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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 5,251
 
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♦ 25.5k
 
2
votes
1
answer
60
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♦ 25.5k
 
2
votes
1
answer
186
views

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 17.3k
 
1
vote
0
answers
30
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♦ 25.5k
 
1
vote
1
answer
20
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
71
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
51
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 17.3k
 
1
vote
1
answer
96
views

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 686
 
0
votes
0
answers
25
views

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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