Questions tagged [training]

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

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30 views

How to have closer validation loss and training loss in training a CNN

I am using an AlexNet architecture as my Convolutional Neural Network. A learning rate of 0.00007 and 128 batch_size. I have 20000 data and 10% test, 40% validation, and 50% for training. I used 100 ...
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8 views

How long will it take to train SSD V1 Mobilenet image recognition algorithm?

I am training a deep learning algorithm using an NVIDIA GEFORCE RTX GPU, with 16 GB RAM. I went through my image database and generated 50,000 training samples with the Labelimg software; the images ...
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1answer
63 views

Why does the training time of SVMs dramatically decrease after applying dimensionality reduction to the features?

Training an SVM with an RBF kernel model with c = 5.5 and gamma = 1.06, for a 5-class classification problem on the NSL-KDD ...
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2answers
42 views

What is the right way to train a generator in a GAN?

I am not fully understanding how to train a GAN's generator. I have a few questions below, but let me first describe what I am doing. I am using the MNIST dataset. I generate a batch of random images ...
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1answer
33 views

Training while predicting on dataset

I have been trying to figure out whether if I train a model and then while predicting is it possible to train images too just like humans Somehow converting valid images to the dataset by asking us ...
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15 views

Role of autoencoder in Hierarchical Extreme Learning Machine

I want to build HELM neural network that consists of autoencoder (AE) and one class classification (OC). HELM with AE and OC have following shape: That is, hidden layer output of AE is input of OC. ...
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1answer
40 views

How does back-propagation through time work for optimizing the weights of a bi-directional RNN?

I am aware that back-propagation through time is used for training the recurrent neural network. But I am not able to understand how this happens for the bi-directional versions of the recurrent ...
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1answer
26 views

How to train the NN of simple agents given a reward system?

I'm not an expert in AI or NN, I gathered most of the information I have from the internet, and I'm looking for advice and guidance. I'm trying to design a NN that is going to be used by all the ...
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1answer
17 views

Is training a CNN object detector on an image containing multiple targets that are not all annotated will teach it to miss targets?

I want to train a convolutional neural network for object detection (say YOLO) to detect faces. Consider this image: In this training image, I have many people, but only 2 of them are annotated. Is ...
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29 views

CNN validation decreased and then fluctuated forever

I'm working on learning CNN. The problem I encountered was to reduce the amount of validation loss to a number of epochs and then a lot of fluctuation around the error of 0.1. Then the error and ...
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2answers
39 views

Is stable learning preferable to jumps in accuracy/loss

A stable/smooth learning validation curve often seems to keep improving over more epochs than an unstable learning curve. My intuition is that dropping the learning rate and increasing the patience of ...
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24 views

Training a CNN for semantic segmentation of large 4600x4600px images

I am trying to implement a CNN (U-Net) for semantic segmentation of similar large grayscale ~4600x4600px medical images. The area I want to segment is the empty space (gap) between a round object in ...
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25 views

Why scaling down the parameter many times during training will help the learning speed be the same for all weights in Progressive GAN?

The title is one of the special things in Progressive GAN, a paper of the NVIDIA team. By using this method, they introduced that Our approach ensures that the dynamic range, and thus the learning ...
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21 views

How do I split test and train data in gait recognition(or Face recognition)?

I am trying to implement gait recognition with Keras, I have a Gait-dataset and I was wondering how I would be able to handling and split the data frame into two samples (80%-20%) for training and ...
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27 views

What is the time complexity for training a single-hidden layer auto-encoder?

What is the time complexity for training a single-hidden layer auto-encoder, for 1 epoch? You can assume that there are $n$ training examples, $m$ features, and $k$ neurons in the hidden layer, and ...
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1answer
32 views

Does it make sense to train images (for object detection algorithms) with cameras that will not be used to collect future data?

I am training an algorithm to identify weeds within crops using the YOLOv5 algorithm. This algorithm will be used in the future to identify weeds in images collected by unmanned aircraft (drones) ...
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1answer
59 views

What are some examples of functions that machine learning models compute?

