# Questions tagged [convergence]

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### What are desirable properties of layers in Deep Learning?

I have been thinking about the following the problem: Given some task we assume there is a magical function that perfectly solve this task. For example, if we want to distinguish cats and dogs, then ...
18 views

### Is learning_rate linear with the time to converge using AdamOpt?

Say that both learning rates 1e-3,1e-4 leading to the same solution (not too high or too small). In terms of convergence by the amount of epochs, does ...
29 views

### Convergence of Sarsa($\lambda$)

Is there any theorem on the convergence of the Sarsa($\lambda$) Algorithm? I am currently working through the theory of Reinforcement Learning with the lecture by David Silver and the book of Sutton &...
13 views

### RL agent behave differently for different data

I am training an RL model using PPO for AAPL stock. There are 3 actions to take, Buy, Sell or Hold. If there is a Buy(/Sell) signal, the environment will buy(/sell) all. To trade for each year, the ...
9 views

### what does it mean when my accuracy converges asymptotically?

I am training a CNN using keras. My accuracy hits 70% quickly enough, then starts converging asymptotically to about 80%. What is this a symptom of? With a normal stack-o-Dense layers, I have ...
455 views

### What exactly is convergence rate referring to in machine learning?

My understanding of the term "Convergence Rate" is as follows: Rate at which maximum/Minimum of a function is reached, so in logistic regression rate at which gradient decent reaches global ...
28 views

### What is going on with this kind of validation loss graph?

I am using stock prices and a whole bunch of indicators values to try to get a tensorflow model to predict to buy,sell, or hold. I think im going about this right but when i train the model, first i ...
65 views

### Rate of convergence - comparison of supervised ML methods

I am working on a project with sparse labelled datasets, and am looking for references regarding the rate of convergence of different supervised ML techniques with respect to dataset size. I know that ...
157 views

### Does convergence equal learning in Deep Q-learning?

In my current research project I'm using the Deep Q-learning algorithm. The setup is as follows: I'm training the model (using Deep Q-learning) on a static dataset made up of experiences extracted ...
1 vote
353 views

### Do smaller neural nets always converge faster than larger ones?

In your experience, do smaller CNN models (fewer params) converge faster than larger models? I would think yes, naturally, because there are fewer parameters to optimize. However, I am training a a ...
24 views

### Force Matching in Coarse Grained Molecular Dynamics with Jax - Forces do not match when neglecting energy loss

I am currently exploring force matching approaches for molecular dynamic simulations. As I am still in an exploration state, I'd tried investigated Force Matching Neural Network Colab Notebook ...
77 views

### ElasticNet Convergence odd behavior

I am optimizing a model using ElasticNet, but am getting some odd behavior. When I set the tolerance hyperparameter with a small value, I get ...
1 vote
36 views

### Uniform convergence garantee on sample complexity

I can't understand why the Uniform Convergence guarantees an upper bound and not a lower bound on sample complexity as stated on  Corollary 4.4. If a class $H$ has the uniform convergence property ...
11k views

### Logistic regression does cannot converge without poor model performance

I have a multi-class classification logistic regression model. Using a very basic sklearn pipeline I am taking in cleansed text descriptions of an object and classifying said object into a category. <...
253 views

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### need explanation on how an equation is being converted to cvxopt logic in solver.lq

This is the equation that is given in the example: and the code to replicate it in python is ...
10k views

### Is the percepetron algorithm's convergence dependent on the linearity of the data?

Does the fact that I have linearly separable data or not impact the convergence of the perceptron algorithm? Is it always gonna converge if the data is linearly separable and not if it is not ? Is ...