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Random forests - are more estimators always better?

I'm learning about more advanced methods of hyperparameter optimization, such as the Bayesian methods in the scikit-optimize package. I noticed that in some ...
0
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1answer
7 views

Weights initialization once the Neural Network is trained (in Keras)

I am trying to understand how weights are initialized in a Neural Network using Keras deep learning framework and what happens if I train a Neural Network and then I want to train it again: are the ...
-1
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0answers
5 views

Negative rewards with Q-learning and FCN networks

I try to train a fully convolutional network (FCN) network with Q-learning that produces pushing actions similar to Zeng18. I added negative rewards in order to complete the task with minimum number ...
6
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2answers
274 views

Why are the Bellman operators contractions?

In these slides, it is written \begin{align} \left\|T^{\pi} V-T^{\pi} U\right\|_{\infty} & \leq \gamma\|V-U\|_{\infty} \tag{9} \label{9} \\ \|T V-T U\|_{\infty} & \leq \gamma\|V-U\|_{\infty} \...
4
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2answers
88 views

How do you measure multi-label classification accuracy?

Multi-label assignment is the task in machine learning to assign to each input value a set of categories from a fixed vocabulary where the categories need not be statistically independent, so ...
3
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1answer
130 views

How difficult is this sound classification?

I want a microphone to pick up sounds around me (let's say beyond a 3 foot radius), but ignore sounds made at my desk, such as the rustling of paper, clicking a mouse and typing, my hands brushing up ...
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0answers
33 views

how to prove that "w will converge to TD fixed point once A is positive definite"

In Reinforcement Learning: An Introduction edition 2 chapter 9-4, it said that when use TD(0) as target and use semi-gradient method to update In general, $w_t$ will be reduced toward zero whenever A ...
1
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1answer
31 views

Best algorithms/approaches for data sets of binary (1/0) features

I am working with a dataset with about 400 features, all binary (1 or 0). What approach would you recommend? Data set is about 500k records.
0
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1answer
51 views

What Past Approaches is the "Taylor Swift" Paper Referring To? [closed]

(My previous question regarded which theorem of probability was equation (2) referring to). This paper mentions that temporal forecasting is meant to solve an integral equation as denoted by (2) (...
1
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1answer
23 views

How to get GPT-3 to translate a specific word in a sentence?

I just gave GPT-3 the following prompt (in the playground, using text-davinci-001 with default settings): ...
0
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1answer
21 views

Why and how can the policy and value iteration methods converge to the OPTIMAL point?

I am reading Reinforcement Learning: An Introduction by Sutton & Barto. According to this textbook, as far as I understood, the authors claim that the policy and value iteration methods converge ...
5
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1answer
338 views

Multi Armed Bandits with large number of arms

I'm dealing with a (stochastic) Multi Armed Bandit (MAB) with a large number of arms. Consider a pizza machine that produces a pizza depending on an input $i$ (equivalent to an arm). The (finite) set ...
0
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1answer
34 views

Are there any algorithms (even backtracking variations) that solve the sudoku in a way more similar to this approach?

I looked a bit online for Sudoku solvers and it seems like all the answers I found involve a backtracking algorithm. However, this is not how humans (at least not me) solve Sudoku. We don't place in ...
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0answers
5 views

Has someone studied the predictive improvement of images of irises over the classic iris dataset?

The Iris dataset is a classic dataset for teaching classification or clustering algorithms. The four measurements Sepal length Sepal width Petal length Petal width give a very rough sketch of the ...
0
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0answers
21 views

How to build/train a recommendation system model with no user related data

I have a set of items with their attributes. I want to use this data to train a an open-source model that uses users-items interactions as positive preferences data. Would it be a good idea to ...
0
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0answers
5 views

Is this the correct method for how to implement a stratified K fold with grid search SVC?

