Unanswered Questions
12,575 questions with no upvoted or accepted answers
22
votes
1
answer
3k
views
Understanding Timestamps and Batchsize of Keras LSTM considering Hiddenstates and TBPTT
What I'm trying to do
What I am trying to do is predicting the next data-point $x_t$ for each point in the timeseries $[x_0, x_1, x_2,...,x_T]$ in the context of a date-stream in real-time, in theory ...
CommunityBot
- 1
22
votes
2
answers
554
views
Formal proof of vanilla policy gradient convergence
So I stumbled upon this question, where the author asks for a proof of vanilla policy gradient procedures. The answer provided points to some literature, but the formal proof is nowhere to be included....
CommunityBot
- 1
10
votes
0
answers
2k
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Find missing object(s) in image with a priori knowledge about the missing object(s) (w.r.t base image)
Problem Statement:
I am working on developing a method, or borrow/modify/combine existing ones, where given an golden image (reference or base with all expected objects to be present), it is able to ...
- 4,108
10
votes
1
answer
551
views
A clear visualization of a two-way ANOVA
To provide a full yet simple picture of a 3-level, one-way ANOVA, I use the following visualization where variation within each group (the filled circles) and variation between the groups (black ...
CommunityBot
- 1
9
votes
2
answers
320
views
Are there any graph embedding algorithms like this already?
I wrote an algorithm for generating node embeddings based on the graph's topology. Most of the explanation is done in the readme file and the examples.
The question is:
Am I reinventing the wheel?
...
CommunityBot
- 1
9
votes
3
answers
3k
views
Loss Function for Probability Regression
I am trying to predict a probability with a neural network, but having trouble figuring out which loss function is best. Cross entropy was my first thought, but other resources always talk about it in ...
CommunityBot
- 1
9
votes
0
answers
2k
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Why is my Keras model not learning image segmentation?
Edit: as is turns out, not even the model's initial creator could successfully fine-tune it. This is most likely a problem of implementation, or possibly related to the non-intuitive way in which the ...
- 2,981
9
votes
0
answers
2k
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AdaBoost implementation and tuning for high dimensional feature space in R
I am trying to implement the AdaBoost.M1 algorithm (trees as base-learners) to a data set with a large feature space (~ 20.000 features) and ~ 100 samples in R. ...
- 203
8
votes
1
answer
887
views
Gensim LDA model: return keywords based on relevance (λ - lambda) value
I am using the gensim library for topic modeling, more specifically LDA. I created my corpus, my dictionary, and my LDA model. With the help of the pyLDAvis library I visualized the results. When I ...
CommunityBot
- 1
8
votes
0
answers
115
views
Training value neural network AlphaGo style
I have been trying to replicate the results obtained by AlphaGo following their supervise learning protocol. The papers specify that they use a network that has two heads: a value head that predicts ...
8
votes
3
answers
640
views
Chi-square as evaluation metrics for nonlinear machine learning regression models
I am using machine learning models to predict an ordinal variable (values: 1,2,3,4, and 5) using 7 different features. I posed this as a regression problem, so the final outputs of a model are ...
CommunityBot
- 1
8
votes
0
answers
198
views
How to predict advantage value in deep reinforcement learning
I'm currently working on a collection of reinforcement algorithms: https://github.com/lhk/rl_gym
For deep q-learning, you need to calculate the q-values that should be predicted by your network. There ...
- 19.4k
8
votes
0
answers
2k
views
Python : Feature Matching + Homography to find Multiple Objects
I'm trying to use OpenCV via Python to find multiple objects in a train image and match it with the key points detected from a query image. For my case, I'm trying to detect the tennis courts in the ...
7
votes
0
answers
9k
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How is WordPiece tokenization helpful to effectively deal with rare words problem in NLP?
I have seen that NLP models such as BERT utilize WordPiece for tokenization. In WordPiece, we split the tokens like playing to play and ##ing. It is mentioned that it covers a wider spectrum of Out-Of-...
- 1,773
7
votes
0
answers
3k
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Tensorflow v1 Dataset API AttributeError with ndim
I'd like to make pipeline for optimizing Gpu and Cpu.
Dataset
It's about 10000 datapoint and 4 description variables for the regression problem.
...
- 203