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31 views

Is the phrase "Feature Pyramid Network" refer to CNN only?

"Feature Pyramid Network" is a network that is used for feature extraction. Since it is pyramid in shape, it might be called so. Consider the following excerpts from two different sources #1 ...
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0answers
29 views

How to use EfficientDet for semantic segmentation?

In the EfficientDet paper, section 5.2. 5.2. EfficientDet for Semantic Segmentation, the authors say we modify our EfficientDet model to keep feature level $\{P2, P3, ..., P7\}$ in BiFPN, but only ...
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0answers
63 views

How is the sub-theory relation represented using Conceptual Graphs?

This post follows on from 3 previous questions (Q1,Q2,Q3) on Conceptual Graphs (CGs). This is a difficult question to pose, because it assumes that I know how to represent theories in CG. I do not ...
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1answer
35 views

Is there an approach where the output of one neural network is used to choose the next neural network?

I'd like to design a deep learning architecture in which the output of a primary neural network $M_{\theta}$ determines which neural network $N^i_{\alpha}$ in a set of secondary networks $\mathcal{N}$ ...
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0answers
30 views

How to use Actor-Critic RL with a categorical, state-dependent action space?

I have a problem where the agent is given an embedding vector to represent the state. Then it is also given a set of possible actions in the environment, let's say that the actions are each ...
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0answers
13 views

How does Stack-Augmented Recurrent Nets in work?

I am new to RNN/LSTM and I am working on a project about language modeling. I just got familiarized with simple RNN and LSTM. However, these simple models did not achieve the performance I want. Since ...
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1answer
50 views

Is there a way to use AI to compare thousands of files and detect the ones containing "unusual" content?

Is there a way to use python and AI to compare thousands of files and detect the ones containing "unusual" content? Those files are supposed to have "homogeneous" configuration ...
1
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1answer
28 views

How to calculate sensitivity and specificity given AUC score?

I couldn't find any relevant information on how to calculate sensitivity and specificity with AUC score. There is one picture that presents what I want, however I wasn't able to interpret it for my ...
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1answer
43 views

Can anyone please explain TFLite quantization part found in Netron neural network viewer?

I was checking tflite file in Netron. There I found the quantization formula in Netron as below: quantization: 0.007709330413490534 * (q + 3) I know the ...
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0answers
18 views

Is it possible that a deep neural network, with some variations, can be used for multiple tasks?

I am asking this question on deep neural network architectures only. If you want to restrict the domain of tasks then you can choose computer vision for this question. Suppose there is an architecture ...
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0answers
39 views

Is it effective to use deep learning method to produce a 1D signal as output from a 2D image as input?

I have a 1D signal that will produce a 2D image after some image processing algorithm. Would it be possible and effective to use deep learning method to reproduce the 1D signal if I have the 2D image ...
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1answer
56 views

Why is the performance of my neural network to predict if the mean of a randomly generated tensor is greater than $0.5$ not good?

I want to train a NN for classification the input x is a random tensor the output y=1 if ...
1
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0answers
29 views

What method is better to use for a two-player reinforcement learning environment?

I want to create an RL agent for a mancala-type two-player game as my first actual project in the field. I've already completed the game itself and coded a minimax algorithm. The question is: how ...
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1answer
48 views

How many layers and neurons in a FFNN do I need to make it equivalent to a CNN?

I started to learn machine learning early, and I studied the convolutional neural network and its ability to understand images and how it helps to reduce the number of parameters that need to be tuned....
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0answers
22 views

Is smoothing wrong in temporal predictions?

I found this paper from 2003 about predicting Forex rates: Using Recurrent Neural Networks To Forecasting of Forex. At the end of page 11, they say The network we built had two inputs and one output. ...
0
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1answer
57 views

What is the benefit of using a neural network instead of a look-up table in this case?

Assuming one has collected the 24 pairs of the input-output datasets for a target system: One can create a simple lookup table to describe the input-output behavior and utilize this as a controller. ...
1
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1answer
36 views

What exactly is data augmentation?

Data augmentation is useful in training. But, I am not sure when does a modification applied to data can be treated as data augmentation. Suppose a technique is applied on the instances of a dataset ...
1
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2answers
51 views

How to make NN distinguish between two types of functions (data)?

