252385794 …
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Success: I trained ResNet-50 on imagenet to 75.9% top-1 accuracy in 3.51 minutes using a 512-core TPUv3. (480,000 images per second. 224x224 res JPG.) Before you think highly of me, all I did was run Google’s code. It was hard though. Logs: https://tensorboard.dev/experiment/jsDrRUynRXyw6dC2Fzpy4g …pic.twitter.com/E6b3cMD5r0
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A great way to realise the sheer quantity of information our
seamlessly processes when we do a “simple” task like driving a car.
This is what the Tesla autopilot sees using a neural network which took 70,000 GPU hours to train.
ht @Rainmaker1973pic.twitter.com/pRSE2WJsBjHvala. Twitter će to iskoristiti za poboljšanje vaše vremenske crte. PoništiPoništi -
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+1! IMHO the most successful machine learning system of all, internet search, is a great example of this. search is just a super powered externalised memory. the next-big-thing (TM) will be super powered externalised cognition. we want to augment ppl rather than automating them.https://twitter.com/fchollet/status/1221203452329484289 …
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#Breaking: Confirmed - A new hospital in#Wuhan in#China is being build right now, and will be finished within 6 days, to transfer all patients with the only symptoms of the#Coronavirus to begin cleaning all of the other hospitals. The hospital will be demolished afterwards.pic.twitter.com/9k3NeMOVFnPrikaži ovu nitHvala. Twitter će to iskoristiti za poboljšanje vaše vremenske crte. PoništiPoništi -
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Lloyd’s algorithm is the continuous counterpart of k-means. Optimizes the optimal quantization energy, which is an optimal transport distance to free Dirac masses. https://en.wikipedia.org/wiki/Lloyd%27s_algorithm … https://en.wikipedia.org/wiki/Vector_quantization …pic.twitter.com/kDENINfetH
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The argument for VAE disentangling representations is that the latent state is normal hence its components are independent. Any rotation would entangle without changing the distribution, so why have components often a clear semantic?
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A mixture of Gaussians model can be represented as a weighted points cloud (actually a measure) over the mean/covariance domain. Mixture fitting is a non-convex optimization problem. https://en.wikipedia.org/wiki/Mixture_model …pic.twitter.com/PFAesnpfko
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Had to verify. And yes. Kernighan and Ritchie really did this. TIL :)pic.twitter.com/KyRqgzRTr2
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A General and Adaptive Robust Loss Function https://arxiv.org/abs/1701.03077 They propose an analytical function that can represent a family of well known robust cost functions just with a single parameter (alpha). Alpha lets you walk through L2, huber, cauchy, tukey and more.pic.twitter.com/Uy5nB7DoOR
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I could propose such predictor: until GANs are not used on
#kaggle, they don't help.https://twitter.com/ducha_aiki/status/1213067461035204608 …Hvala. Twitter će to iskoristiti za poboljšanje vaše vremenske crte. PoništiPoništi -
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Before ML Twitter gets sick of hearing about
#NeurIPS2019, I wanted to highlight a really cool talk by Prof. Zhiru Zhang from Cornell about Neural Network and Hardware co-design. Here’s a great summary slide giving an overview of different NN model optimization techniques!pic.twitter.com/g9xjPC2XyD
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Solving linear systems comes with different flavors.pic.twitter.com/hp95oDuI79
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For saddle point problems and more general games, gradient descent can cycle and diverge. Using an extrapolation steps adresses this issue and converges to a saddle point (Nash equilibrium). https://en.wikipedia.org/wiki/Variational_inequality …pic.twitter.com/Kpxbd2Cqbh
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Found this gem @
#Neurips2019! Using orthogonal property of Legendre polynomials, Legendre Memory Units (LMU) can efficiently handle temporal dependencies spanning 100k timesteps, converge rapidly and use fewer internal state-variables compares to LSTMs. https://papers.nips.cc/paper/9689-legendre-memory-units-continuous-time-representation-in-recurrent-neural-networks.pdf …pic.twitter.com/xGsEtTlok5
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1st 90+ on GLUE
! Baidu’s pre-training language model ERNIE achieves new #SOTA on#GLUE (90.1) and becomes the 1st team to elevate the overall score above 90. View more at https://gluebenchmark.com/leaderboard . Our paper of ERNIE 2.0 has been accepted by#AAAI2020. https://arxiv.org/abs/1907.12412 pic.twitter.com/zTfFre3Ikx
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#NeurIPS2019 Wednesday: Fun day ahead! -9:20 to 10:05 Meet the#AlphaStar team at the@DeepMindAI stand -CAS Score for evaluating gen. models, 10:45 Poster #111 -VQVAE2, 17:00 Poster #140pic.twitter.com/k7oJcPaiWa
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We’ve invested in an app for people who text “I’m going to be in LA/SF/NY next week who should I meet?” Currently in TestFlight, growing 30% daily, the round was oversubscribed instantly.
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