MRF Inference by k-Fan Decomposition and Tight Lagrangian Relaxation J¨ org Hendrik Kappes, Stefan Schmidt, and Christoph Schn¨orr Image and Pattern Analysis Group & HCI, University of Heidelberg, Germany, {kappes,schm

Source URL: ipa.iwr.uni-heidelberg.de

Entanglement in correlated quantum systems: A quantum information perspective

Source URL: www.cond-mat.de

• Physics
• Quantum mechanics
• Matrix product state
• Quantum entanglement
• Tensor
• Schmidt decomposition
• Quantum state
• Density matrix renormalization group
• Qubit

BPR: Bayesian Personalized Ranking from Implicit Feedback Steffen Rendle, Christoph Freudenthaler, Zeno Gantner and Lars Schmidt-Thieme {srendle, freudenthaler, gantner, schmidt-thieme}@ismll.de Machine Learning Lab, Un

Source URL: www.algo.uni-konstanz.de

• Algebra
• Mathematics
• Information science
• Linear algebra
• Matrix theory
• Recommender systems
• Statistical theory
• Collaborative filtering
• Machine learning
• Loss function
• Singular value decomposition
• Artificial neural network

The field descent and class groups of CM -fields Bernhard Schmidt School of Physical & Mathematical Sciences Nanyang Technological University No. 1 Nanyang Walk, Blk 5, Level 3

Source URL: www.ntu.edu.sg

• Algebraic number theory
• Splitting of prime ideals in Galois extensions
• Algebraic number field
• Permutation
• Discriminant of an algebraic number field
• Decomposition of spectrum

Universal Probability Distribution for the Wave Function of a Quantum System Entangled with Its Environment Sheldon Goldstein∗, Joel L. Lebowitz†, Christian Mastrodonato‡, Roderich Tumulka§, and Nino Zangh`ı¶ Fe

Source URL: math.rutgers.edu

• Quantum mechanics
• Algebra
• Physics
• Quantum information science
• Quantum states
• Linear algebra
• Functional analysis
• Density matrix
• Wave function
• Schmidt decomposition
• Fidelity of quantum states
• Secondary measure

ERGODIC DECOMPOSITION OF QUASI-INVARIANT PROBABILITY MEASURES GERNOT GRESCHONIG AND KLAUS SCHMIDT This paper is dedicated to Anzelm Iwanik in memory of his contributions to the subject and his personal fortitude

Source URL: www.mat.univie.ac.at

Nearly Linear-Time Model-Based Compressive Sensing Chinmay Hegde, Piotr Indyk, and Ludwig Schmidt Massachusetts Institute of Technology, Cambridge MA 02139, USA Abstract. Compressive sensing is a method for recording a

Source URL: people.csail.mit.edu

• Analysis of algorithms
• Linear algebra
• Computational complexity theory
• Numerical linear algebra
• Sparse approximation
• Time complexity
• Compressed sensing
• Big O notation
• Tree decomposition
• Theoretical computer science
• Mathematics
• Applied mathematics

POSTDOCTORAL & EARLY CAREER RESEARCHER EXCHANGE – REPORT DR. SONJA SCHMIDT – UNIVERSITY OF ABERTAY, SIMBIOS EXCHANGE TO AgroParisTech, CNRS, INRA & Bioemco FRANCE – MARCH 2014 The effect of particulate organic matt

Source URL: www.sages.ac.uk

• Soil biology
• Soil
• Organic matter
• Decomposition
• Pom
• Carbon cycle
• Chemistry
• Biology
• Land management

Pairwise Interaction Tensor Factorization for Personalized Tag Recommendation ∗ Lars Schmidt-Thieme

Source URL: www.wsdm-conference.org

• Matrix theory
• Data mining
• Functional analysis
• Numerical linear algebra
• Singular value decomposition
• Recommender system
• ECML PKDD
• Fur language
• Algebra
• Mathematics
• Linear algebra

F05 – Orthogonalisation F05AAF NAG Library Routine Document F05AAF

Source URL: www.nag.com

• Linear independence
• Euclidean vector
• Singular value decomposition
• Gram–Schmidt process
• Orthogonality
• Orthogonalization
• Vector space
• Null vector
• Vector
• Algebra
• Mathematics
• Linear algebra