I have a neural network which is trying to predict two types of functions in a noisy setting. The input is an array, and the output is also an array. The two types of functions I am trying to predict ...
1
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0answers
37 views

Proper way to count environment steps / frames in distributed RL architecture for algorithms like CLEAR or LASER => modified impala with replay

In classical - on-policy - vtrace/Impala algorithm env_steps are incremented every training iteration like this : ...
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0answers
19 views

Does adding new keypoints increase accuracy for foot keypoint detection?

I am trying to have better results for foot keypoint detection(or foot pose estimation). In foot keypoints dataset the images labeleld for 6 different keypoints(big,small toes and heel for each foot). ...
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1answer
44 views

Is my intuition about RNN wrong?

Until today, my intuition about RNN (LSTM/GRU) was that this is some kind of NN that can remember previous inputs. Consider a task where you need to predict 0 if the previous input was 1. For example: ...
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1answer
34 views

Are there any algorithms (even backtracking variations) that solve the sudoku in a way more similar to this approach?

I looked a bit online for Sudoku solvers and it seems like all the answers I found involve a backtracking algorithm. However, this is not how humans (at least not me) solve Sudoku. We don't place in ...
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0answers
31 views

Is my calculation of the partial derivative of the cost function with respect to a single weight in the first layer correct?

I'm trying to understand the chain rule of backpropagation. This is what I understood. Is it correct? $$ \frac{\partial E }{ \partial w} = \sum_{i} \frac{\partial E }{ \partial a_i^{(l)} } (\sum_{j} \...
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0answers
17 views

What does "These designs employ skip connections to avoid a situation where the shortest path between time steps increases" mean?

Less popular alternatives include adding layers to the connections from input to the hidden state, between hidden states, or from the hidden state to the output. These designs employ skip connections ...
3
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1answer
65 views

How can we convert an MDP to a POMDP?

If a partially observable Markov decision process (POMDPs) is a generalisation of a (fully observable) MDP, then how exactly can we mathematically formulate an MDP as a POMDP?
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0answers
13 views

How to train with a non-differentiable activation function (such as SVT in deep unrolling low-rank optimization)?

I planned to design a deep unfolding for decomposition into low-rank and sparse in Pytorch environment. I read this paper that might help me to understand how to do it. I always taught that this model ...
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0answers
18 views

Augmented an Image with other data when training CNN

In the typical RL/MDP framework, I have offline data of $(s,a,r,s')$ of expert Atari gameplay. I'm looking to train a CNN to predict $r$ based on $(s, a)$. The states are represented by a $4 \times 84 ...
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0answers
23 views

Why some encoders reduce dimensionality of data while some others increase it?

We know that the encoder part in VAE reduces dimensions of data. In some other papers related to neural radiance fields and 3d shape reconstruction like https://arxiv.org/pdf/2106.01553.pdf, the ...
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0answers
52 views

How can we formulate a state-space search problem as a Markov decision process?

A Markov Decision Process (MDP) is a mathematical model for sequential decision-making in stochastic environments. Formally, we can define an MDP as a tuple $M = (S, A, p, \gamma)$, where $S$ is the ...
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2answers
39 views

How do sine and cosine transforms help in extracting frequencies in time series forecasting models?

I'm trying to learn how time series forecasting models work and while reading a tutorial off the TensorFlow website I came across these algorithms. I don't quite understand what the article means by &...
0
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1answer
34 views

Order of operations on sparse recurrent network alters the output. How to deal with it?

I'm working on an implementation of NEAT, which evolves neural networks with small and sparse topologies. Evaluating a sparse and possibly recurrent network requires a different approach than the ...
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0answers
28 views

GAN performance starts to get worse as training continues

I'm currently trying to train a GAN to recreate similar images from a dataset. The dataset is using the Eiffel Tower Pictures from Googles Quick Draw dataset. The images aren't very large (only 12x12 ...
1
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0answers
27 views

What is the difference between the $Q_a$ calculated to update delta and those to select next action in the exploitation phase?

As the title suggests, I have a doubt about the computation of the $Q_a$ used to update the delta and the $Q_a$ used to select the next action in the exploitation phase, as shown below (source of ...
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0answers
29 views

Could anyone please explain this sentence about training in parallel?