I'm writing a support vector classifier for a binary class using some toy data. This is the code: ...
2
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1answer
290 views

How to train a LSTM model with multi dimensional data

I am trying to train my model using LTSM layer in Keras (python). I have some problems regarding the data representation and feeding it into the model. My data is 184 XY coodinates encoded as a numpy ...
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0answers
14 views

What should I make for my game? [closed]

I want to make a game based on what an ai tells me, but this is the only ai I can find so can you please tell me what the flipping flip I can do?!
1
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1answer
34 views

How does a VGG-based Style-Loss incorporate color information?

I've recently been reading a lot about style transfer, its applications and implications. I understand what the Gram matrix is and does. I can program it. But one thing that has been boggling me is: ...
0
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0answers
17 views

Margin of a SVM

I am pretty new to the field. So, if this is the wrong place to ask the following question, please let me know. Currently, I am trying to understand the mathematical of SMVs using the textbook '...
0
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0answers
7 views

Why is the maximal data path of RNNs $O(logk(n))$

On this video https://www.youtube.com/watch?v=OyFJWRnt_AY at about 1:07:00, complexity and maximal data path for transformers and RNNs is compared. What it says about maximal data path : The maximal ...
0
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1answer
410 views

Is the self-attention matrix softmax output (layer 1) symmetric?

Let's assume that we embedded a vector of length 49 into a matrix using 512-d embeddings. If we then multiply the matrix by its transposed version, we receive a matrix of 49 by 49, which is symmetric. ...
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0answers
5 views

Visualizing entries using backpropagation, deconvnets and guided backpropagation

I recently took a look at this paper: Striving for Simplicity: The All Convolutional Net, introducing some visualization methods to understand a neural network's classification choices. I don't ...
0
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1answer
23 views

Why are Directed Graphical Models considered ML methods?

Consider the following problem. The probability of being born in countries [1,2,3,4] is given by [a, b, c, d] respectively. This is a categorical problem. Now, assume that the height of a person ...
0
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1answer
30 views

How to understand slope of a (non-convex) function at a point in domain?

Consider the following paragraph from Numerical Computation of deep learning book that says derivative as a slope of the function curve at a point Suppose we have a function $y= f(x)$, where both $x$ ...
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0answers
13 views

How SVM model predict output on the new dataset?

I am using SVM for a binary classification problem. My model accuracy on test data is 87%. The training code is as below: ...
3
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1answer
61 views

Why should one focus on spectral operations as a computer vision researcher?

While reading about various types of mathematical operations on tensors, I encountered spectral operations for the first time. The description is as follows (p. 53 of this book) Spectral ops - ...
0
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0answers
23 views

Impact of imbalanced dataset on CNN model performance

I trained a 1D CNN model to model bacterial plate count based on time series data of water temperature. Bacterial place count is numerical, based on which I created two category variables, namely &...
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1answer
20 views

Simple Polynomial Gradient Descent algorithm not working

I am trying to implement a simple 2nd order polynomial gradient descent algorithm in Java. It is not converging and becomes unstable. How do I fix it? ...
2
votes
1answer
112 views

Is the traditional meaning of "strong AI" outmoded?

Traditionally, "strong AI" refers to Artificial General Intelligence, the human mind understood as an algorithm (Searle, Chinese Room) and Artificial Consciousness. But recent advances in Artificial ...
0
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1answer
176 views

How to do early classification of time series event with small dataset?

I would like to build a real-time binary classifier that can predict an event of interest that is occurring as soon as it starts. These are electromyographic signals, and the event classification ...
1
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0answers
26 views

Knowledge representation and reasoning(KRR) over a Image scene: Neurosymbolic AI

What are the ways and SOTA in domain of knowledge representation and reasoning over scene. Suppose there are 3 objects in the scene and which objects needs to be picked first among them is governed by ...
0
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1answer
79 views

Is it a good idea to overfit on a small part of your data for faster model convergence?

I working on a classification problem that needs to detect patterns on a time serie. Basically, there's a catch-all class that means "no pattern detected", the other are for the specific patterns. The ...
0
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2answers
45 views

Why data required for hyperparameter tuning is considered as an additional data?

