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18 views

Should I represent my reinforcement learning as an episodic or continuous task?

I would like the community to help me understand if the following example would be better represented as episodic or continuous task, this will help me structure the problem and chose the right RL ...
0
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1answer
62 views

Generating automatic sports commentary (NLG)

I am trying to develop a "simple" announcer for sports segments that mainly consists of events like goals, fouls, substitutions, and many other events that could happen in many sports. The ...
1
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0answers
21 views

Why Acme is using own uniform initializer?

Why is Acme using own initializer for both tanh and ELU, when commonly used for tanh is Xavier and for ELU is He initializer? What mathematics is behind them? Here is the code. ...
0
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1answer
13 views

Why is training all layers at a time effective for a multi-layer autoencoder?

This training of all layers of a CNN simultaneously is standard practice today. It is found in every CNN (AlexNet (2012), VGG, Inception, GANs, etc) and even pre-CNN networks such as Le et al. 2012. ...
1
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1answer
54 views

What is the time complexity for testing a stacked LSTM model?

In the data preparation phase, we have to divide the dataset into two parts: the training dataset and the test dataset. I have seen this post regarding the time complexity for training a model. ...
1
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0answers
17 views

How to align or synchronize Youtube caption with audio accurately

I need to use the automatic caption from Youtube to precisely isolate excerpts from the video aligned to text and generate the dataset to train a model in French. So I've already written the script, ...
3
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1answer
43 views

Custom Tensorflow loss function that disincentivizes all black pixels

I'm training a Tensorflow model that receives an image and segments the image into foreground and background. That is, if the input image is w x h x 3, then the ...
0
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2answers
86 views

Is it true that batch size of form $2^k$ gives better results?

I am confused among the following in selecting the batch size for my model. #1: powers of 2 I generally see that batch sizes are in powers of two: 32, 64, 128, 256. #2: maximum GPU Suppose my GPU ...
2
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1answer
75 views

What are knowledge graph embeddings?

What are knowledge graph embeddings? How are they useful? Are there any extensive reviews on the subject to know all the details? Note that I am asking this question just to give a quick overview of ...
1
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1answer
34 views

How does the classification head of EfficientDet work?

EfficientDet outputs classes and bounding boxes. My question is about both but specifically I am interested in the class prediction net part. In the paper's diagram it shows 2 conv layers. I don't ...
1
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1answer
37 views

Triplet Loss- Three forward pass and one backward pass(Propagation)

I am trying to build a CNN model based on the concepts of Contrastive Learning. In specific based on Triplet loss. I have 5 different class labels and I create triplets such that in a triplet, two ...
0
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0answers
15 views

What is the story of a logic based inferring system which gave disastrous logic related to shaver?

While reading a textbook, I came across a story as follows A research project was to develop a logic-based inferring system. After the completion of the project, the system gave a terrible result on ...
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0answers
25 views

What are the "two new constraints" that the authors of the "TeEther" paper are referring to?

Smart contracts (SC) are programs developed for Ethereum Blockchain initially. They are used for transferring Ether and subsequently can be applied in place of Banking transactions and credit cards. ...
0
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0answers
45 views

Is it possible to find a good neural network structure without training it? [duplicate]

Neural networks consist of so many parameters. Researchers could create as many possible neural networks as they wish. So I want to ask a general question. Could we devise an evolutionary algorithm ...
0
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1answer
31 views

What is the expression for projective transformation?

The following are the two types are projections that are generally used in image processing Affine transformation Projective transformation Affine transformation is a backbone operation in neural ...
-1
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0answers
24 views

How can I perform analysis with this given data

I'm currently working on an AI playing Mandarin using Minimax. I can extract this dictionary from a game where 2 AI with different depth play with each other: ...
-1
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0answers
20 views

What exactly happens during meta-testing?

I am reading some material on meta-learning and I'm not completely sure about some things. Here's what I'm reading: I would like to know exactly what meta-testing is doing exactly and check if my ...
1
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1answer
28 views

How to mix grid matrix and explicit values when designing RL state?