My simple understanding of AI is that it is based on a mathematical model of a problem. If I understood correctly, the model is a polynomial equation and its weights are calculated by training the ...
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39 views

Is continuous learning possible for a deep neural network (without changing its topology)?

Is continuous learning possible for a deep neural network? Is it possible without fundamentally changing the network topology? This is a theoretical question. I have a trained network for which the ...
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2answers
75 views

How to calculate the GPU memory need to run a deep learning network?

In general, how do I calculate the GPU memory need to run a deep learning network? I'm asking this question because my training for some network configuration is getting out of memory. If the ...
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2answers
63 views

How can I be sure that the final model, trained on all data, is correct?

The 'by the book' method of delivering final machine learning models is to include all data in the final training (including validation and test sets). To check robustness of my model I use randomly ...
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25 views

Select training data for episodic reinforcement learning (stock trading agent)

I playing around with a stock trading agent trained via (deep) reinforcement learning, including memory replay. The agent is trained for 1000 episodes, where each episodes consists of 180 timesteps (e....
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0answers
12 views

Understanding graphs of the mean square error: relationships between val loss and train loss

I am currently working with some models aimed at predicting time series (89 days for training, 22 for testing), including a CNN LSTM and a convLSTM. When training these models, I had the following ...
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29 views

What would happen if validation set was the same as the training set?

Just to check if everything is working properly in my neural net, I set my validation data to be the same as my training data, expecting to achieve a better NRMS for validation data (since it uses ...
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1answer
32 views

How to input dataset with multi-value properties?

I'm trying to learn to use AI, and so I've followed some basic tutorials like training an MLP to predict the price of a car given properties like its age and manufacturer. Now I want to see if I can ...
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2answers
49 views

How to handle images that don’t pertain to image classifier at all?

I am trying to create a CNN model that classifies if a person is wearing a seatbelt or not to verify they drive safely. I know to get images of people wearing seatbelts and people not wearing ...
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1answer
58 views

How to predict the “word” based on the meaning in a document?

What I mean to say is For example, if I give the meaning of Apple from the dictionary as input to the program, it should give output as Apple. Or I say My day to day job involves monitoring and ...
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60 views

Is there a way to reduce the RMSE error when training a neural network to recognise MNIST digits using ANFIS?

I wanted to build a digit recognition neural network using MATLAB ANFIS kit. I started by using the MNIST database and I figured out it's almost impossible to classify 784 dimension data using ANFIS. ...
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60 views

How large should the corpus be to optimally retrain the GPT-2 model?

I just started working with the GPT-2 models and want to retrain one on a pretty narrow topic, so I have problems finding training material. How large should the corpus be to optimally retrain the GPT-...
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41 views

How can I build a deep reinforcement learning model that can be trained with multiple time series datasets

I built a DRL model to trade stocks in the financial market but the number of observations is relatively small and I would like to increase it by training the same model with stocks from several ...
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1answer
54 views

How are training hyperparameters determined for large models?

When training relatively small DL model which takes several hours to train, I typically start with some starting points from literature and then use trial-and-error or grid-search approach to tune up ...
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2answers
73 views

How can I predict the true label for data with incomplete features based on the trained model with data with more features?

Suppose I have a model that was trained with a dataset that contains the features (f1, f2, f3, f4, f5, f6). However, my test dataset does not contain all features ...
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80 views

Forcing a neural network to be close to a previous model - Regularization through given model

I'm wondering, has anyone seen any paper where one trains a network but biases it to produce similar outputs to a given model (such as one given from expert opinion or it being a previously trained ...
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1answer
92 views

Why can't we train neural networks in a peer-to-peer manner?

I have recently been exposed to the concept of decentralized applications, I know that neural networks require a lot of parallel computing infra for training. What are the technical difficulties one ...
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1answer
71 views

What is the purpose of a Neural Network in Reinforcement Learning when we have a Q-learning update rule?

