Questions tagged [training]

For questions about training networks, rules systems, or other AI system components.

92 questions with no upvoted or accepted answers
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3answers
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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 minibatches. Commonly they start when the discriminator overshoots, ...
6
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2answers
78 views

Why do very deep non resnet architectures perform worse compared to shallower ones for the same iteration? Shouldn't they just train slower?

My understanding of the vanishing gradient problem in deep networks is that as backprop progresses through the layers the gradients become small, and thus training progresses slower. I'm having a hard ...
5
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1answer
175 views

For each epoch, can I use only on a subset of the full training dataset to train the neural network?

If one has a dataset large enough to learn a highly complex function, say learning chess game-play, and the processing time to run mini-batch gradient descent on this entire dataset is too high, can I ...
4
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0answers
14 views

How do weights changes handles during back-propagation when there are unknown labels

I have a question about how weights are updated during back-propagation for some of my samples that have unknown labels (please note, unknown, not missing). The reason they are unknown is because this ...
4
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0answers
50 views

Training and inference for highly-context-sensitive information

What is the best way to train / do inference when the context matters highly as to what the inferred result should be? For example in the image below all people are standing upright, but because of ...
4
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1answer
54 views

GPU/TPU acceleration for neural networks with various network topologies

I was thinking about different neural network topologies for some applications. However, I am not sure how this would affect the efficiency of hardware acceleration using GPU/TPU/some other chip. If, ...
3
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1answer
24 views

What is meant by the expected BLEU cost when training with BLEU and SIMILE?

Recently I was reading a paper based on a new evaluation metric SIMILE. In a section, validation loss comparison had been made for SIMILE and BLEU. The plot showed the expected BLEU cost when training ...
3
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0answers
17 views

How to organize model training hyperparameters

I am working on multiple deep learning projects, most of them in the area of computer vision. For many of them I create multiple models, try different approaches, use various model architectures. And ...
3
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1answer
57 views

REINFORCE algorithm for portfolio optimization - problem while training

I'm trying to implement the Reinforce algorithm (Monte Carlo policy gradient) in order to optimize a portfolio of 94 stocks on a daily basis (I have suitable historical data to achieve this). The idea ...
3
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0answers
29 views

How to train a model to extract custom and unknown entities

I'm trying to figure out how to extract specific text from an utterance by a user. I need to extract "unknown" text from a short and simple text. In this case, the user wants to create a list. ...
3
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0answers
47 views

When to use RMSE as opposed to MSE and vice versa?

I understand that RMSE is just the square root of MSE. Generally, as far as I have seen, people seem to use MSE as a loss function and RMSE for evaluation purposes, since it exactly gives you the ...
3
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1answer
161 views

How can I incrementally train a Yolo model without catastrophic forgetting?

I have successfully trained a Yolo model to recognize k classes. Now I want to train by adding k+1 class to the pre-trained weights (k classes) without forgetting previous k classes. Ideally, I want ...
3
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0answers
50 views

How to train CNN such it eliminate dependent features and focuses on independent ones?

How we should train a CNN model when training dataset contains only limited number of cases, and the trained model is supposed to predict class (label) for several other cases, which has not seen ...
3
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1answer
444 views

Periodic Pattern in Validation Loss Curve

I am currently trying to solve a regression problem using neural networks. I want to detect movement patterns in images over time (video) and output a continuous value. During the training process I ...
2
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0answers
18 views

How can I implement a Facial Recognition algorithm in C++ from scratch, without using OpenCV?

I wanna implement an algorithm for Facial Recognition in C++ with the help of Viola-Jones, aka Adaboost, but without using OpenCV or any other similar library. I wanna do it all from scratch. Any tips?...
2
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0answers
22 views

What could cause a big fluctuation of the loss in the last epochs of training an AlexNet?

I am training an AlexNet neural network, with about 12000 images which 80% is for training, 10% is for validation and another 10% is for testing. I have a problem in my plots. There is a big ...
2
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1answer
22 views

Data scan not making sense for coco dataset

I am doing a simple scan to see how dataset size affects training. Basically, I took 10% of the coco dataset and trained a yolov3 net (from scratch) to just look for people. Then I took 20% of the ...
2
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0answers
13 views

Why is the loss of one of the outputs of a model with multiple outputs increasing while the others are decreasing?