I'm trying to do multi-agent reinforcement learning on the grid world navigation task where multiple agents try to collectively reach multiple goals while avoiding collisions with stationary obstacles ...
10
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2answers
650 views

Is there a fundamental difference between an environment being stochastic and being partially observable?

In AI literature, deterministic vs stochastic and being fully-observable vs partially observable are usually considered two distinct properties of the environment. I'm confused about this because what ...
2
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1answer
42 views

What is the relevance of the concept size to the time constraints in PAC learning?

My question is about the relevance of concept size to the polynomial-time/example constraints in efficient PAC-learning. To ask my question precisely I must first give some definitions. Definitions: ...
0
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0answers
19 views

Model Architecture for Mapping Audio from Low-Quality Space to High-Quality

I am doing a side project, where I am planning on recording with a bad mic and a good mic concurrently, and am trying to make a model to map your low quality audio to the high quality space. First ...
1
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1answer
37 views

How does Horn–Schunck method for Optical Flow solve the aperture problem?

This is regarding the details stated in Wikipedia. I am reading optical flow in Computer Vision. I understood the Horn–Schunck method as such, but did not get how it is related to the aperture problem,...
1
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0answers
15 views

Optimize parametric Log-Likelihood with a Decision Tree

Suppose there are some objects with features, and the target is parametric density estimation. Density estimation is model-based. Parameters are obtained by maximizing log-likelihood. $LL = \sum_{i \...
2
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0answers
27 views

Is there any way to force one input have more effect on model?

Now I am working on building a deep learning model for a regression problem. I used 50 inputs and try to add one new categorical input. The problem is that this one input is much more important than ...
1
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1answer
23 views

Validity of ImageNet for measurement of the model performance

ImageNet dataset is an established benchmark for the measurement of the performance of CV models. ImageNet involves 1000 categories and the goal of the classification model is to output the correct ...
1
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1answer
49 views

Would it be possible to enforce the same $s_{t + 1}$ between the model's estimate and the target function's Q-value?

Say I have a game of blackjack, and I am trying to teach a single forward-pass neural network to approximate the Q value of the current state and action. There are 3 inputs: The current card in hand, ...
0
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0answers
19 views

Why does the Bandit Slippery Walk environment have complimentary probabilities?

I am learning about Reinforcement learning in the book Grokking Deep Reinforcement Learning. Below are snippets. Below is the description of Bandit Slippery Walk (BSW) Below is the description of two ...
0
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0answers
12 views

What is the primary advantage of viewing RNN as a directed graphical model?

While reading the chapter titled "Sequence Modeling: Recurrent and Recursive Nets" from the textbook named Deep Learning by Ian Goodfellow et al, I came across a subsection 10.2.3 titled &...
1
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0answers
20 views

a loss for binary step function data

I have some data with ground truth that looks like a binary step function, where part of it is 0 and part is one. An example for the GT can be like ...
1
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1answer
25 views

How to do testing for an RNN that was trained with teacher forcing only?

If an RNN is trained using only the teacher forcing, then the network takes the actual output from the previous time step as input to the hidden state the next time step. We know that the actual ...
0
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0answers
20 views

Object Center-point detection/tracking without bounding box

The dataset is of microscopic cells. The data format is that it comes with annotations of the center point location of each cell. Usually, the object detection/tracking dataset comes with a bounding ...
0
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1answer
226 views

How do I show the relationship between theories and models using Conceptual Graphs?

The Mereology Theory below contains three first-order axioms that represent a part of a mereology theory. For this posting, it is important that the set of axioms should be considered as a theory. ...
0
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0answers
19 views

Can I use a Mask R-CNN to detect a skin texture?

I'm trying to implement a solution in python to detect skin in an image. I'm evaluating the Mask R-CNN model to create a mask on the skin (not on clothes). The problem is that every solution I have ...
1
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1answer
39 views

Does higher FLOPS mean higher throughput?

I understand that FLOPS means floating-point operations per second, and throughput is the number of inputs (for example, images) per second. If a model has higher FLOPS, it means it performs faster. ...
0
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1answer
46 views
0
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0answers
10 views

Can Dynamical Variational Auto-encoders be trained on and used to generate static 2D images?