I'm confused as to the purpose of training a neural network (NN) for reinforcement learning (RL) tasks such as Gridworld. In RL tasks, namely q-learning, we have a q-learning update rule, which is ...
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37 views

What is the amount of test data needed to evaluate a CNN?

I have an image dataset of about 400 images. 70% of these data points were used for training, 15% for validation, and 15% for testing. I am using the 70% to train a CNN-based binary classifier. I ...
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41 views

Why is it that having a duplicate in features set makes training to work bad

I'm defining a deep network to emulate a multitarget regression. When I costruct my training set, I take information from a graph; without going into too much detail, it could happen that I take 2 ...
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58 views

Finding the 'ultimate resolution' of an ANN

I want to use a neural network to predict the refractive index of a solution. My thinking is, instead of immediately training on many samples, I will first find the 'ultimate resolution' of the ...
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33 views

Isn't it true that using max over a softmax will be much slower because there is not a smooth gradient?

Isn't it true that using max over a softmax will be much slower because there is not a smooth gradient? Max basically zeros out the gradients of all the non-maximum values. Especially at the beginning ...
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0answers
39 views

Is it necessary to label the background when generating the labelled dataset for semantic segmentation?

When I label images for semantic segmentation (using u-net, if that matters), is labeling the background (anything I am not interested in) necessary? Will it improve the network's performance?
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1answer
45 views

How should we interpret all the different metrics in reinforcement learning?

I'm trying to train some deep RL agents using policy gradient methods like AC and PPO. While training, I have a ton of different metrics being monitored. I understand that the ultimate goal is to ...
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34 views

Where can I find a training text for some specific intents in English?

Where can I find a training text for some specific intents in English? For example, the intent of asking for an appointment, or asking for contact info exchange? Is there any recommended source of ...
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1answer
30 views

How to manually collect rectangular training data samples from images?

I want to collect training samples from images. That can mean different things depending on the context. I think of the simplest case, which should be most commonly required. Because it is so common, ...
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0answers
23 views

Algorithm to train a neural network against differentiable and non-differentiable databases?

Let's say I have two databases, $(\mathbf{x_i}, \mathbf{\hat{p_i}})$ and $(\mathbf{x_j}, \mathbf{\hat{q_j}})$. A neural network with weights $\theta$ can receive an input $\mathbf{x}$ and produce an ...
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1answer
43 views

Intuitively, why can the training of a neural network be formulated as a probability estimation problem?

Neural network training problems are oftentimes formulated as probability estimation problems (such as autoregressive models). How does one intuitively understand this idea?
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2answers
46 views

How to combine several chatbots into one?

I'm in the middle of a project in which I want to generate a TV series script (characters answering to each other, scene by scene) using SOTA models, and I need some guidance to simplify my ...
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1answer
28 views

How to split data into training validation and test set when the number of data in classes varies greatly?

I have 5 classes of pictures to classify: 0 -> ~3 200 (~800 initial number before interference and duplication) 1 -> ~9 000 (I reduced from ~90 000) 2 -> ~8 000 3 -> ~3 000 4 -> ~7 200 How to ...
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42 views

What are the training and optimization technique to train GPT-2 with 1.5B parameters?

I am able to train 345M parameter GPT-2 using DialoGPT on Reddit data topics like AskReddit, Askmen, AskWomen, casualConvo, etc. And I using AWS p3dn.24xlarge instance with 256GB GPU. It is trained ...
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0answers
35 views

How many training runs are needed to obtain a credible value for performance?

I'm trying to optimize a neural network. For that, I'm changing parameters like the batch size, learning rate, weight initialization, etc. A neural network is not a deterministic algorithm, so, in ...
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2answers
63 views

What kind of problems cannot be solved using machine learning techniques?

For the problems that can be solved algorithmically. We have very good formal literature for which problems can be solved in polynomial, exponential time and which cannot. P/NP/NP-hard But do we ...
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2answers
52 views

What does it mean to train a model?

We hear this many time for different problems Train a model to solve this problem! What do we really mean by training a model?

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