I'm a newbie in neural networks. I'm trying to fit my neural network that has 3 different outputs: semantic segmentation, box mask and box coordinates. When my model is training, the loss of ...
2
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0answers
16 views

What effect does increasing the actions in RL have?

Consider a 2D snake game, where the snake has to eat food to become longer. It must avoid hitting walls and biting into her tail. Such a game could have a different amount of actions: 3 actions: go ...
2
votes
1answer
38 views

When training a CNN, what are the hyperparameters to tune first?

I am training a convolutional neural network for object detection. Apart from the learning rate, what are the other hyperparameters that I should tune? And in what order of importance? Besides, I read ...
2
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0answers
16 views

Which CNN hyper-parameters are most sensitive to centered versus off centered data?

Which hyper-parameters of a convolutional neural network are likely to be the most sensitive to depending on whether the training (and test and inference) data involves only accurately centered images ...
2
votes
1answer
56 views

How difficult is this sound classification?

I want a microphone to pick up sounds around me (let's say beyond a 3 foot radius), but ignore sounds made at my desk, such as the rustling of paper, clicking a mouse and typing, my hands brushing up ...
2
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0answers
44 views

What form of output would be needed to train a model on a connect 4 AI?

I've had a big interest in machine learning for a while, and I've followed along a few tutorials, but have never made my own project. After losing many games of connect 4 with my friends, I decided to ...
2
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0answers
726 views

How to transfer learn Darknet YOLOv3

I've started getting into object detection in image. I have YOLOv3 neural network with Darknet framework. The network is pre-trained from COCO data set. Now I need to do some transfer learning in ...
2
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0answers
17 views

A NN based model of a Cattle for 'Heat Detection'

I am very new to AI/ML but have lot of interest in these. I am trying to understand how this gadget works. So far I have understood that a NN model of the cattle is generated by offline ...
2
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0answers
21 views

Train detector : 300 images with 30 objects or 9000 images with one?

so I have this dataset of images of people sitting in a restaurant. I've annotated about 300 images with an average of 30 instances of "person" per image. Now I'm wondering if I should have annotated ...
2
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0answers
38 views

Difference between retraining on different portions of data and training initially on larger data set

I have a large data set that doesn't fit in memory and would have to use something like Keras's model.fit_generator if I would like to train the model on all of the ...
2
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0answers
29 views

What methods are there to generate artificial training examples based on existing training examples?

I have a small dataset (117 training examples) and many features (4005). Each of the training examples is binary labeled (healthy / diseased). Each feature represents the connectivity between two ...
2
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3answers
118 views

Extracting algebraic constraints from the input data

I would appreciate your help with this (naive) question of mine. Given the set of points located on a circle, $x_{i}, y_{i}$ as the input data, Can a deep/machine learning algorithm infer that radius ...
2
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0answers
65 views

Regarding L0 sparsification of DNNs proposed by Louizos, Kingma and Welling

I am reading the paper on $\ell_0$ regularization of DNNs by Louizos, Welling and Kingma (2017) (Link to arxiv). In Section 2.1 the authors define the cost function as follows: $$ \mathcal{R}\left( \...
2
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0answers
67 views

Sentence classification and named identity detection with automatic retraining

I am learning AI and trying out my first real-life AI application. What I am trying to do is taking as an input various sentences, and then classifying the sentences into one of X number of categories ...
2
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0answers
40 views

What methods are there to detect discrimination in trained models?

