# Questions tagged [optimization]

For questions about implementing and improving optimization algorithms used in creating AI programs, or optimization in general.

47 questions with no upvoted or accepted answers
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### How to use MOPSO to align characters vertically?

I need to efficiently align characters vertically using Multi Objective PSO. Alignment is achieved by adding spaces in between a given set of characters. ...
60 views

### How does SGD escape local minima?

SGD is able to jump out of local minima that would otherwise trap BGD I don't really understand the above statement. Could someone please provide a mathematical explanation for why SGD (Stochastic ...
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### Does Retina-net's focal loss accomplish its goal?

Taking out the weighting factor we can define focal loss as $$FL(p) = -(1-p)^\gamma log(p)$$ Where $p$ is the target probability. The idea being that single stage object detectors have a huge ...
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### How are the lower and upper bound values of the moths determined in the Moth-Flame Optimization algorithm?

I am currently implementing the Moth-Flame Optimization (MFO) Algorithm, based on the paper: Moth-Flame Optimization Algorithm: A Novel Nature-inspired Heuristic Paradigm. To calculate the values of ...
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### When training a CNN, what are the hyperparameters to tune first?

I am training a convolutional neural network for object detection. Apart from the learning rate, what are the other hyperparameters that I should tune? And in what order of importance? Besides, I read ...
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### Is logistic regression used for unconstrained or constrained optimisation problems?

Is logistic regression used for unconstrained or constrained optimization problems, and why?
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### How can I assign agents to tasks based on time and affinity?

I am working on an assignment problem. Consider $K$ agents $A_1, \dots A_K$ and $N$ tasks $T_1, \dots T_N$. Each task has a certain time $t(T_i)$ to be completed and each agent has a matching (or ...
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### Is a neural network the correct approach to optimising a fitness function in a genetic algorithm?

I've written an application to help players pick the optimal heroes during the draft phase of the Heroes of the Storm MOBA. It can be daunting to pick from 80+ characters that have synergies/counters ...
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### Is a very powerful oracle sufficient to trigger the AI singularity?

Lets say we have a oracle $S$ that, given any function $F$ and desired output $y$, can find an input $x$ that causes $F$ to output $y$ if it exists, or otherwise returns nil. I.e.: S(F, y) = x \...
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### Which features and algorithm could optimize this air-conditioner problem?

Imagine we have 2 air conditioner systems (AA) and 2 "free cooling" systems which mix external and internal air (FC) in a closed box which always tends to warm up. For each system, we have to find ...
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### Knapsack of mixture with constraints

I'm trying to find the optimized mixture for a specific set of substances. Each of those substances have characteristics that I want to optimize in the mixture (some characteristics I want to minimize ...
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### Root finding in Deep Equilibrium Models

In the Deep Equilibrium Model the neural network can be seen as "infinitely deep". Training learns a nonlinear function as usual. But there is no forward propagation of input data through ...
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### Why scaling down the parameter many times during training will help the learning speed be the same for all weights in Progressive GAN?

The title is one of the special things in Progressive GAN, a paper of the NVIDIA team. By using this method, they introduced that Our approach ensures that the dynamic range, and thus the learning ...
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### Why does Simulated Annealing not take worse solution if the Energy Difference becomes higher?

In Simualated Annealing a worse solution is accepted with this probability: $p=e^{-\frac{E(y)-E(x)}{kT}}$. If that understanding is correct: Why is this probability function used? Because it means ...
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### Which method of tree searching should be used for this board game?

Suppose the following properties of a board game: High branching factor in the beginning of the game (~500) which slowly tends towards 0 at the end of the game Evaluation of the any given board ...
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### Continuous state and continuous action Markov decision process time complexity estimate: backward induction VS policy gradient method (RL)

Model Description: Model based(assume known of the entire model) Markov decision process. Time($t$): Finite horizon discrete time with discounting factor State($x_t$): Continuous multi-dimensional ...
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### How many training runs are needed to obtain a credible value for performance?

I'm trying to optimize a neural network. For that, I'm changing parameters like the batch size, learning rate, weight initialization, etc. A neural network is not a deterministic algorithm, so, in ...
43 views

### Simplifying Log Loss

I am reading through a paper (https://www.mitpressjournals.org/doi/pdf/10.1162/0891201053630273) where they describe logloss as a ranking function and can be simplified to the margin of the training ...
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### How to improve neural network training against a large data set of points with varying magnitude

I am currently using TensorFlow and have simply been trying to train a neural network directly against a large continuous data set, e.g. $y = [0.014, 1.545, 10.232, 0.948, ...]$ corresponding to ...
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### Are there optimizers that schedule their learning rate, momentum etc. autonomously?

I'm aware there are some optimizer such as Adam that adjust the learning rate for each dimension during training. However, afaik, the maximum learning rate they can have is still determined by the ...
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### Optimizer effects on neural network with two outputs

I'm confused about the following issue. Let assume that we have a neural network that takes one input and two outputs. I try to visualize my model like as follows: ...
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### Imposing contraints on sequence of image classifications

Are there example implementations of networks that apply constraints across sequences of image classifications where class labels are ordinal numbers? For example, to cause the output of a CNN to ...
109 views

### How does the automated temperature adjustment step work in Soft Actor-Critic?

In section 5 of the paper Soft Actor-Critic Algorithms and Applications, it is proposed an optimization problem to obtain an optimal temperature parameter $\alpha^*_t$. First, one uses the original ...
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### Is convergence to a local minima more likely with transfer learning?

While doing transfer learning where my two problems are face-generation and car-generation is it likely that, if I use the weights of one problem as the initialization of the weights for the other ...
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### Could the Jensen-Shannon divergence and Kullback-Leibler divergence be used as loss functions of non-generation problems?

If I understand correctly, the KL divergence is a measure of information loss between a ground truth distribution $P$ and a predicted distribution $Q$, and the Jensen-Shannon divergence is the mean of ...
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### How can I model this problem of delivering assets by choosing a route with reinforcement learning?

I would like to build a model based on reinforcement learning (RL) for the following scenario Recommend the best route (of cities listed for a given country) that satisfies the required criteria (...
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### Which of these two strategies is the best to select solutions in simulated annealing?

I am using simulated annealing (SA) for an NP-hard combinatorial optimisation problem. 1) I am testing over a range of problem instances in which the objective values can be in the 100's or in the ...
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### What are swarm optimization techniques used for: training the ANN by weight optimization or for feature selection?

Swarm intelligence (SI) is the collective behavior of decentralized, self-organized systems, natural or artificial. The concept is employed in work on artificial intelligence. SI-based algorithms, ...
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### Can neural networks handle redundant inputs?

I have a fully connected neural network with the following number of neurons in each layer [4, 20, 20, 20, ..., 1]. I am using TensorFlow and the 4 real-valued ...