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How do Transformer decoders handle arbitrary length input?

I am working through a Tensorflow Neural Machine Translation tutorial (https://www.tensorflow.org/text/tutorials/transformer) and am confused about how the decoder handles inputs when making ...
0 votes
0 answers
6 views

How does Supervised learning models handle time-varying data

I need to train a supervised learning model which would take some input which differs in its output relating to time. to better understand my question I would give a simple binary classification, the ...
0 votes
0 answers
10 views

Training loss decreases very fast after few epochs

I am implementing an ANN whose training loss is in Figure: As you can see training loss decreases very fast and it is approximately 3.2 at epochs 2, 3, ..., 8, ... 10, and so on. (batch learning) The ...
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0 votes
0 answers
7 views

How to remove boilerplate (or extract main content) from web pages?

Data: Raw source code of a website and the final cleaned main content I want to extract from the raw source code. The source code comes from different websites with different layouts and code ...
0 votes
0 answers
29 views

Why is the embedding of a task using Task2Vec not depend on the model?

I saw this in the Task2Vec paper: TASK2VEC depends solely on the task, and ignores interactions with the model which may however play an important role. To address this, we learn a joint task and ...
0 votes
1 answer
13 views

How can I use larger input images when using a pre-trained CNN without resizing?

I have a ResNet18 model trained on the Places365 image dataset, and I'd like to use this pre-trained model to expedite the training needed to identify distressed houses. My dataset is images of size ...
0 votes
0 answers
7 views

How can we approximate infinite horizon MDP with finite horizon MDP in the context of reinforcement learning?

For a given value of "discount factor" (and reward values' range) in fixed finite horizon markov decision process (MDP), upto how many episodes we have to extend this MDP so that we can ...
1 vote
0 answers
17 views

off-policy Monte Carlo learning: Why is Probability of Sampling a Trajectory the same as Having a return?

In Sutton and Barto's RL book, in the section for off-policy learning, we would like to find the expected value of the random variable $G_t$, given $S_t = s$ under our target policy: $$E_{\pi}[G_t|S_t ...
0 votes
0 answers
5 views

References for Stochastic Process for Sequential Decision Making

I am reading papers on Multi-armed bandit problem. In these papers, they use some notations in measure-theory like filtration, adapted filtration, and so on. Also, to prove theorems, many papers ...
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0 votes
1 answer
12 views

Is this a better formulation of the Turing test?

Would the Turing test be better formulated by assessing whether the creator (as opposed to a third party) was able to tell the difference between their program and a human? A magician, through the use ...
-1 votes
1 answer
22 views

Is AI the right tool for solving walking?

Modern robots walk like they had a heart attack and then a stroke... twice. Everyone in AI fiercely believes that the higher number of neurons (or the quality of training with smaller number of ...
0 votes
1 answer
31 views

What material might a truly sentient A.I. brain be made of?

I read that silicon may not be able to be create a robot brain that actually thinks because of its inability to process enough. Some people say nanomagents could generate low energy A.I. but I was ...
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0 answers
9 views

Unable to resolve: dot: graph is too large for cairo-renderer bitmaps. Scaling by 0.596708 to fit

I am building a random forest classifier using Grid search CV. I have build my best estimator tree using the graphviz library of python, but due to the depth and min_samples_per_leaf parameters my ...
1 vote
0 answers
15 views

Understanding the features given in Example 13.1 of Sutton and Barto

I'm struggling to understand the notation used to represent the features within Example 13.1 (Short corridor with switched actions" in the Sutton and Barto RL book. I assume as it is a free pdf ...
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0 votes
0 answers
11 views

PPO continous action space working in a complex scenario but failing to work in a simple scenario

I tried solving supply chain optimization problem using RL discrete and continuous actipn space. For some reason, with simplified version of problem (i.e. if customer order is always equal to 1), how ...
  • 111
-1 votes
1 answer
23 views

Extract a document page from a photo

I am trying to extract a document as an image from another image. Let's say that we take a photo of a document on a surface. My ultimate goal is to be able to digitize this document but as an image, ...
0 votes
1 answer
18 views

Detecting object position given the relative position of another object

I know that the title might be redundant but I'm trying to understand if there is way to predict where a specific object will be if I provide a certain object as a reference. See as an example the ...
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0 votes
0 answers
35 views

How does having zero advantage help with identifiability?

