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Questions tagged [statistical-ai]

For questions about the applications/clarifications/intuitions/proofs behind the use of statistical methods in AI/ML programs.

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11 views

How to interpret the generated ACF and PACF plot in time-series problem?

I recently started working onto Time-Series problem and gathered insights onto the working and the logic behind. However I'm still not clear that how ACF and PACF plots help us in building a model? ...
5
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2answers
138 views

Why exactly do neural networks require i.i.d. data?

In reinforcement learning, in general, successive states (actions and rewards) are highly correlated. An "experience replay" buffer was used, in the DQN architecture, to avoid training the neural ...
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1answer
36 views

Can we derive the distribution of a random variable based on a dependent random variable's distribution?

In the diagram below, there are three variables: X3 is a function of (depends on) X1 and X2, ...
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2answers
96 views

Are neural networks statistical models?

By reading the abstract of Neural Networks and Statistical Models paper it would seem that ANNs are statistical models. In contrast Machine Learning is not just glorified Statistics. I am looking ...
3
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1answer
69 views

Why KNN, Decision Trees, etc have a high variance?

Some examples of low-variance Machine Learning algorithms include Linear Regression, Linear Discriminant Analysis and Logistic Regression. Examples of high-variance Machine Learning algorithms ...
4
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1answer
85 views

Methodology bias in AI textbooks

Let me compare two textbooks: (1) "Artificial Intelligence: A Modern Approach" by Stuart J. Russell and Peter Norvig and (2) "Artificial Intelligence: Structures and Strategies for Complex Problem ...
4
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1answer
152 views

Difference in scope of statistical AI and classical AI?

I'm interested in the differences in scope between statistical AI and Classical AI (gofai). What are the different qualities, and the differences in capability and application? Real world examples ...
3
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2answers
82 views

Reinforcement learning objective as conditional expectations

In one of his lectures Levine describes the objective of reinforcement learning as: $$J(\tau) = E_{\tau\sim p_\theta(\tau)}[r(\tau)]$$ where $\tau$ refers to a single trajectory and $p_\theta(\tau)$ ...
5
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1answer
361 views

TRPO/PPO importance sampling term in loss function

In the Trust-Region Policy Optimisation (TRPO) algorithm (and subsequently in PPO also), I do not understand the motivation behind replacing the log probability term from standard policy gradients ...
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1answer
780 views

Is Nassim Taleb right about AI not being able to accurately predict certain types of distributions?

So Taleb has two heuristics to generally describe data distributions. One is Mediocristan, which basically means things that are on a Gaussian distribution such as height and/or weight of people. The ...
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0answers
195 views

Why do we need Upsampling and Downsampling in Progressive Growing of Gans

I was working recently on Progressive Growing of GANs (aka PGGANs). I have implemented the whole architecture, but the problem that was ticking my mind is that in simple GANs, like DCGAN, PIX2PIX, we ...
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0answers
50 views

Confidence interval around a DNN prediction

I am facing a problem and do not know whether it is even solvable: I want to predict the behaviour of a system using a DNN, say a CNN, in the sense that I want to predict the time and intensity of a ...
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2answers
68 views

Finding the right questions to increase accuracy in classification

Lets say I have a list of 100k medical cases from my hospital, each row = patient with symptoms (such as fever , funny smell, pain etc.. ) and my labels are medical conditions such as Head trauma, ...
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1answer
315 views

Are standard deviation, variance, skew good features for ML?

Pretty simple question here: Is it useful to use the standard deviation, skew, kurtosis, or any other extrapolatory stats as features, and if so in which problem sets? In this case, I am talking ...
11
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2answers
2k views

What is sample efficiency, and how can importance sampling be used to achieve it?

For instance, the title of this paper reads: "Sample Efficient Actor-Critic with Experience Replay". What is sample efficiency, and how can importance sampling be used to achieve it?
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2answers
81 views

Bayesian decision function

How to prove and what is the mathematical condition in terms of probability that a MEASURABLE FUNCTION is a bayesian decision function ? Can you give an example with standard or weighted binary ...
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1answer
63 views

Computing a “prominence score” (Computer Vision)

Is there any previous work on computing some sort of prominence score based on the prevalence of features in an image? For example, let's say I am classifying images based on whether or not they have ...
3
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2answers
82 views

Figure out the meaning of words

Imagine two languages that have only these words: Man = 1, deer = 2, eat = 3, grass = 4 And you would form all sentences possible from these words: ...
3
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1answer
119 views

With gradient descent w/MSE on a regression, must/should every Epoch use the exact same training samples?

Let's say I've got a training sample set of 1 million records, which I pull batches of 100 from to train a basic regression model using gradient descent and MSE as a loss function. Assume test and ...
5
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1answer
149 views

What is Statistical relational learning?

I have gone through the wikipedia explanation of SRL. But, it only confused me more: Statistical relational learning (SRL) is a subdiscipline of artificial intelligence and machine learning that is ...
6
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4answers
476 views

What are some examples of statistical AI?

I believe that statistical AI uses inductive thought processes. For example, deducing a trend from a pattern, after training. What are some examples of successfully applying statistical AI to real ...
11
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3answers
380 views

How does noise affect generalization?

Does increasing the noise in data help to improve the learning ability of a network? Does it make any difference or does it depend on the problem being solved? How is it affect the generalization ...