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14 Questions

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What are some use cases of discrete optimization in Deep Learning?

Apr 1 at 16:11 SpiderRico 620

vote

answers

views

How to deal with losses on different scales in multi-task learning?

deep-learning loss-functions gradient-descent multi-task-learning

Mar 18 at 10:42 nbro♦ 26.8k

vote

answer

views

Does feature scaling have any benefits if all features are on the same scale?

data-preprocessing features feature-engineering

Feb 24 at 19:10 Abhishek Verma 705

vote

answer

135

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Should we also shuffle the test dataset when training with SGD?

machine-learning training datasets stochastic-gradient-descent testing

Nov 3 at 13:57 nbro♦ 26.8k

vote

answer

142

views

Applications of Information Theory in Machine Learning

machine-learning deep-learning information-theory

Nov 23 at 1:57 nbro♦ 26.8k

votes

answers

views

Image classification on SVG format

neural-networks convolutional-neural-networks image-recognition

Aug 5 at 5:12 SpiderRico 620

votes

answers

views

Is there any application of topology to deep learning?

deep-learning theory topology

May 3 '20 at 23:37 DukeZhou♦ 6,048

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answer

128

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What are examples of machine learning techniques inspired by neuroscience?

machine-learning neuromorphic-engineering spiking-neural-networks neuroscience reservoir-computing

Apr 22 '20 at 16:35 nbro♦ 26.8k

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answers

views

Why do momentum techniques not work well for RNNs?

recurrent-neural-networks gradient-descent stochastic-gradient-descent momentum

Dec 13 at 12:37 nbro♦ 26.8k

votes

answers

views

Machine learning frameworks for esoteric languages [closed]

machine-learning programming-languages resource-request

Feb 13 '20 at 18:53 SpiderRico 620

votes

answer

155

views

Is there a reason to use TensorFlow over PyTorch for research purposes?

deep-learning tensorflow comparison research pytorch

Feb 13 '20 at 2:08 nbro♦ 26.8k

votes

answers

243

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Should I prefer the model with the lowest validation loss or the highest validation accuracy to deploy?

neural-networks deep-learning applications overfitting early-stopping

Mar 23 at 5:56 CuCaRot 367

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Are there optimizers that schedule their learning rate, momentum etc. autonomously?

optimization hyperparameter-optimization adam

Feb 6 '20 at 18:43 SpiderRico 620

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answer

117

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Is there a reason to choose regular momentum over Nesterov momentum for neural networks?

neural-networks comparison loss-functions gradient-descent hyperparameter-optimization

Feb 5 '20 at 6:48 Ketil Malde 124

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14 Questions

What are some use cases of discrete optimization in Deep Learning?

How to deal with losses on different scales in multi-task learning?

Does feature scaling have any benefits if all features are on the same scale?

Should we also shuffle the test dataset when training with SGD?

Applications of Information Theory in Machine Learning

Image classification on SVG format

Is there any application of topology to deep learning?

What are examples of machine learning techniques inspired by neuroscience?

Why do momentum techniques not work well for RNNs?

Machine learning frameworks for esoteric languages [closed]

Is there a reason to use TensorFlow over PyTorch for research purposes?

Should I prefer the model with the lowest validation loss or the highest validation accuracy to deploy?

Are there optimizers that schedule their learning rate, momentum etc. autonomously?

Is there a reason to choose regular momentum over Nesterov momentum for neural networks?