Newest 'convergence' Questions

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votes

1answer

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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 ...

asked May 11 at 7:01

haneulkim

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Speed up convergence of GLM fitting in custom GLM code (using GD)

So, I've got a little bit of an unusual situation. I do ML on encrypted data, and the ecosystem there is relatively young, so I have to build my own infrastructure, and there are certain restrictions ...

machine-learning regression statistics convergence glm

asked Mar 25 at 18:41

Ian Q

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23 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 ...

tensorflow loss-function learning-rate convergence

asked Mar 11 at 1:40

JRowan

101

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votes

1answer

43 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 ...

machine-learning supervised-learning reference-request convergence

asked Feb 24 at 13:52

Avatrin

1215 bronze badges

2

votes

1answer

67 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 ...

deep-learning reinforcement-learning q-learning convergence generalization

asked Feb 21 at 16:00

Aeryan

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vote

2answers

89 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 ...

neural-network training convergence convolutional-neural-network

asked Dec 8 '20 at 8:29

Sid

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3

votes

0answers

21 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 ...

machine-learning neural-network convergence graph-neural-network

asked Oct 21 '20 at 16:16

not_converging

314 bronze badges

1

vote

1answer

33 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 ...

predictive-modeling cross-validation convergence elastic-net

asked Aug 24 '20 at 5:59

mr_python

111 bronze badge

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vote

0answers

29 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 [1] Corollary 4.4. If a class $H$ has the uniform convergence property ...

machine-learning sampling convergence

asked Aug 5 '20 at 8:39

Enrico R.

111 bronze badge

2

votes

2answers

6k 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. <...

scikit-learn logistic-regression multiclass-classification convergence

asked Jul 16 '20 at 14:55

jasper

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votes

1answer

160 views

How do i iterate functions until convergence in R?

I am looking to iterate until convergence but I am not sure how i should code it. A simple similar example is something like $X_0=5 , Y_0=3$ for $n=1,2..$ $P_n=X_{n-1}-Y_{n-1}$ $Y_n=3P_n$ $X_n=P_n+...

r statistics convergence

asked Jul 11 '20 at 19:52

John_cena123123

11 bronze badge

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votes

2answers

72 views

How to assess that a cross entropy based model has converged

I have a question regarding cross entropy convergence using Stochastic Gradient Descent. I am a little bit confused about how the convergence should be assessed. Should we treat the model as converged ...

cnn loss-function convergence

asked Dec 30 '19 at 11:28

Jim

1252 bronze badges

1

vote

1answer

38 views

Why GA convergence curves continue as two parallel lines?

I'm working on a optimization problem and using GA algorithm (in MATLAB, ga function). As you know MATLAB plots GA result with two curves, one for the best values and other to show the mean values ...

matlab genetic-algorithms convergence genetic-programming

asked Nov 24 '19 at 12:44

motevalizadeh

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2

votes

0answers

23 views

Is there a universal convergence rate when stacking models/experts?

It's fairly common to see people stacking different models when chasing marginal gains in contexts such as Kaggle competitions or the Netflix challenge. I would like to know about the mathematics ...

ensemble-modeling mathematics convergence

asked Nov 18 '19 at 17:05

Learning is a mess

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2

votes

1answer

43 views

How can we conclude that an optimization algorithm is better than another one

When we test a new optimization algorithm, what the process that we need to do?For example, do we need to run the algorithm several times, and pick a best performance,i.e., in terms of accuracy, f1 ...

algorithms optimization performance convergence

asked Sep 23 '19 at 1:29

user82620

211 bronze badge

1

vote

0answers

121 views

Help with MLP convergence

I posted this question on AI SE and got advised to ask here for guidance. I've been stuck for a couple of days trying to figure it out how the standard MLP works and why my code doesn't converge at ...

machine-learning algorithms mlp implementation convergence

asked Sep 7 '19 at 5:18

ivansnpmaster

112 bronze badges

0

votes

2answers

786 views

Python lifelines - ConvergenceWarning: Newton-Raphson failed to converge sufficiently in Cox prop hazard

When calling CoxPHFitter() on my full dataset I'm getting the following error: ...

machine-learning python optimization convergence survival-analysis

asked Jul 30 '19 at 8:25

Serendipity

1948 bronze badges

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vote

0answers

50 views

Huge cost not converging well with TensorFlow logistic regression

I try to use Logistic Regression for a dataset which contains 15 numeric features and 4238 rows of examples. The calculated cost started at 415.91, and converged when the cost was reduced to 220.119 ...

python tensorflow logistic-regression loss-function convergence

asked Jul 5 '19 at 21:26

user77241

2

votes

0answers

200 views

How does permutation of training data improve convergence time when training a perceptron or neural network model? [duplicate]

I'm currently studying some basic concepts regarding Deep Learning and Neural Networks with this material. When discussing the training algorithm for a perceptron, the author states that looping ...

neural-network training beginner perceptron convergence

asked Jul 5 '19 at 21:16

Nilton Junior

836 bronze badges

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votes

1answer

84 views

Can one use non converged results from Logistic Regression?

