<--- Back to Details
First PageDocument Content
Probability theory / Neural networks / Convex optimization / Mathematical optimization / Lipschitz continuity / Convex function / Fourier transform / Artificial neuron / Moment / Mathematical analysis / Analysis / Convex analysis
Date: 2014-06-21 17:32:59
Probability theory
Neural networks
Convex optimization
Mathematical optimization
Lipschitz continuity
Convex function
Fourier transform
Artificial neuron
Moment
Mathematical analysis
Analysis
Convex analysis

Signal recovery from Pooling Representations

Add to Reading List

Source URL: yann.lecun.com

Download Document from Source Website

File Size: 263,43 KB

Share Document on Facebook

Similar Documents

Hausdorff Center for Mathematics, Summer School (May 9–13, 2016) Problems for “Discrete Convex Analysis” (by Kazuo Murota) Problem 1. Prove that a function f : Z2 → R defined by f (x1 , x2 ) = φ(x1 − x2 ) is

DocID: 1vjVY - View Document

Mathematical analysis / Mathematics / Analysis / Generalized functions / Smooth functions / Operations research / Travelling salesman problem / Distribution / Limit of a function / Approximation algorithm / Convex function / Euclidean algorithm

Smoothed Analysis of Partitioning Algorithms for Euclidean Functionals∗ Markus Bl¨aser1 Bodo Manthey2

DocID: 1rtnz - View Document

Mathematical analysis / Mathematics / Calculus / Multivariable calculus / Differential calculus / Convex analysis / Mathematical optimization / Derivative / Lagrange multiplier / Quasiconvex function / Hessian matrix / Gradient

REVIEW SHEET FOR FINAL: ADVANCED MATH 195, SECTION 59 (VIPUL NAIK) To maximize efficiency, please bring a copy (print or readable electronic) of this review sheet to all review sessions. 1. Directional derivatives and gr

DocID: 1rrJ2 - View Document

Mathematical optimization / Numerical analysis / Mathematical analysis / Operations research / Linear programming / Convex optimization / Convex analysis / Ellipsoid method / Feasible region / Convex function / Linear inequality / Candidate solution

CS168: The Modern Algorithmic Toolbox Lecture #18: Linear and Convex Programming, with Applications to Sparse Recovery Tim Roughgarden & Gregory Valiant∗ May 25, 2016

DocID: 1rjsj - View Document

Mathematical analysis / Mathematics / Analysis / Functions and mappings / Inverse function / Function / Convex function / Injective function / Continuous function / Derivative / Bijection / Limit of a function

ONE-ONE FUNCTIONS AND INVERSES MATH 152, SECTION 55 (VIPUL NAIK) Corresponding material in the book: Section 7.1. What students should definitely get: The definition of one-to-one function, the computational and checking

DocID: 1rfrF - View Document