Sciweavers
Explore
Publications
Books
Software
Tutorials
Presentations
Lectures Notes
Datasets
Labs
Conferences
Community
Upcoming
Conferences
Top Ranked Papers
Most Viewed Conferences
Conferences by Acronym
Conferences by Subject
Conferences by Year
Tools
Sci2ools
International Keyboard
Graphical Social Symbols
CSS3 Style Generator
OCR
Web Page to Image
Web Page to PDF
Merge PDF
Split PDF
Latex Equation Editor
Extract Images from PDF
Convert JPEG to PS
Convert Latex to Word
Convert Word to PDF
Image Converter
PDF Converter
Community
Sciweavers
About
Terms of Use
Privacy Policy
Cookies
Free Online Productivity Tools
i2Speak
i2Symbol
i2OCR
iTex2Img
iWeb2Print
iWeb2Shot
i2Type
iPdf2Split
iPdf2Merge
i2Bopomofo
i2Arabic
i2Style
i2Image
i2PDF
iLatex2Rtf
Sci2ools
23
click to vote
LOGCOM
2007
favorite
Email
discuss
report
75
views
more
LOGCOM 2007
»
The Extent of Constructive Game Labellings
13 years 10 months ago
Download
www.illc.uva.nl
We define a notion of combinatorial labellings, and show that ∆0 2 is the largest boldface pointclass in which every set admits a combinatorial labelling.
Benedikt Löwe, Brian Semmes
Real-time Traffic
Boldface
|
Combinatorial Labelling
|
Largest Boldface Pointclass
|
LOGCOM 2007
|
claim paper
Related Content
»
CBC Clustering Based Text Classification Requiring Minimal Labeled Data
»
An ontological approach to the construction of problemsolving models
»
Approximate Lasserre Integrality Gap for Unique Games
»
A game based approach to assign geographical relevance to web images
»
Detecting pitching frames in baseball game video using Markov random walk
»
Using Posting Templates for Enhancing Students Argumentative Elaborations in Learning Vill...
»
Graph composition in a graph grammarbased method for automata network evolution
»
Spacetime Interest Points
»
Identifying ambiguous queries in web search
more »
Post Info
More Details (n/a)
Added
16 Dec 2010
Updated
16 Dec 2010
Type
Journal
Year
2007
Where
LOGCOM
Authors
Benedikt Löwe, Brian Semmes
Comments
(0)
Researcher Info
LOGCOM 1998 Study Group
Computer Vision