Is it possible to train dynamical variational autoencoders, such as Kalman Variational Autoencoders (KVAE), Recurrent Variational Autoencoders (RVAE), or Disentangled Sequential Autoencoders (DSAE) on ...
0
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0answers
20 views

Which kind of RNNs are mostly used in applications: hidden-hidden or actual output-hidden?

I came across two types of RNN while reading the chapter titled Sequence Modeling: Recurrent and Recursive Nets of the textbook named Deep Learning by Ian Goodfellow et al. First type: Recurrent ...
-1
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1answer
50 views

Is my dataset a time series dataset? and should I use an LSTM?

I have a dataset where I am recording temperature after every 4milliseconds till 500 and another feature "conductivity value". The length of the dataset is around a 1000 rows. I need to find ...
0
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0answers
24 views

How do we give recommendations when users create/post content (like in YouTube)?

I've explored tools like amazon personalize, etc. for generating recommendations. It seems like amazon personalize is appropriate when all the content is with the company/a single entity. For example, ...
1
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0answers
24 views

Can teacher forcing in RNN ensure Turing completeness?

RNN has the same capability as a universal Turing machine. But I am confused whether RNN holds the same capabilities if we use teacher forcing. Consider the following excerpts from paragraphs taken ...
0
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1answer
25 views

Deep Learning Architecture where outputs from two different inputs are used for error calculation

Is there a deep learning architecture where outputs of the same model with two different inputs are used for error calculation (backpropagation)? Workflow: Input1 -----> Model ------> Output1 ...
1
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0answers
25 views

Generative systems based on Schmidhuber's compression framework

In Driven by Compression Progress: A Simple Principle Explains Essential Aspects of Subjective Beauty, Novelty, Surprise, Interestingness, Attention, Curiosity, Creativity, Art, Science, Music, Jokes ...
0
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0answers
25 views

Why is there a Hessian diagonal approximation? And when can we use it?

This topic has been introduced in "Pattern Recognition and Machine Learning, Bishop, 2006", section 5.4.1. I am a bit confused about this method and I have two questions. Why this method ...
2
votes
2answers
55 views

How does backprop work through the random sampling layer in a variational autoencoder?

Implementations of variational autoencoders that I've looked at all include a sampling layer as the last layer of the encoder block. The encoder learns to generate a mean and standard deviation for ...
0
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0answers
16 views

Model for predicting whether an event will or will not happen

I am not very learned in the realm of ai and coding, but want to try to learn! There's a specific type of model I'm looking for but don't know how to find. I want to see if ai can predict the chances ...
1
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0answers
32 views

How to teach Machine Learning Agent to destroy replicating objects in a puzzle game?

I have an unusual but very interesting problem. I have a game that is very similar to Toon Blast (a puzzle mobile game). It's based on a Match-2 mechanic in which you can destroy 2 or more connected ...
1
vote
1answer
45 views

Which computer scientists have received the Turing Award specifically for their contributions to Artificial Intelligence?

Many people have heard of Hinton, Bengio, and LeCun in recent years, given the popularity of deep learning and neural networks, and their contributions to this subfield of Artificial Intelligence. For ...
0
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0answers
14 views

Could current AI models reimagine Star Trek Enterprise to depict space & celestial bodies in the grandiose, astounding style of Nolan's Interstellar?

Post-Interstellar, my aptitude shifted in terms of sci-fi. I no longer can enjoy excessively speculative, unfounded predominantly fantasy subordinately scientific story telling, and imagery. I used to ...
1
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0answers
38 views

Is the capability of RNN more than the capability of MLP?

Consider the following excerpt paragraph taken from the section titled "Recurrent Neural Networks" of the chapter 10: Sequence Modeling: Recurrent and Recursive Nets of the textbook named ...
0
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0answers
23 views

Transfer learning on YOLOv5 for character and shape detection

The task is to detect rotated alphanumeric characters embedded on colored shapes. We will have an aerial view of the object (from a UAS: Unarmed Aerial System), something of this sort: (One Uppercase ...

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