Any parametric model may have parameters as well as hyperparameters. Learning algorithm deals with parameters and hyperparameters should be dealt outside learning algorithm. Consider the following ...
1
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1answer
59 views

When doing binary classification with neural networks, how can I order the importance of the features for a class?

I have a simple neural network for binary classification. The input features include age, sex, economic situation, illness, disability, etc. The output is simply 1 and 0. I would like to order the ...
0
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0answers
24 views

What kind of test verify that we have made Strong AI? [duplicate]

Let's say we invented Strong AI technology, and made robot with it, how can we proove that it is real autonomous artificial creature? We know that with only deep learning technology, it is not ...
0
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1answer
21 views

What can I infer if my model is converging extremely fast?

I am running a model with fixed hyperparameters. To my surprise/shock, the model converged extremely fast with the least loss possible. I want to know the causes of this phenomenon. I have the ...
0
votes
1answer
15 views

Why is the WMT16 dataset favoured for evaluating machine translation models?

The Workshop on Statistical Machine Translation has released translation challenges each year from 2004 on, which feature a dataset of sentence pairs in a variety of languages. Even though the ...
1
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1answer
51 views

Does the substituted variable/constant have to appear in the unified term?

I'm checking out how to manually apply resolution on a first order predicate logic knowledge base and I'm confused about what is allowed or not in the algorithm. Let's say that we have the following ...
1
vote
1answer
787 views

How to use the LSTM layer in PPO architecture?

What is the best way of using the LSTM layer in PPO architecture? Should I use them in the first layer of both actor and critic, or use them just before the final layer of these networks? Should I ...
2
votes
2answers
154 views

How to design a recommendation system for shift swapping?

I need to design an algorithm such that it handles the request for shift swapping. The algorithm will recommend a list of people who are more likely to swap that shift with the person by analyzing ...
3
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1answer
76 views

What is the stride information of an image referring here?

In convolutional neural networks, the convolution and pooling operations have a parameter known as stride, which decides the amount of jump the kernel needs to do on the input image. You can get more ...
1
vote
1answer
44 views

Why doesn't the high precision of neural network weights improve accuracy?

Consider the following paragraph from the subsubsection 3.5.2: A dtype for every occasion chapter named It starts with a tensor from the textbook titled Deep Learning with PyTorch by Eli Stevens et al....
1
vote
1answer
59 views

What does it mean "having Lipschitz continuous derivatives"?

We can enforce some constraints on functions used in deep learning in order to guarantee optimizations. You can find it in Numerical Computation of the deep learning book. In the context of deep ...
0
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0answers
21 views

When should discretization of observations be considered?

I found some literature regarding the design of action-spaces and that e.g. a discretization of continuous actions in video-game environments can be crucial for successful learning (source: https://...
2
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0answers
20 views

Minimax evaluation function for games with score instead of loss/draw/win result

I am trying to create minimax evaluation function for the Ms Pacman game. The goal of the player is to maximize score. I have some idea about the features that I would like to use in my evaluation ...
1
vote
1answer
47 views

Handling imbalanced data with multiple targets

I have the model which has 3 outputs (it is a regression task, I have the angle of the steering wheel, brake and acceleration). I can divide my values to some smaller bins and in this way I can change ...
2
votes
2answers
70 views

How to classify two very similar images using Deep Learning?

I am a newbie in Computer Vision. I have a scenario in which I have a stationary camera in a factory. I want to detect whether the technician is working on the machine or not. Images are like the ...
0
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1answer
17 views

Why does validation accuracy stop rising so soon?

I have implemented a GRU to deal with youtube comment data. I am a bit confused about why the validation score seems to even out around 70% and then keeps rising, this doesn't look like overfitting ...
0
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0answers
21 views

How to calculate the gradient (or derivative) of y = f(x) of y w.r.t x where y represents the order statistics divided by median of x?

How to calculate the gradient (or derivative) of y = f(x) of y w.r.t x where y represents the order statistics divided by median of x? For instance x is ...

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