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Probability Distributions
Several families of probability distributions arise repeatedly in various machine learning settings. We refer to these probability distributions as...
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Probability Review
We briefly review key concepts in probability in this appendix.
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Probability
In this third chapter, we are going to see the essential aspects related to the concept of Probability. As in the previous chapters and the coming...
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Probability
This chapter introducesProbability Probabilitydefinition Probabilitynotation the subject of probability using examples to create various scenarios,...
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Soft Probability and Entropy
This chapter extends classical probability theory using Soft logic. To do so, we start from a fundamental distinction in continuous probability...
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Fuzzy Probability Theory
In this chapter we look more closely at the fuzzy binomial distribution, the fuzzy Poisson, and at the fuzzy normal,exponential and uniform...
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Probability Spaces
Probability theory is the basis for statistics. This is what we deal with in this chapter. At the end of it...
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Reconstructing Probability Distributions from Data
Machine learning applications often assume that the observed data is sampled from probability distributions. How can these probability distributions...
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Probability Basics and Random Variables
Probability theory predicts the expected frequencies of specific outcomes of experiments. On the other hand, statistical methods view data as...
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Probability and Statistics for Machine Learning A Textbook
This book covers probability and statistics from the machine learning perspective. The chapters of this book belong to three categories:
1. The basics...
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Probability Distributions Using PyTorch
Probability and random variables are an integral part of computation in a graph-computing platform like PyTorch. You must understanding probability...
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Statistics and Probability for Machine Learning
This chapter delves into the critical role of statistics and probability in machine learning, starting with an overview of random experiments and...
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Introduction to Probability Theory
Probability is a way of expressing the likelihood of a particular event occurring, and we discuss discrete random variables; probability...
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Bayesian optimization over the probability simplex
Gaussian Process based Bayesian Optimization is largely adopted for solving problems where the inputs are in Euclidean spaces. In this paper we...
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Probability Ordinal-Preserving Semantic Hashing
Existing semantic hashing methods primarily concentrate on preserving piecewise class information or pairwise correlations in learned binary codes,...
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Probability cost function based weighted extreme learning machine
Standard extreme learning machine has good generalization performance and fast learning speed, but has the disadvantage of degrading performance for...
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Human Presence Probability Map (HPP): A Probability Propagation Based on Human Flow Grid
Personal assistance, delivery services, and crowd navigation through robots fleet are complex activities that involve human-robot interaction and...
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6G secure quantum communication: a success probability prediction model
The emergence of 6G networks initiates significant transformations in the communication technology landscape. Yet, the melding of quantum computing...
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Probability Theory
Statistics is a science that is concerned with principles, methods, and techniques for collecting, processing, analyzing, presenting, and...
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A probabilistic generative model for tracking multi-knowledge concept mastery probability
Knowledge tracing aims to track students’ knowledge status over time to predict students’ future performance accurately. In a real environment,...