Smarter training of neural networks | MIT News

Smarter training of neural networks | MIT News

MIT CSAIL project shows the neural nets we typically train contain smaller “subnetworks” that can learn just as well, and often faster.

31 mentions: @KirkDBorne@dnlcrl@waynerad@SigOpt@jreuben1@THEAdamGabriel@iamChuckRussell@sharon_smith_1
Date: 2019/05/20 14:18

Referring Tweets

@waynerad "The team likens traditional deep learning methods to a lottery. Training large neural networks is kind of like trying to guarantee you will win the lottery by blindly buying every possible ticket." https://t.co/0VN7PskQ1i
@SigOpt Researchers at @MIT_CSAIL found that neural networks, known for needing large datasets and extended time to train, contain subnetworks able to make similar predictions in less time. https://t.co/7QpdnbXuhA
@dnlcrl Neural nets typically contain smaller “subnetworks” that can often learn faster https://t.co/hAfVquKCQD
@jreuben1 Neural nets typically contain smaller “subnetworks” that can often learn faster https://t.co/tP4HuHebmB
@KirkDBorne #MachineLearning Research Scientists Have Figured Out How to Make #NeuralNetworks 90 Percent Smaller—but Just as Smart! https://t.co/I4UXJoubAH by @MIT_CSAIL #BigData #DataScientists #DataScience #AI
@THEAdamGabriel HT KirkDBorne : #MachineLearning Research Scientists Have Figured Out How to Make #NeuralNetworks 90 Percent Smaller—but Just as Smart! https://t.co/1g9fGyEfQb by MIT_CSAIL #BigData #DataScientists #DataScience #AI — Kirk Borne (KirkDBorne) May 12, 2019
@sharon_smith_1 Neural nets typically contain smaller “subnetworks” that can often learn faster https://t.co/NEMrzn17kX
@speedealz #NeuralNetworks typically contain smaller “subnetworks” that can often learn faster via https://t.co/xG2HaQZt1t https://t.co/OgwaYvgnQU

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