Questions tagged [convergence]
The convergence tag has no usage guidance.
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1answer
31 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 ...
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0answers
16 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 ...
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0answers
28 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 =...
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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 ...
2
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0answers
129 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. ...
2
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1answer
125 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 ...
3
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4answers
121 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 ...
1
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1answer
561 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 ...
2
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1answer
199 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 ...
2
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1answer
1k 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 ...
2
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0answers
327 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 ...
1
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1answer
619 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 ...
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1answer
102 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
...
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1answer
3k 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 ...
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0answers
714 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^...
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2answers
3k 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 ...
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4answers
10k 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=...
