Unanswered Questions
3,715 questions with no upvoted or accepted answers
14
votes
1
answer
244
views
Will parameter sweeping on one split of data followed by cross validation discover the right hyperparameters?
Let's call our dataset splits train/test/evaluate. We're in a situation where we require months of data. So we prefer to use the evaluation dataset as infrequently as possible to avoid polluting our ...
CommunityBot
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13
votes
3
answers
493
views
Can some one help me understand this paragraph from Nvidia's progressive GAN paper?
Furthermore, we observe that mode collapses traditionally
plaguing GANs tend to happen very quickly, over the course of a dozen mini-batches. Commonly
they start when the discriminator overshoots, ...
CommunityBot
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12
votes
0
answers
258
views
What is the number of neurons required to approximate a polynomial of degree n?
I learned about the universal approximation theorem from this guide. It states that a network even with a single hidden layer can approximate any function within some bound, given a sufficient number ...
- 33k
10
votes
0
answers
276
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Extending FaceNet’s triplet loss to object recognition
FaceNet uses a novel loss metric (triplet loss) to train a model to output embeddings (128-D from the paper), such that any two faces of the same identity will have a small Euclidean distance, and ...
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9
votes
0
answers
148
views
Why is my GAN more unstable with bigger networks?
I am working with generative adversarial networks (GANs) and one of my aims at the moment is to reproduce samples in two dimensions that are distributed according to a circle (see animation). When ...
- 2,977
9
votes
2
answers
366
views
Back-of-the-envelope machine learning (specifically neural networks) calculations
There is a popular story regarding the back-of-the-envelope calculation performed by a British physicist named G. I. Taylor. He used dimensional analysis to estimate the power released by the ...
CommunityBot
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9
votes
0
answers
764
views
Are Cellular Neural Networks one type of Neural Networks?
I am researching Cellular Neural Networks and have already read Chua's two articles (1988). In cellular neural networks, a cell is only in relation with its neighbors. So it is easy to use them for ...
- 33k
8
votes
1
answer
196
views
How to deal with a small amount of labeled samples?
I'm trying to develop skills to deal with very small amounts of labeled samples (250 labeled/20000 total, 200 features) by practicing on Kaggle "Don't Overfit" dataset (Traget_Practice have ...
CommunityBot
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8
votes
1
answer
179
views
Why are documents kept separated when training a text classifier?
Most of the literature considers text classification as the classification of documents. When using the bag-of-words and Bayesian classification, they usually use the statistic TF-IDF, where TF ...
CommunityBot
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7
votes
1
answer
110
views
Validation accuracy higher than training accurarcy
I implemented the unet in TensorFlow for the segmentation of MRI images of the thigh. I noticed I always get a higher validation accuracy by a small gap, independently of the initial split. One ...
CommunityBot
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7
votes
0
answers
200
views
Is the Bellman equation that uses sampling weighted by the Q values (instead of max) a contraction?
It is proved that the Bellman update is a contraction (1).
Here is the Bellman update that is used for Q-Learning:
$$Q_{t+1}(s, a) = Q_{t}(s, a) + \alpha*(r(s, a, s') + \gamma \max_{a^*} (Q_{t}(s',
...
CommunityBot
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7
votes
2
answers
254
views
How can I solve the zero subset sum problem with hill climbing?
I want to solve the zero subset sum problem with the hill-climbing algorithm, but I am not sure I found a good state space for this.
Here is the problem: consider we have a set of numbers and we want ...
CommunityBot
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7
votes
0
answers
76
views
Normalizing Normal Distributions in Thompson Sampling for online Reinforcement Learning
In my implementation of Thompson Sampling (TS) for online Reinforcement Learning, my distribution for selecting $a$ is $\mathcal{N}(Q(s, a), \frac{1}{C(s,a)+1})$, where $C(s,a)$ is the number of times ...
- 33k
7
votes
1
answer
79
views
What is the impact of using multiple BMUs for self-organizing maps?
Here's a sort of a conceptual question. I was implementing a SOM algorithm to better understand its variations and parameters. I got curious about one bit: the BMU (best matching unit == the neuron ...
CommunityBot
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7
votes
1
answer
104
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How does the network know which objects to track in the paper "Label-Free Supervision of Neural Networks with Physics and Domain Knowledge"?
I was reading the paper Label-Free Supervision of Neural Networks with Physics and Domain Knowledge, published at AAAI 2017, which won the best paper award.
I understand the math and it makes sense. ...
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