Questions tagged [weight-initialization]

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Does training of neural networks follow the same order in each epoch?

Each epoch uses the weight from the end of the previous epoch(correct me if I am wrong). Is the updating of parameters after each batch always in the same order? To rephrase, are the batches always in ...
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1answer
21 views

Why don't different output weights break symmetry?

My deep learning lecturer told us that if a hidden node has identical input weights to another, then the weights will remain the same over the training/there will be no separation. This is confusing ...
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1answer
19 views

Weight-initialisation and model instability

Trying to calibrate a relatively vanilla NN, setting the hyper-parameter tuning aside*, it appears that weight initialisation has a lot of impact on the model output. Ie. Models calibrated with ...
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8 views

Neural network - calibration strategy & cross-validation

I have a hard time articulating the different parts of a calibration process of a relatively vanilla neural network. I am mostly concerned with : Grid search for the regularisation hyperparameter ...
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2answers
26 views

What is wrong with a neural network model which is so dependent on the seed of initialization?

I have a fully-connected neural network with one hidden layer with 2 units which its goal is to classify a dataset with 324 samples and 300 features. 50% of the dataset is used for train and 50% of it ...
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18 views

Debugging VGG16 Convergence Issues: Effect of Image Normalization and Weight Initialization

I've implemented VGG16 in Keras with 2 output classes for the Kaggle 'dogs v. cats' dataset as a learning exercise. I'm trying to understand the training behavior that I'm seeing. For all my tests, I ...
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17 views

If input data to CNN is not normalised, how should I initialise the weights?

I've read that He normalisation is preferred for Relu activated CNN's. However, understanding how Relu's work by linearly activating positive inputs while zero or negative inputs are zero'd (with no ...
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22 views

Is the hyperbolic tangent function a solution to the weight clipping problem of WGAN?

Instead of clipping to the range [-c,c] why not smoothly map into the range [-c,c] by using c*tanh(w) ? This would guarantee the Lipschizt constant is no greater than c. The problem I am talking ...
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1answer
24 views

Should weight distribution change more when fine-tuning transformers-based classifier?

I'm using pre-trained DistilBERT model from Huggingface with custom classification head, which is almost the same as in the reference implementation: ...
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0answers
11 views

How to make sure that the learned weights are initialized instead of only layer structure?

I have trained a model for 100 epochs. The network is designed to save checkpoints after every 10th epoch. Besides this, once the training finished I saved the model using these commands: ...
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2answers
305 views

Compare Coefficients of Different Regression Models

in my project, I am using asuite of shallow and deep learning models in order to see which has the best performance on my data. However, in the pool of shallow machine learning models, I want to be ...
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1answer
333 views

Is it wrong to use Glorot Initialization with ReLu Activation?

I'm reading that keras' default initialization is glorot_uniform. However, all of the tutorials I see are using relu ...
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0answers
42 views

How could we use a neuron instead of 100 neurons in 0.01 standard Weight initialization

Many books explain that we don't need to use 100 neurons and just can use a neuron if all result values(sigmoid(Wx)) are same at each of hidden layers. but, I don't know that we can just use a ...
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35 views

Cold-start problem in Real Time Bidding

I'm currently on the reading stage of the deployment of an RTB system. I've seen the problem of a cold start (having no initial guess of how to bid) in several papers, but I haven't really seen it be ...
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22 views

What does Keras Initializers assume about the datasets distribution?

I have a dataset that consists of 9000 Synthetic Aperture Radar images normalized to [0,1]. One of them is visualized in the histogram below. All of the images follow the same structure where most of ...
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1answer
18 views

Why is the variance going down so much in this weight initialization problem(using pytorch)?

first look at this example >>> x = t.randn(512) >>> w = t.randn(512, 500000) >>> (x @ w).var() tensor(513.9548) it makes sense that ...
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1answer
18 views

Same probability for all classes

I implemented a fully connected MLP of shape [783 (input), 128 (hidden layer) and 10 (output)] the hidden layer had a sigmoid activation function and the output a sofmax. I tested with the dataset of ...
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1answer
36 views

How can I have the same initialization for all my networks?

I want to have the same weights for layer initializations in all my networks, so that when I'm comparing their first epoch loss they all start from the same value. Is there a way in keras to do this? ...
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0answers
49 views

A model that only works by setting all initial weights to zero

In this model from MusicNet, they set the initial weights of their neural network to all zeros. ...
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3answers
248 views

weight training speed too slow in CNNs

I'm writing my own CNN code from scratch. Though I got fast, converged and satisfactory results, the trained weights change very little in value (while cost/loss function drops in time rapidly in a ...
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1answer
66 views

How large of a value should a weight have in a neural network?

If you're assigning random values to the weights in a neural network before back-propagation, is there a certain maximum or minimum value for each weight ( for example, 0 < w < 1000 ) or can ...
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1answer
88 views

Weights initialization in Neural Network

I was viewing code for custom neural network for sentiment analysis. It had 3 layers (1 hidden layer). I am more concerned with weight initialization for the layers ...
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2answers
156 views

C++ return array from function

I would like to implement machine learning algorithm in C++ without using any C++ machine learning library. So I'm writing this initializer function for generating zero matrices but can't figure out ...
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0answers
33 views

What are the reasons for drawing initial neural network weights from a Gaussian?

Are there theoretical or empirical reasons for drawing initial weights of a multilayer perceptron from a Gaussian rather than from, say, a Cauchy distribution?
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2answers
6k views

what is difference between the DDQN and DQN?

I think I did not understand what is the difference between DQN and DDQN in implementation. I understand that we change the traget network during the running of DDQN but I do not understand how it is ...
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2answers
4k views

What are the cases where it is fine to initialize all weights to zero

I've taken a few online courses in machine learning, and in general, the advice has been to choose random weights for a neural network to ensure that your neurons don't all learn the same thing, ...