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Intro
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Tensor Decomposition: A Mathematical Tool for Data Analysis
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Tensors Vector Outer Products
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Matrix Decomposition: Detecting Low-Rank Structure
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CP Tensor Factorization (3-way): Detecting low-rank 3-way structure
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CP first invented in 1927
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New Devices Enable Measuring Multiple Neurons Simultaneously
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Neuron Data
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Fitting CP: Alternating Least Squares
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Solving the Least Squares Problem
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Randomizing the Convergence Check
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Application to Hazardous Gas Dataset
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Factors from Gas Dataset
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Rayleigh CP with Linear Link
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Generalized CP
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Mouse Data using Rayleigh (Nonnes)
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Gas Data Using Rayleigh
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Binary Chat Data using Boolean CP
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CP Tensor Decomposition & Data Analysis
Description:
Explore tensor decomposition as a powerful mathematical tool for data analysis in this SIAM Invited Address from the 2018 Joint Mathematics Meetings. Delve into the fundamentals of tensors, vector outer products, and matrix decomposition for detecting low-rank structures. Learn about CP tensor factorization and its applications in neuroscience and hazardous gas detection. Discover advanced techniques like Rayleigh CP with linear link, generalized CP, and Boolean CP for analyzing diverse datasets including mouse experiments and binary chat data. Gain insights into solving least squares problems and implementing alternating least squares for CP fitting.

Tensor Decomposition - A Mathematical Tool for Data Analysis

Joint Mathematics Meetings
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