I am reading the D3QN paper and they have the following paragraph - Equation (7) is unidentifiable in the sense that given Q we cannot recover V and A uniquely. To see this, add a constant to V (s; θ,...
1 vote
1 answer
36 views

Similarities between 2d-vectors. (to flatten or to not)

I have this scenario where I need to measure the similarity between a 2d tensor t1: (100,8) and 61 tensors of the same shape(100,8). 100 represent time-steps and 8 is the no. of options. I first tried ...
2 votes
2 answers
82 views

Is Computer Vision always related to Machine Learning?

So I have AI project about motion detection with image subtraction. Regardless what are the object used, if there are change between two frames according threshold ...
1 vote
0 answers
31 views

Training a neural network simultaneously with two different loss functions rather than considering the weighted sum

This is a follow up on the already asked question: Is the neural network 100% accurate on training data if epoch loss is minimized to 0? I want to train a neural network that works as an approximator ...
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1 vote
0 answers
15 views

Can the Jacobian of a Neural Network be Full Column Rank?

Let $\mathcal{X}$ be the input data space and $\mathcal{Y}$ be the output data space. $f: \mathcal{X} \to \mathcal{Y}$ is a function represented by some Neural Network. Is it possible to to check if ...
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10 votes
2 answers
2k views

Using AI to extend an imagine pattern

I have created some nice patterns using the MidJourney tool. I'd like to find a way to extend these patterns, and I was thinking about an AI tool that takes one of these patterns and extends it in all ...
0 votes
0 answers
31 views

Implementation of DQN

Good day I attempted to implement DQN from scratch to solve the cartpole problem, the Tested my neural network class on the XOR table and it worked so I'm assuming the issue isn't with the neural ...
0 votes
0 answers
6 views

Frozen baseline for policy gradient rewards

I have a continuous reinforcement learning problem for which I use policy gradients and I use a baseline to decrease the variance of the gradients. The baseline that I used is the moving average of ...
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0 votes
1 answer
13 views

How to use Categorical Cross Entropy for Multi-Label Classification?

Say my target with classes A, B, C, D, E is [0, 1, 1, 0, 0]. And my output layer is of B x N where N is the number of classes. ...
0 votes
0 answers
9 views

Why DQN model select same action during the training

Now i try to create the DQN model. During the training process, the action value of each step is different, but most of the time, the same action is always selected. How can i solve it? Replay memory ...
0 votes
1 answer
24 views

What kind of neural network and GPU should I use to classify images into > 10 000 classes?

I am trying to developp an image classifier that would have more than 10 000 classes but I don't know what kind of neural network I should use ? Some Other questions arise from this one : How big ...
0 votes
0 answers
11 views

Matrix Dot Product of and [B, N] and [N x N] in Tensor

I have a pre-computed co-occurence matrix in shape of [NxN] I want to utilize this info on the last layer of my multi-label classification of [B, N]. Is dot product the best way to do it? How do I use ...
1 vote
1 answer
43 views

Can neural network be used to predict deltas between numbers?

I have a list of increasing numbers with no duplicates for example : 3,6,11 and so on. Difference or deltas between these numbers such as in above case : 3, 3, 5 are frequent and with greatest ...
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0 votes
0 answers
14 views

Best Paper to Begin Studying Prompt Engineering

I am into AI in general and NLP in particular. Besides, I have a background in philosophy, and the new LLMs like GPT-3 seem to have exciting capabilities. I want to study prompt engineering (for ...
0 votes
1 answer
33 views

Why is training of SVM so slow?

I've read it sometimes now, for example in A. Singh, N. Thakur and A. Sharma, "A review of supervised machine learning algorithms," and S. B. Kotsiantis, "Supervised Machine Learning: A ...
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0 answers
14 views

Adversarial training reduces MNIST test accuracy under FGSM attack

I have trained a basic convnet model on MNIST. I am conducting FGSM attack. The training accuracy is like 98%. and initial adversarial test accuracy under FGSM attack is like 20%. I tried to do ...
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0 votes
0 answers
10 views

Reinforcement Learning with sparse/delayed reward - should intermediate rewards be decayed over time/training?