One way to reduce the computational complexity of hidden state recurrences is to connect a unit's hidden state to the prior unit's output rather than its hidden state. The resulting RNN has a lower ...
0
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0answers
19 views

How to train a FCNN with audio spectrogram images?

I'm working on an audio dereverberation deep learning model, based on the U-net architecture. The idea of my project came from image denoising with autoencoders. I feed the reverberated spectrogram to ...
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0answers
28 views

What are the "per image" annotations that are generally used for image datasets in AI?

Computer vision is highly benefited by AI algorithms. Image data is abundantly available. There are different varieties of tasks such as image classification, prediction, segmentation, generation, ...
0
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1answer
55 views

How to derive the dual function step by step in relative entropy policy search (REPS)?

TL:DR, (Why) is one of the terms in the expectation not derived properly? Relative entropy policy search or REPS is used to optimize a policy in an MDP. The update step is limited in the policy space (...
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0answers
12 views

Is there some algorithms to get rid of pulses of noise in a video? [closed]

At about 0:12, 0:19, 0:21, 0:22 and 0:23 into the video, there are lots of pulses of noise. Is there some algorithms to get rid of them automatically?
2
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0answers
44 views

Watkins' Q(λ) with function approximation: why is gradient not considered when updating eligibility traces for the exploitation phase?

I'm implementing the Watkins' Q(λ) algorithm with function approximation (in 2nd edition of Sutton & Barto). I am very confused about updating the eligibility traces because, at the beginning of ...
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0answers
17 views

Are there any resources about using RL with RNN to produce Open AI Five-type of AI?

I want to make a minimal working version of Open AI Five. It seems it uses PPO with LSTM, but I don't know how to implement the actual code, and couldn't find any online tutorials for it. Are there ...
1
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0answers
17 views

Is there a paper/article on contextual $\epsilon$-greedy algorithm?

I am reading the paper A Contextual-Bandit Approach to Personalized News Article Recommendation, where it refers to $\epsilon$-greedy (disjoint) algorithm. I suspect, that it is just a version of a K-...
1
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0answers
22 views

NEAT: How to properly handle Node IDs and avoid Competing Conventions?

I'm working on yet another NEAT implementation for a personal project, and I feel like I'm missing something about the proposed solution to the Competing Conventions problem. Here's what I'm assuming: ...
1
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1answer
27 views

What inherent quality of a function makes it treated as either loss or evaluation metric?

A neural network model needs a loss function for training. The neural network needs to minimize the loss function. A neural network is evaluated after training using a metric. The neural network needs ...
-1
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0answers
20 views

Algorithms for classification of very short text

I am to create a classification model for texts that typically have 3 to 4 words in them. I thought of using BERT and XLNet but not sure if they are the right choice for texts that short. Are there ...
-1
votes
1answer
69 views

Why is the cross-entropy a cost function?

The question looks foolish, but I think cross-entropy is somewhat weird as a cost function. As a cost function for linear regression, the mean square error $ \sum_{i=1}^{n} (y_i - (ax_i+b)) ^2$ seems ...
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0answers
12 views

Evaluating different board states with a minimax AI algorithm python

I am working on writing a connect 4 game as well as a minimax algorithm to play against. I am currently writing and implementing the minimax algorithm. Right now I am just trying to print out all ...
0
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0answers
21 views

Is categorical cross entropy better than binary cross entropy for imbalanced binary classification problems

I am training a NN model. The data is highly imbalanced (3% for positive labels), and I have not resampled more true classes in the training set. The model performs much better when categorical cross-...
-1
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0answers
15 views

How to automatically generate yes/no questions from a paragraph to train question-answer systems?

In order to train a question-answer model without the use of external labelers, it would be good to generate training questions and answers automatically from a given paragraph. For instance if I have ...
0
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0answers
26 views

How to normalize rewards in DQN?

I want to use a Deep Q-Network for a specific problem. My immediate rewards ($r_t = 0$) are all zeros. But my terminal reward is a large positive value $(r_T=100$). How could I normalize rewards to ...
-1
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0answers
35 views

why GPU is faster than a CPU to train or made inference in a neural network? [duplicate]

Is because a GPU is composed by a lot of proccessors (more than 1000)? what kind of calculous is better to perform on a gpu instead of a CPU?

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