For questions surrounding gradient descent, a method for finding the optimum state of a parameterized function based on another function often called the loss or error function. It iteratively descends the loss surface to the minimum loss by adjusting parameters based on the product of the partial derivatives comprising the gradient and a learning rate.

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### Eligibility vector for softmax policy with policy gradients

There is this nice result for policy gradients that the gradient of some performance measure, $\nabla v_{\pi_{\theta}}(s_0)$ (here, in the episodic case for the starting state $s_0$ and policy $\pi$, ...
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### How to reduce variance of the model loss during training?

I know that stochastic gradient descent always gives different results. What are the best practices to reduce this variance today? I tried to predict simple function with two different approaches and ...
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### Can Grad CAM feature maps be used for Training?

I am trying to recreate the architecture of the following paper: https://arxiv.org/pdf/1807.03058.pdf Can someone help me in explaining how are the feature maps coming out of the output of GradCam ...
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### Understanding the partial derivative with respect to the weight matrix and bias

Say we have the layer $X W + b = Y$. I want to get $\frac{dL}{dW}$ and we assume I have $\frac{dL}{dY}$. So all I need is to find $\frac{dY}{dW}$. I know that it should be $X^T\frac{dL}{dY}$ but don'...
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### How to plot Loss Landscape with more than 2 weights in the network

For a single neuron with 2 weights, I can plot the loss landscape and it looks like this (OR data, sigmoid activation, MAE loss): But, when the neuron accepts more inputs, which means more than 2 ...
34 views

### Is the gradient at a layer independent of the activations of the previous layers?

Is the gradient at a layer (of a feed-forward neural network) independent of the activations of the previous layers? I read this in a paper titled Mean Field Residual Networks: On the Edge of Chaos (...
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27 views

### neuralnetworksanddeeplearning.com chapter 5 problems

For http://neuralnetworksanddeeplearning.com/chap5.html , could anyone suggest: 1) how to approach the derivation of expression (123) ? 2) what constitutes value ~ 0.45 ? 3) why the need of taylor ...
293 views

### Feed forward neural network using numpy for IRIS dataset

I tried to build a neural network for working on IRIS dataset using only numpy after reading an article (link: https://iamtrask.github.io/2015/07/12/basic-python-network/). I tried to search the ...
254 views

### SARSA won't work for linear function approximator for MountainCar-v0 in OpenAI environment. What are the possible causes?

I am learning Reinforcement Learning from the lectures from David Silver. I finished lecture 6 and went on to try SARSA with linear function approximator for MountainCar-v0 environment from OpenAI. A ...
2k views

### Can the mean squared error be negative?

I'm new to machine learning. I was watching a prof. Ng's video about gradient descent from the machine learning course. It said that we want our cost function (in this case, the mean squared error) to ...
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My understanding is that the conjugate gradient method is faster than gradient descent because it does less zig zags while descending. How come the state of the art papers I see all use gradient ...
289 views

### Deep Q-Learning: why don't we use mini-batches during experience reply?

In examples and tutorial about DQN, I've often noticed that during the experience replay (training) phase people tend to use stochastic gradient descent / online learning. (e.g. link1, link2) ...
3k views

### How do I choose the optimal batch size?

Batch size is a term used in machine learning and refers to the number of training examples utilised in one iteration. The batch size can be one of three options: batch mode: where the batch ...
720 views

### Should the weights of a neural network be updated after each example or at the end of the batch? [duplicate]

Should the weights of a neural network be updated after each example or at the end of the batch? Do I need a normalization factor in the second case?
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### Weight Normalization paper

I am trying to dissect paper about weight normalization: https://papers.nips.cc/paper/6114-weight-normalization-a-simple-reparameterization-to-accelerate-training-of-deep-neural-networks.pdf ...
89 views

### Do good approximations produce good gradients?

Let’s say I have a neural net doing classification and I’m doing stochastic gradient descent to train it. If I know that my current approximation is a decent approximation, can I conclude that my ...
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### Can non-differentiable layer be used in a neural network, if it's not learned?

For example, AFAIK pooling layer in CNN is not differentiable, but it can be used because it's not learning. Is it always true?
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### Has anyone investigated iteration awareness beyond RNN and LSTM?

This question considers the convergence of an artificial networks (MLPs, RNNs, LSTM nets, CNNs) over time or over the course of epochs made up of iterations through training examples. In this ...