Quantitative image recovery theorems Muhammad Aqeel Ahmad Khan1,2 , Ulrich Kohlenbach2,∗ 1 Department of Mathematics, The Islamia University of Bahawalpur, Bahawalpur, 63100, Pakistan 2 Department of Mathematics, Techn

Source URL: www.mathematik.tu-darmstadt.de

• Mathematical analysis
• Mathematics
• Operator theory
• Analysis
• Banach space
• Hilbert space
• Convex function
• Fourier analysis

A Mini-Course on Convex Optimization with a view toward designing fast algorithms Nisheeth K. Vishnoi i

Source URL: theory.epfl.ch

• Mathematical optimization
• Mathematical analysis
• Numerical analysis
• Convex analysis
• Convex optimization
• Operations research
• Linear programming
• Convex function
• Gradient descent
• Derivative
• Convex set
• Ellipsoid method

General Convex Order on Risk Aggregation Edgars Jakobsons∗, Xiaoying Han† and Ruodu Wang‡ January 19, 2015 Abstract Using a general notion of convex order, we derive general lower bounds for risk measures of aggreg

Source URL: sas.uwaterloo.ca

• Mathematical analysis
• Actuarial science
• Financial risk
• Analysis
• Economy
• Coherent risk measure
• Convex function
• Risk aversion
• Risk
• Comonotonicity
• Distribution

MetaGrad: Faster Convergence Without Curvature in Online Convex Optimization Wouter M. Koolen Tim van Erven

Source URL: wouterkoolen.info

• Convex analysis
• Mathematical analysis
• Mathematical optimization
• Analysis
• Operations research
• Convex optimization
• Convex function
• Machine learning
• Cognition

6.006 Intro to Algorithms Recitation 24 May 6, 2011

Source URL: courses.csail.mit.edu

• Geometry
• Mathematics
• Space
• Convex analysis
• Convex geometry
• Convex hull algorithms
• Computational geometry
• Euclidean plane geometry
• Convex hull
• Convex set
• Convex polygon
• Convex function

The hyperbolic meaning of the Milnor–Wood inequality Daniel V. Mathews Abstract We introduce a notion of the twist of an isometry of the hyperbolic plane. This twist function is defined on the universal covering group

Source URL: www.danielmathews.info

• Geometry
• Mathematics
• Space
• Lemmas
• Lie groups
• Convex analysis
• Convex cone
• Linear algebra
• Differential geometry of surfaces
• Closed and exact differential forms
• Mbius transformation
• Constructible universe

ActiveClean: Interactive Data Cleaning While Learning Convex Loss Models Sanjay Krishnan, Jiannan Wang, Eugene Wu † , Michael J. Franklin, Ken Goldberg UC Berkeley, † Columbia University {sanjaykrishnan, jnwang, fran

Source URL: sampleclean.org

• Statistics
• Statistical theory
• Estimator
• Statistical inference
• M-estimators
• Convex optimization
• Stochastic gradient descent
• Bias of an estimator
• Loss function
• Data analysis
• Linear regression
• Generalised Hough transform

Journal of Machine Learning Research1890 Submitted 12/10; Revised 10/11; Published 6/12 Regularization Techniques for Learning with Matrices Sham M. Kakade

Source URL: dept.stat.lsa.umich.edu

• Mathematical analysis
• Mathematical optimization
• Mathematics
• Convex analysis
• Convex function
• Bregman divergence
• Convex conjugate
• Lp space
• Convex optimization
• Online machine learning
• Norm
• Multiple kernel learning

4164 IEEE TRANSACTIONS ON INFORMATION THEORY, VOL. 58, NO. 7, JULY 2012 Interior-Point Methods for Full-Information and Bandit Online Learning

Source URL: www-stat.wharton.upenn.edu

• Mathematical optimization
• Convex analysis
• Operations research
• Convex optimization
• Machine learning
• Self-concordant function
• Interior point method
• Ellipsoid method
• Linear programming
• Algorithm
• Convex set
• Stability

THEOREM OF THE DAY Jensen’s Inequality If f is a real convex function, x1, . . . , xn are values in the domain of f , and a1, . . . , an are positive real numbers summing to 1 then X  X 

Source URL: theoremoftheday.org