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» Approximate Objects and Approximate Theories
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ICML
2009
IEEE
16 years 7 months ago
Learning with structured sparsity
This paper investigates a new learning formulation called structured sparsity, which is a naturalextensionofthestandardsparsityconceptinstatisticallearningandcompressivesensing. B...
Junzhou Huang, Tong Zhang, Dimitris N. Metaxas
ICML
2005
IEEE
16 years 7 months ago
Proto-value functions: developmental reinforcement learning
This paper presents a novel framework called proto-reinforcement learning (PRL), based on a mathematical model of a proto-value function: these are task-independent basis function...
Sridhar Mahadevan
WWW
2005
ACM
16 years 7 months ago
TotalRank: ranking without damping
PageRank is defined as the stationary state of a Markov chain obtained by perturbing the transition matrix of a web graph with a damping factor that spreads part of the rank. The...
Paolo Boldi
KDD
2006
ACM
143views Data Mining» more  KDD 2006»
16 years 7 months ago
Algorithms for discovering bucket orders from data
Ordering and ranking items of different types are important tasks in various applications, such as query processing and scientific data mining. A total order for the items can be ...
Aristides Gionis, Heikki Mannila, Kai Puolamä...
KDD
2006
ACM
136views Data Mining» more  KDD 2006»
16 years 7 months ago
Very sparse random projections
There has been considerable interest in random projections, an approximate algorithm for estimating distances between pairs of points in a high-dimensional vector space. Let A Rn...
Ping Li, Trevor Hastie, Kenneth Ward Church