I'm running Logistic Regression on a dataset for a classification problem. I used the model on the dataset when it was normalized and I had no problem with it converging. Now, I wanted to see the ...

machine-learning classification logistic-regression convergence

asked May 13 '19 at 15:45

dungeon

1652 silver badges12 bronze badges

1

vote

0answers

454 views

sequence convergence - python

Let $\{p_i : i \in \mathbb{Z}\}$ be an i.i.d sequence with $p_i \in (0, 1)$. Fix this random environment, then consider the random walk $$P[ X_{n+1} = i + 1 | X_n = i] = 1 − P[ X_{n+1} = i − 1 | X_n =...

python convergence

asked Apr 25 '19 at 20:23

Med Qadi

111 bronze badge

2

votes

0answers

829 views

LSTM not converging

I am sorry if this questions is basic but I am quite new to NN in general. I am trying to build an LSTM to predict certain properties of a light curve (the output is 0 or 1). I build it in pytorch. ...

lstm pytorch convergence

asked Apr 4 '19 at 5:16

Bill

211 bronze badge

3

votes

1answer

754 views

DQN fails to find optimal policy

Based on DeepMind publication, I've recreated the environment and I am trying to make the DQN find and converge to an optimal policy. The task of an agent is to learn how to sustainably collect apples ...

reinforcement-learning q-learning dqn convergence deepmind

asked Apr 1 '19 at 1:23

macwiatrak

313 bronze badges

3

votes

4answers

289 views

Weights not converging while cost function has converged in neural networks

My cost/loss function drops drastically and approaches 0, which looks a sign of convergence. But the weights are still changing in a visible way, a lot faster than the cost function. Should I ensure ...

neural-network training cost-function convergence

asked Feb 18 '19 at 15:20

feynman

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vote

1answer

2k views

Recurrent Neural Network (LSTM) not converging during optimization

I am trying to train a RNN with text from wikipedia but I having having trouble getting the RNN to converge. I have tried increasing the batch size but it doesn't seem to be helping. All data is one ...

neural-network lstm rnn optimization convergence

asked Dec 26 '18 at 22:17

treutm

376 bronze badges

2

votes

1answer

1k views

Very slow convergence with CNN [closed]

I am new to deep learning. I am working on training an SSD model on a set of small objects. I am using Adam gradient descent for optimization and a large input (800x800), but I seem to only get an ...

cnn object-detection convergence

asked Dec 4 '18 at 20:53

deeprai

234 bronze badges

2

votes

1answer

4k views

Why this model does not converge in keras?

This case has an underlying story but I have essentially boiled it down to the simplest possible re-producible example I could. Essentially let us think that I have up to 1000 nodes and each node ...

python keras convergence

asked Aug 9 '18 at 17:39

Aliostad

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1

vote

0answers

639 views

Validation loss keeps fluctuating about training loss

I am training a Keras model for multi-target regression by using a custom loss function with the goal of getting predictions accurate to below 0.01 with respect to ...

deep-learning keras loss-function convergence

asked Aug 6 '18 at 22:11

a_guest

1112 bronze badges

2

votes

1answer

2k views

Convergence of vanilla or natural policy gradients (e.g. REINFORCE)

I am reading in a lot of places that policy gradients, especially vanilla and natural, are at least guaranteed to converge to a local optimum (see, e.g., pg. 2 of Policy Gradient Methods for Robotics ...

reinforcement-learning convergence

asked Jul 30 '18 at 4:55

user650261

715 bronze badges

3

votes

1answer

122 views

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 ...

python convergence

asked Jan 30 '18 at 9:53

Sourav Roy

412 bronze badges

2

votes

1answer

8k 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 ...

perceptron convergence

asked Oct 12 '17 at 18:15

astudentofmaths

2633 silver badges8 bronze badges

21

votes

2answers

7k views

local minima vs saddle points in deep learning

I heard Andrew Ng (in a video I unfortunately can't find anymore) talk about how the understanding of local minima in deep learning problems has changed in the sense that they are now regarded as less ...

machine-learning deep-learning optimization convergence

asked Sep 5 '17 at 19:14

oW_♦

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15

votes

5answers

19k views

Number of epochs in Gensim Word2Vec implementation

There's an iter parameter in the gensim Word2Vec implementation ...

gensim word2vec convergence

asked Jan 17 '16 at 13:14

alvas

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Questions tagged [convergence]

What exactly is convergence rate referring to in machine learning?

Speed up convergence of GLM fitting in custom GLM code (using GD)

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

Rate of convergence - comparison of supervised ML methods

Does convergence equal learning in Deep Q-learning?

Do smaller neural nets always converge faster than larger ones?

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

ElasticNet Convergence odd behavior

Uniform convergence garantee on sample complexity

Logistic regression does cannot converge without poor model performance

How do i iterate functions until convergence in R?

How to assess that a cross entropy based model has converged

Why GA convergence curves continue as two parallel lines?

Is there a universal convergence rate when stacking models/experts?

How can we conclude that an optimization algorithm is better than another one

Help with MLP convergence

Python lifelines - ConvergenceWarning: Newton-Raphson failed to converge sufficiently in Cox prop hazard

Huge cost not converging well with TensorFlow logistic regression

How does permutation of training data improve convergence time when training a perceptron or neural network model? [duplicate]

Can one use non converged results from Logistic Regression?

sequence convergence - python

LSTM not converging

DQN fails to find optimal policy

Weights not converging while cost function has converged in neural networks

Recurrent Neural Network (LSTM) not converging during optimization

Very slow convergence with CNN [closed]

Why this model does not converge in keras?

Validation loss keeps fluctuating about training loss

Convergence of vanilla or natural policy gradients (e.g. REINFORCE)

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

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

local minima vs saddle points in deep learning

Number of epochs in Gensim Word2Vec implementation

Hot Network Questions

Questions tagged [convergence]

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