I'm thinking of a situation like a game (say, chess) where the real objective/reward is actually determined at the very end. I understand that it's important/helpful to do reward shaping with ...
0 votes
0 answers
17 views
+50

Clustering by using Locality sensitive hashing *after* Random projection

It is well known that Random Projection (RP) is tightly linked to Locality Sensitive Hashing (LSH). My goal is to cluster a large number of points lying in a $d$-dimensional Euclidean space, where $d$ ...
1 vote
0 answers
6 views

How do I use the N correctly in NEATs speciation delta function?

When implementing NEAT I'm having some issues with the speciation distance/delta function, specifically the term N (number of genes in biggest genome). Won't term $N$ in $δ=c1*E/N+c2*D/N+c3*W$ just ...
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-1 votes
1 answer
60 views

Why do we need Tensorflow, Keras and other ML/AI modules?

This question might seem stupid at first glance, and it might be - that is because I am very new here and I've tried to think about an answer of my own, and search this question but to find no answer.....
  • 101
0 votes
0 answers
26 views

How to increase accuracy for CNN?

I have built one CNN model and applied it to chest-xray Covid 19 pneumonia dataset. I am getting the classification report as follows: I am surprised to see that it is giving an excellent result on ...
  • 111
0 votes
0 answers
7 views

How to Create a Fixed-Length, Binary, Sequence of Tokens Embedding?

Say I have 10 classes represented by 1 x n_classes vector of binary My goal is to embed a sequence of 1xN binary so that I could also model the class-co occurrence. Say, class A, B, D are present and ...
0 votes
0 answers
36 views
+100

Survey on non-machine learning object detection algorithms

I am working on a project in which I will be performing object detection on deformed objects. Unfortunately, there isn't enough data sets to train them on some neural network. I am looking for ...
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0 votes
0 answers
19 views

Can Graph Neural network leverage only the topological structure?

Graph Neural Networks (GNNs) are a powerful tool that allow learning on graphs by leveraging both the topological structure and the feature information for each node. For the particular problem I am ...
1 vote
2 answers
20 views

Why do iterative deepening search start from the root each iteration in the context of the minmax-algorithm?

Consider the graph below for an understanding on how IDS work. Now my question is: why do IDS start at the root every iteration, why not start at the previously searched depth in the context of minmax?...
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0 votes
1 answer
26 views

Model Suggestions for Real Life local Hospital Data

I'm doing a machine learning project and was looking for suggestions. It's meant to get the date, household, age, sex, doctor, date of the medical appointment, and type of medical appointment of a ...
0 votes
0 answers
10 views

How to determine whether this situation belongs to data leakage or not

Suppose that I use three features (x1, x2, x3) to predict the value of y. After hyperparameters tuning, the r2 score on train/valid/test set is 0.92, 0.54, 0.55 respectively, it's not so good.(It is ...
0 votes
0 answers
20 views

Utility function vs evaluation function vs heuristic function in terms of minmax + alphabeta

So i am trying to grasp the difference between a utility function, an evaluation function and an heuristic function in terms of the minmax algorithm with alphabeta on top. So far my understanding is ...
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0 votes
0 answers
29 views

Is it possible to compare Machine Learning algorithms on an abstract level without a specific use case?

I've got the task of comparing some ML algorithms at an abstract level on an argumentative basis. I wonder if this is possible in general without a specific use case (it is derived from ML in ...
2 votes
1 answer
95 views

Why diffusion model always use U-Net?

I want to know why diffusion models always use U-Net. In my opinion, they use U-Net because you can see features of different resolutions and skip connection is good to add detail of images. But I am ...
1 vote
1 answer
25 views

What loss function will be correlated with classification metrics?

Recently I developed a custom training algorithm for deep learning models, based on evolutionary algorithms. Details are not important, except that it also uses decreasing regular cross entropy loss ...
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0 votes
0 answers
11 views

Normal equations for linear decision boundary

For solving linear regression, we have gradient descent and the normal equations, with no iterations. In logistic regression, however, we have gradient descent but no known closed form solution. This ...
0 votes
1 answer
34 views

What is the role of self loop in Hidden Markov Models(HMM)?

What actually does the self-loop (within the single hidden state ) in the Hidden Markov model helpful for? I learn that one of the use cases concerning Natural language Understanding is that it helps ...

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