Questions tagged [theory]
Use for questions on AI theory and other theoretical subjects related to AI.
89
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1answer
50 views
Flowchart for a simplified perceptron leaning algorithm [critique request]
I made a flowchart for a simplified perceptron leaning algorithm.
Here is the process of the leaning algorithm.
Step_1: Initialize the weights first.
Step_2: Get a training example randomly and make ...
0
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1answer
34 views
Fitting a gaussian distribution into another distribution - and correlation with Machine Learning
Assume we have two vectors, containing random samples (maybe audio data?). Their distribution can be approximated to a normal distribution, so we can calculate their mean and standard deviation.
I am ...
0
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0answers
28 views
How to detect dynamic hand gestures?
I already know how to detect static hand gestures like fist, peace etc.
I wonder however, how to detect dynamic hand gestures like swipe left/right or "draw" circle with hand. Is some kind ...
1
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0answers
29 views
What would happen if we set the evaluation function in the best-first search algorithm as the cost of paths taken to new nodes?
I am reading AI: A Modern Approach. In Chapter 3, Section 3.3.1, The best-first search algorithm is introduced. We learn that in each iteration, this algorithm chooses which node to expand based on ...
0
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0answers
80 views
What is the difference between learning agents and other kinds of agents, and more specifically, between performance standard and performance measure?
I am reading AI: A Modern Approach. In the 2nd chapter when introducing different agent types, i.e., reflex, utility-based, goal-based, and learning agents, I understood that all types of agents, ...
1
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1answer
41 views
What are the different types of goals for an AI system called?
I remember reading about two different types of goals for an intelligence. The gist was that the first type of goal is one that "just is" - it's an end goal for the system. There doesn't ...
1
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1answer
52 views
What is “Pattern Theory”?
I came across Grenander's work "Probabilities on Algebraic Structures" recently and found that much of Grenander's work focused on what he called "Pattern Theory." He's written ...
2
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1answer
96 views
Is GPT-3 an early example of Strong AI in a Narrow setting?
In GPT-2, the large achievement was being able to generate coherent text over a long-form while maintaining context. This was very impressive but for GPT-2 to do new language tasks, it had to be ...
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0answers
21 views
The convolutional network architectures with enhanced invariance
It is well known, that CNN have advantage with respect to the Dense neural networks in the image classification and other pattern recognition tasks, because they have a translationall invariance built ...
1
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1answer
45 views
The are some fundamental learning theories for developing an AI that imitates human behavior
Most if not all AI systems are not to imitate human, but to finally out-perform human. Examples include using AI to play a game, classification problems, auto-driving, and goal-oriented chatbots. ...
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0answers
35 views
Is it a good idea to train a neural network to classify images without base-hypothesis?
I'm a relative beginner in deep-learning (understand by that, I'm doing my first kaggle competition right now, and I have loads to learn still) and I was just wondering something.
Let's say you have ...
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1answer
82 views
How artificial intelligence will change the future?
AI is the emerging field and biggest business opportunity of the next decade. It's already automating manual and repetitive tasks. And in some areas, it can learn faster than humans, if not yet as ...
7
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1answer
3k views
What is the relationship between gradient accumulation and batch size?
I am currently training some models using gradient accumulation since the model batches do not fit in GPU memory. Since I am using gradient accumulation, I had to tweak the training configuration a ...
2
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0answers
55 views
Is there any application of topology to deep learning?
Is there any application of topology (as in math discipline) to deep learning? If so, what are some examples?
0
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2answers
49 views
Is it theoretically possible (or impossible) that principal component analysis worsens the performance of the model?
In case I had a prediction model and decided to add a PCA step prior to the model, is it theoretically possible/impossible that the number of output dimensions that is better for all tests may perform ...
2
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0answers
34 views
Is there a theory that captures the following ideas?
A big class of problems that are relevant in today's society are full of uncertainty and are also sometimes computationally intractable. Along our lives we come to realize that we are solving the same ...
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2answers
254 views
What are some examples of classical AI methods?
All of the attention in the AI field over the past few years has been toward statistical AI, now that Machine Learning has been validated on hard problems.
However, I want to learn more about ...
1
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1answer
51 views
What is the theoretical basis for the use of Cross Validation set?
So let's follow this line of reasoning. We use a MLE estimator (implementation doesn't matter) and we have a train set. We assume that we have sampled training set from a Gaussian distribution $\...
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0answers
20 views
Suitable kernels for Gaussian processes
Consider a stochastic process $\{X_t \colon t \in T\}$ indexed by a set $T$. We assume for simplicty that $T \in \mathbb{R}^n$. We assume that for any choice of indexes $t_1, \dots, t_n$, the random ...
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2answers
158 views
Understanding CNN in a few sentences
I don't know if this is the right place to ask this question. If it is not, please tell me and I remove it.
I've just started to learn CNN and I'm trying to understand what they do and how they do it....
4
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1answer
64 views
Is there a way to ensure that my model is able to recognize an unseen example?
My question is more theoretical than practical. Let's say that I am training my cat classifier with a dataset that I feel is pretty representative of cat images in general. But then a new breed of cat ...
2
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0answers
27 views
Did people analyze dynamics of very simple LSTMs?
I wonder if researchers tried to understand how LSTMs work by analyzing the dynamics of simple LSTM (e.g. with 2 units)? For example how the hidden state evolves depending on the properties of weight ...
2
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1answer
173 views
What make a CNN suitable for image classification or for semantic segmentation?
I've just started with CNN and there is something that I haven't understood yet:
How do you "ask" a network: "classify me these images" or "do semantic segmentation"?
I think it must be something on ...
2
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0answers
471 views
What does “episodic training” mean?
