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KDD
2010
ACM
249views Data Mining» more  KDD 2010»
14 years 12 months ago
Semi-supervised sparse metric learning using alternating linearization optimization
In plenty of scenarios, data can be represented as vectors mathematically abstracted as points in a Euclidean space. Because a great number of machine learning and data mining app...
Wei Liu, Shiqian Ma, Dacheng Tao, Jianzhuang Liu, ...
AAAI
1997
14 years 11 months ago
Worst-Case Absolute Loss Bounds for Linear Learning Algorithms
The absolute loss is the absolute difference between the desired and predicted outcome. I demonstrateworst-case upper bounds on the absolute loss for the perceptron algorithm and ...
Tom Bylander
NIPS
2000
14 years 11 months ago
Learning Switching Linear Models of Human Motion
The human figure exhibits complex and rich dynamic behavior that is both nonlinear and time-varying. Effective models of human dynamics can be learned from motion capture data usi...
Vladimir Pavlovic, James M. Rehg, John MacCormick
AUTOMATICA
2007
103views more  AUTOMATICA 2007»
14 years 10 months ago
Adaptive learning control of linear systems by output error feedback
: This paper addresses the problem of designing an output error feedback tracking control for single-input, single-output, minimum phase, observable linear systems. The reference o...
Stefano Liuzzo, Riccardo Marino, Patrizio Tomei
PKDD
2009
Springer
148views Data Mining» more  PKDD 2009»
15 years 4 months ago
Feature Selection by Transfer Learning with Linear Regularized Models
Abstract. This paper presents a novel feature selection method for classification of high dimensional data, such as those produced by microarrays. It includes a partial supervisio...
Thibault Helleputte, Pierre Dupont