Unanswered Questions
4,261 questions with no upvoted or accepted answers
16
votes
1
answer
338
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
- 1
11
votes
0
answers
377
views
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 ...
CommunityBot
- 1
10
votes
1
answer
859
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 ...
CommunityBot
- 1
9
votes
2
answers
441
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
- 1
8
votes
1
answer
664
views
Are there transformer-based architectures that can produce fixed-length vector encodings given arbitrary-length text documents?
BERT encodes a piece of text such that each token (usually words) in the input text map to a vector in the encoding of the text. However, this makes the length of the encoding vary as a function of ...
CommunityBot
- 1
8
votes
2
answers
398
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
- 1
8
votes
0
answers
115
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 ...
- 39.1k
8
votes
1
answer
158
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
- 1
8
votes
0
answers
111
views
What are the current trends/open questions in logics for knowledge representation?
What are the future prospects in near future from a theoretical investigation of description logics, and modal logics in the context of artificial intelligence research?
CommunityBot
- 1
8
votes
1
answer
4k
views
Does it make sense to use batch normalization in deep (stacked) or sparse auto-encoders?
Does it make sense to use batch normalization in deep (stacked) or sparse auto-encoders?
I cannot find any resources for that. Is it safe to assume that, since it works for other DNNs, it will also ...
CommunityBot
- 1
7
votes
0
answers
213
views
Why is there a Uniform and Normal version of He / Xavier initialization in DL libraries?
Two of the most popular initialization schemes for neural network weights today are Xavier and He. Both methods propose random weight initialization with a variance dependent on the number of input ...
- 618
7
votes
0
answers
258
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
- 1
7
votes
2
answers
127
views
Can training a model on a dataset composed by real images and drawings hurt the training process of a real-world application model?
I'm training a multi-label classifier that's supposed to be tested on underwater images. I'm wondering if feeding the model drawings of a certain class plus real images can affect the results badly. ...
CommunityBot
- 1
7
votes
1
answer
3k
views
How many training data is required for GAN?
I'm beginning to study and implement GAN to generate more datasets. I'll just try to experiment with state-of-the-art GAN models as described here https://paperswithcode.com/sota/image-generation-on-...
CommunityBot
- 1
7
votes
1
answer
141
views
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. ...
CommunityBot
- 1