I've been researching AI regulation and compliance (see my related question on law.stackexchange), and one of the big take-aways that I had is that the regulations that apply to a human will apply to ...
2
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0answers
104 views

Performance Evaluation Metrics used in Training, Validation and Testing

Which specific performance evaluation metrics are used in training, validation and testing and why? I am thinking error metrics (RMSE, MAE, MSE) are used in validation, and testing should use a wide ...
2
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0answers
43 views

Shifting training data

I want to create a neural network and train it on some data, however I want to be able to create a new model without retraining it from the start. An example, I have 1000 data points in my training ...
2
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0answers
106 views

Classification Learning - Normalization of time series and live usage

UPDATE: The tables look messed up so i put them on pastebin for better visibility. https://pastebin.com/gDX28uVF I am using Neural Network with different learning types (for example Standard ...
2
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0answers
75 views

How would I implement this New Type of NN

CIO NN CIO NN stands for Controller Input Output Nerual Network note due to a typo the "nearon" means "neron" For this we have to redefine the Nearon 2 Inputs 2 Outputs 4 Weights (each input and ...
2
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0answers
46 views

Recommendations on which architecture to use to guess appointment

I'm currently developping an application which allows psychologists to manage their schedule and budget. As a proof of concept, I would like to create an intelligent appointment service. There can be ...
2
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0answers
109 views

Train, Validation and Test Split for Reporting Accuracy of Neural Model and BOW

I need to report accuracies of my neural model in a conference paper as compared to various baselines. What are the accepted standards for reporting accuracies in a fair manner? Neural Model: To be ...
2
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0answers
536 views

3D - CNN. Why my cost function decreases, but the accuracy does not increase?

I'm implementing a C3D-inspired neural network for human emotion recognition, the problem I'm facing is that altough the cost function is decreasing, for both training and validation sets, I do not ...
1
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1answer
28 views

Why do we also need to normalize the action's values on continuous action spaces?

I was reading here tips & tricks for training in DRL and I noticed the following: always normalize your observation space when you can, i.e., when you know the boundaries normalize your ...
1
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0answers
26 views

Confidence Interval around prediction with bootstrapping

I want to generate a confidence interval around my prediction (vector) $\hat{y}$. I have implemented the following procedure. However, I am not sure whether this makes sense in a statistical way: I ...
1
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0answers
18 views

Why does this tutorial on reinforced learning not check whether the environment is 'game over' during training?

I am following the tutorial Train a Deep Q Network with TF-Agents. It uses the hello world environment of reinforced learning: cart pole. At the end, the agent is ...
1
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3answers
84 views

How to improve neural network training against a large data set of points with varying magnitude

I am currently using TensorFlow and have simply been trying to train a neural network directly against a large continuous data set, e.g. $y = [0.014, 1.545, 10.232, 0.948, ...]$ corresponding to ...
1
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0answers
24 views

How to make binary neural networks resilient to flipped activation values?

Assume I am given a binary neural network where the activation values are constrained to be 0 or 1 (by clipping the ReLU function). Additionally, assume the neural network is supposed to work in a ...
1
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0answers
36 views

Can AI be trained to create social media post?

I am trying to conduct an experiment for fun to see if AI could be trained to create "good" social media post. I pulled examples of 1,000s "good" social media post from Facebook. Can someone point ...
1
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0answers
29 views

How to reduce fluctuation of a neural network?

I've modeled an AlexNet neural network, with 50 epochs and a batch size of 64. I used a stochastic gradient descent optimizer with a learning rate of 0.01. I attached the train and validation loss and ...
1
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0answers
9 views

Multi user DL trainings: VMs VS Multi-seat configuration

For a project of Deep Learning for Detection algorithm (for e.g., improving YOLO) implying 4 users using the same hardware, is it more efficient to set the environment as each user has his own session ...
1
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0answers
21 views

Steps to train and re-train a good model

I'm still a bit new to deep learning. What I'm still struggling, is what is the best practice in re-training a good model over time? I've trained a deep model for my binary classification problem (...
1
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0answers
25 views

What is the use of concatenate layer in CNN?

I am not asking what does concatenate layer does in general in point of mathematical operation. But at feature level, what significance does it provide. Does it helps removing false negatives or does ...
1
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0answers
18 views

Training dataset for convolutional neural network classification - will images captured on the ground be useful for training aerial imagery?

I am an agronomy graduate student looking to classify crops from weeds using convolutional neural networks (CNNs). The basic idea that I am wanting to get into involves separating crops from weeds ...