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10 Questions

Votes Activity Newest Views

3

votes

3

answers

86

views

How does adding a small change to an neuron's weighted input affect the overall cost?

neural-networks backpropagation

Jun 5 '19 at 11:57 DuttaA 5,308

2

votes

1

answer

51

views

Why does using a higher representation space lead to performance increase on the training data but not on the test data?

neural-networks machine-learning deep-learning deep-neural-networks

Sep 1 at 12:01 nbro♦ 26.2k

2

votes

1

answer

65

views

When using experience replay in reinforcement learning, which state is used for training?

neural-networks machine-learning reinforcement-learning q-learning dqn

Aug 12 at 21:07 nbro♦ 26.2k

2

votes

1

answer

223

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Why is the expected return in Reinforcement Learning (RL) computed as a sum of cumulative rewards?

reinforcement-learning q-learning rewards value-functions return

Jul 17 at 16:46 Neil Slater 18k

1

vote

0

answers

32

views

Why should variance(output) equal variance(input) in Xavier Initialisation?

neural-networks deep-learning feedforward-neural-network weights weights-initialization

Dec 1 at 13:10 nbro♦ 26.2k

1

vote

1

answer

23

views

How do LSTMs work if the following two matrices are not able to be multiplied?

neural-networks machine-learning recurrent-neural-networks long-short-term-memory

Oct 20 at 12:49 THAT_AI_GUY 157

1

vote

1

answer

97

views

In DQN, when do the parameters in the Neural Network update based on the reward received?

neural-networks machine-learning reinforcement-learning deep-learning dqn

Aug 13 at 13:30 THAT_AI_GUY 157

1

vote

1

answer

68

views

Why are Target Networks used in Deep Q-Learning as opposed to the Expected Value equation?

machine-learning reinforcement-learning deep-learning dqn deep-rl

Aug 13 at 8:52 Neil Slater 18k

1

vote

1

answer

105

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What is the purpose of a Neural Network in Reinforcement Learning when we have a Q-learning update rule?

neural-networks reinforcement-learning deep-learning training q-learning

Jul 16 at 17:45 harwiltz 706

0

votes

0

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27

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In LSTMs, how does the additive property enables better balancing of gradient values during backpropagation?

recurrent-neural-networks long-short-term-memory backpropagation vanishing-gradient-problem bptt

Oct 15 at 15:07 THAT_AI_GUY 157

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