TENSOR PRODUCT AND IRREGULARITY FOR HOLONOMIC D-MODULES by Jean-Baptiste Teyssier Introduction

Source URL: jbteyssier.com

• Abstract algebra
• Algebra
• Mathematics
• Commutative algebra
• Dimension
• Algebraic analysis
• D-module
• Sheaf theory
• Support
• Krull dimension

Lecture 3, Tues Jan 24: Basic Rules of QM Tensor products are a way of building bigger vectors out of smaller ones. Let’s apply a NOT operation to the first bit, and do nothing to the second bit. That’s really the sa

Source URL: www.scottaaronson.com

• Quantum mechanics
• Physics
• Theoretical computer science
• Quantum information science
• Quantum states
• Quantum computing
• Information theory
• Qubit
• Mathematical formulation of quantum mechanics
• Unitary matrix
• Quantum superposition
• Matrix

Incorporating Side Information in Tensor Completion Hemank Lamba*, Vaishnavh Nagarajan*, Kijung Shin*, Naji Shajarisales* Carnegie Mellon University 5000 Forbes Avenue Pittsburgh PA 15213, USA

Source URL: gdac.uqam.ca

• Algebra
• Linear algebra
• Mathematics
• Matrix theory
• Matrix
• Tensor
• Factorization
• Singular value decomposition
• Tensor product

Tensority: an ASIC-friendly Proof of Work Algorithm Based on Tensor Bytom Foundation Email: April 17, 2018 Abstract

Source URL: bytom.io

• Search algorithms
• Statistical randomness
• Matrix
• Probability distribution
• Hash function
• Bitcoin
• Scrypt
• Random variable
• Information retrieval
• Information science
• Cryptography

UNIVERSAL IDENTITIES, II: ⊗ AND ∧ KEITH CONRAD 1. Introduction We will describe how algebraic identities involving operations of multilinear algebra – the tensor product and exterior powers – can be proved by the

Source URL: www.math.uconn.edu

Statistical Performance of Convex Tensor Decomposition Ryota Tomioka† Taiji Suzuki† Department of Mathematical Informatics, The University of Tokyo

Source URL: tomioka.dk

Extraction of Brain Cortical Activities Related to Auditory Impressions Induced by HVAC Sound Using Nonnegative Tensor Factorization

Source URL: www.me.cs.scitec.kobe-u.ac.jp

Tensor-Train Recurrent Neural Networks for Video Classification Yinchong Yang 1 2 Denis Krompass 2 Volker Tresp 1 2 arXiv:1707.01786v1 [cs.CV] 6 JulAbstract

Source URL: www.dbs.ifi.lmu.de

Convex Tensor Decomposition via Structured Schatten Norm Regularization Ryota Tomioka Toyota Technological Institute at Chicago Chicago, IL 60637

Source URL: tomioka.dk

Tensor products Let R be a commutative ring. Given R-modules M1 , M2 and N we say that a map b: M1 × M2 → N is R-bilinear if for all r, r0 ∈ R and module elements mi , m0i ∈ Mi we have b(r · m1 + r0 · m01 , m2

Source URL: www.math.ru.nl