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AAAI
2010
15 years 1 months ago
Multi-Label Learning with Weak Label
Multi-label learning deals with data associated with multiple labels simultaneously. Previous work on multi-label learning assumes that for each instance, the "full" lab...
Yu-Yin Sun, Yin Zhang, Zhi-Hua Zhou
CISM
1993
149views GIS» more  CISM 1993»
15 years 3 months ago
The Weak Instance Model
The weak instance model is a framework to consider the relations in a database as a whole, regardless of the way attributes are grouped in the individual relations. Queries and upd...
Paolo Atzeni, Riccardo Torlone
GECCO
2006
Springer
152views Optimization» more  GECCO 2006»
15 years 3 months ago
Strong recombination, weak selection, and mutation
We show that there are unimodal fitness functions and genetic algorithm (GA) parameter settings where the GA, when initialized with a random population, will not move close to the...
Alden H. Wright, J. Neal Richter
ICMLA
2010
14 years 9 months ago
Boosting Multi-Task Weak Learners with Applications to Textual and Social Data
Abstract--Learning multiple related tasks from data simultaneously can improve predictive performance relative to learning these tasks independently. In this paper we propose a nov...
Jean Baptiste Faddoul, Boris Chidlovskii, Fabien T...
CORR
2010
Springer
137views Education» more  CORR 2010»
14 years 12 months ago
Local algorithms in (weakly) coloured graphs
A local algorithm is a distributed algorithm that completes after a constant number of synchronous communication rounds. We present local approximation algorithms for the minimum ...
Matti Åstrand, Valentin Polishchuk, Joel Ryb...