I'm reading the book Hands-On Meta Learning with Python, and in Prototypical networks said:
So, we use episodic training—for each episode, we randomly sample a
few data points from each class in ...
2
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1answer
51 views
How many ways are there to perform image segmentation?
I'm new in Artificial Intelligence and I want to do image segmentation.
Searching I have found these ways
Digital image processing (I have read it in this book: Digital Image Processing, 4th edition)...
2
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0answers
80 views
Is this a problem well suited for machine learning?
The light-field of a certain scene is the set of all light rays that travel through the volume of that scene at a specific point of time. A light-field camera for example captures and stores a subset ...
4
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2answers
195 views
Are current AI models sufficient to achieve Artificial General Intelligence?
I read an interesting essay about how far we are from AGI. There were quite a few solid points that made me re-visit the foundation of AI today. A few interesting concepts arose:
imagine that you ...
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0answers
31 views
How would you differentiate between different on-policy reinforcement learning algorithms?
How would you differentiate between different on-policy reinforcement learning algorithms?
0
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1answer
119 views
When are compiled vs. interpreted languages more optimal in AI?
When are interpreted languages more optimal? When are compiled languages more optimal? What are the qualities and functions that render the so in relation to various AI methods?
6
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2answers
6k views
What is convergence in machine learning?
I came across this answer on Quora, but it was pretty sparse. I'm looking for specific meanings in the context of machine learning, but also mathematical and economic notions of the term in general.
4
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1answer
701 views
What does 'democratizing AI' exactly mean?
In my AI literature research, I often notice authors use term 'democratizing AI', especially in the AutoML area. I think I have an idea of what this means, but I would like to ask you for some more ...
12
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3answers
165 views
Is there a way to understand neural networks without using the concept of brain?
Is there a way to understand, for instance, a multi-layered perceptron without hand-waving about them being similar to brains etc?
For example: it is obvious that what a perceptron does is ...
1
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1answer
40 views
Why is image classification tasks are dominated by minimizing cost function instead of maximizing ones?
I was watching a video of policy gradient by Andrej Karpathy at 10:00 there shows an equation for supervised learning for image classification.
$max\sum _{i}log \:p(y_i|x_i)$
I have worked with ...
5
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2answers
80 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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9answers
1k views
Can Neural Networks self-optimize?
Suppose that you show a neural network its own code, and allow it to edit itself?
Can a neural network modify its own weights and architecture (the number of layers, the number of neurons per layer, ...
52
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4answers
14k views
Are neural networks prone to catastrophic forgetting?
Imagine you show a neural network a picture of a lion 100 times and label with "dangerous", so it learns that lions are dangerous.
Now imagine that previously you have shown it millions of images of ...
2
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0answers
43 views
Why do neural networks have bias units?
Why do neural networks have bias units? Why is it sometimes okay to opt them out?
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1answer
2k views
What is an agent in Artificial Intelligence?
While studying artificial intelligence, I have often encountered the term "agent" (often autonomous, intelligent). For instance, in fields such as Reinforcement Learning, Multi-Agent Systems, Game ...
2
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1answer
77 views
Is explainable AI more feasible through symbolic AI or soft computing?
Is explainable AI more feasible through symbolic AI or soft computing?
How much each paradigm, symbolic AI and soft computing (or hydrid approaches), adresses explanation and argumentation, where ...
2
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1answer
65 views
What are the known ways to test AI black boxes? [closed]
Is there any conmprehensive paper or site that describes an overview of the known black box testing techniques?
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0answers
17 views
Theoretical grounding for ease of training with a prior
If we have a neural network that learns the generative model for P(A, B, C)
And now, we want to learn the generative model for P(A, B, C, D)
Is there any theory that says learning P(A,B,C) and then ...
0
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0answers
29 views
Superhuman AI to disguise as human players
TL;DR below.
You entered a online mini video game.
It's a fast-paced hypercasual game. But it's a ranked one - top 10 get prizes. The leaderboard resets and prizes are handed out every couple of ...
2
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1answer
96 views
Neural nets need a short term memory of some sort
I notice with the recent revelation of severe limitations in some AI domains such as self driving cars that NNets behave with the same sort of errors as in simpler models. Ie: They may be ~100% ...
1
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1answer
39 views
Is Intelligence a naturally occurring function of Information Technology?
Here intelligence is defined as any analytic or decision making process, regardless of strength (utility), and, potentially, any process of computation that produces output, regardless of the medium.
...
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2answers
76 views
Are winning and imitating the primary indicators of intelligence?
Conjecture 1: The smartest chess playing system is the one that wins the tournament.
Conjecture 2: The computer system that imitates human dialog is as smart as the human whose dialog was imitated.
...
3
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1answer
91 views
How would a quantum computer potentially facilitate artificial consciousness, assuming it is possible?
How would a quantum computer potentially facilitate artificial consciousness, assuming it is possible?
3
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0answers
32 views
Batch PTA stopping condition
I am reviewing my Neural Network lectures and I have a doubt: My book's (Haykin) batch PTA describes a cost function which is defined over the set of the misclassified inputs.
I have always been ...
2
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0answers
72 views
An idea I had to create the first Humanoid using Deep Learning
I've come up with an idea on how we could use a combination of Deep Learning and body sensors to create a walking talking living humanoid. Here goes:
First, we will recruit 1 billion people and have ...
7
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2answers
138 views
What does learning mean?
Can someone explain what is the process of learning? What does it mean to learn something?
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1answer
91 views
How can I systematically learn about the theory of neural networks?
I have seen a few articles about neural nets. Mostly they went along these lines: we tried these architectures, these meta parameters, we trained it for $x$ hours on $y$ CPUs, and it gave us these ...
