Newest 'convergence' Questions

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votes

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23 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 ...

asked Dec 30 '19 at 11:28

Jim

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vote

1answer

21 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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15 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 convergence

asked Nov 18 '19 at 17:05

Learning is a mess

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Cross entropy loss for sigmoid function

Suppose instead of squared error loss I take cross entropy loss: $$H(y) = - \sum y' \log(y) $$ ( where y' is the actual distribution) . I read somewhere that this loss function converges faster ...

machine-learning loss-function convergence

asked Sep 24 '19 at 9:20

Sambhav Khurana

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vote

1answer

25 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

111 bronze badge

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vote

0answers

25 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 convergence

asked Sep 7 '19 at 5:18

ivansnpmaster

112 bronze badges

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2answers

215 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

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vote

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38 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

Enyang Wang

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2

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0answers

29 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

436 bronze badges

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votes

0answers

11 views

Initialisation of weights for input sensitivity

Iam trying to architect a neural network. I have 3 inputs and I require the output to be as sensitive as possible to changes in the input. The outputs are calculated using 10 hidden ReLU layers and a ...

machine-learning convergence weight-initialization

asked Jun 24 '19 at 9:38

pranav

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1answer

48 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

12510 bronze badges

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votes

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42 views

Training loss and accuracy is oscillating and failed to converge

I was using AlexNet to do dog&cat classification tasks practice: https://github.com/stephen-v/tensorflow_alexnet_classify While I run the training, the loss oscillated while decreasing, which ...

training convergence alex-net

asked May 1 '19 at 5:55

林彥良

11 bronze badge

1

vote

0answers

105 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

0

votes

0answers

4 views

What are some common sources of variance in a convolutional neural network DICE scores?

I know it's basically impossible to pinpoint the exact answer to this question without data, code, architecture, etc, but I'm curious as to if anyone has any general ideas on why this might be ...

variance convergence score

asked Apr 16 '19 at 18:30

Monica Heddneck

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2

votes

0answers

378 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

2

votes

1answer

375 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

213 bronze badges

3

votes

4answers

133 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

1k 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

461 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

233 bronze badges

2

votes

1answer

2k 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

1356 bronze badges

2

votes

0answers

496 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

1212 bronze badges

1

vote

1answer

1k 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

615 bronze badges

3

votes

1answer

112 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

311 bronze badge

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vote

1answer

4k 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

2233 silver badges8 bronze badges

0

votes

0answers

835 views

Neural Network: how to interpret this loss graph?

I have built a deep CNN with TensorFlow that does not classify on one-hot encoded vectors but probability distributions, i.e. given some input $X$ I feed a normal distribution $\mathcal{N}(\mu, \sigma^...

neural-network convnet training loss-function convergence

asked Sep 8 '17 at 23:43

daniel451

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18

votes

2answers

4k 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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13

votes

4answers

13k views

Number of epochs in Gensim Word2Vec implementation

There's an iter parameter in the gensim Word2Vec implementation class gensim.models.word2vec.Word2Vec(sentences=None, size=...

gensim word2vec convergence

asked Jan 17 '16 at 13:14

alvas

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Questions tagged [convergence]

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?

Cross entropy loss for sigmoid function

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]

Initialisation of weights for input sensitivity

Can one use non converged results from Logistic Regression?

Training loss and accuracy is oscillating and failed to converge

sequence convergence - python

What are some common sources of variance in a convolutional neural network DICE scores?

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?

Neural Network: how to interpret this loss graph?

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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