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arXiv (Cornell University)
Nonlinear Function Estimation with Empirical Bayes and Approximate Message Passing
2019
Nonlinear function estimation is core to modern machine learning applications. In this paper, to perform nonlinear function estimation, we reduce a nonlinear inverse problem to a linear one using a polynomial kernel expansion. These kernels increase the featu…
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Algorithm

Sequence of operations for a task

In mathematics and computer science, an algorithm ( ) is a finite sequence of mathematically rigorous instructions, typically used to solve a class of specific problems or to perform a computation. Algorithms are used as specifications for performing calculations and data processing. More advanced algorithms can use conditionals to divert the code execution through various routes (referred to as automated decision-making) and deduce valid inferences (referred to as automated reasoning).

In contrast, a heuristic is an approach to solving problems without well- defined correct or optimal results. For example, although social media recommender systems are commonly called "algorithms", they actually rely on heuristics as there is no truly "correct" recommendation.

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arXiv (Cornell University)
Nonlinear Function Estimation with Empirical Bayes and Approximate Message Passing
2019
Nonlinear function estimation is core to modern machine learning applications. In this paper, to perform nonlinear function estimation, we reduce a nonlinear inverse problem to a linear one using a polynomial kernel expansion. These kernels increase the feature set, and may result in poorly conditioned matrices. Nonetheless, we show several examples where the matrix in our linear inverse problem contains only mild linear correlations among columns. The coefficients vector is modeled within a Bayesian setting for w…
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Bayes' Theorem
Computer Science
Mathematics
Polynomial Kernel
Artificial Intelligence
Kernel Method
Machine Learning
Support Vector Machine
Physics
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Quantum Mechanics
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