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» The Computational Structure of Progress Conditions
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KDD
2010
ACM
224views Data Mining» more  KDD 2010»
15 years 1 months ago
Multi-label learning by exploiting label dependency
In multi-label learning, each training example is associated with a set of labels and the task is to predict the proper label set for the unseen example. Due to the tremendous (ex...
Min-Ling Zhang, Kun Zhang
AAAI
2006
14 years 11 months ago
Learning Partially Observable Action Schemas
We present an algorithm that derives actions' effects and preconditions in partially observable, relational domains. Our algorithm has two unique features: an expressive rela...
Dafna Shahaf, Eyal Amir
GECCO
2008
Springer
168views Optimization» more  GECCO 2008»
14 years 10 months ago
Parameterizing pair approximations for takeover dynamics
Pair approximations have often been used to predict equilibrium conditions in spatially-explicit epidemiological and ecological systems. In this work, we investigate whether this ...
Joshua L. Payne, Margaret J. Eppstein
AMCS
2008
146views Mathematics» more  AMCS 2008»
14 years 10 months ago
Fault Detection and Isolation with Robust Principal Component Analysis
Principal component analysis (PCA) is a powerful fault detection and isolation method. However, the classical PCA which is based on the estimation of the sample mean and covariance...
Yvon Tharrault, Gilles Mourot, José Ragot, ...
ALGORITHMICA
2005
93views more  ALGORITHMICA 2005»
14 years 9 months ago
Universal Asymptotics for Random Tries and PATRICIA Trees
Abstract. We consider random tries and random patricia trees constructed from n independent strings of symbols drawn from any distribution on any discrete space. We show that many ...
Luc Devroye