Sciweavers

58 search results - page 7 / 12
» Empirical comparison of graph classification algorithms
Sort
View
IJCV
2006
115views more  IJCV 2006»
13 years 7 months ago
Object Recognition as Many-to-Many Feature Matching
Object recognition can be formulated as matching image features to model features. When recognition is exemplar-based, feature correspondence is one-to-one. However, segmentation e...
M. Fatih Demirci, Ali Shokoufandeh, Yakov Keselman...
ECAI
2010
Springer
13 years 5 months ago
A Hybrid Continuous Max-Sum Algorithm for Decentralised Coordination
Abstract. In this paper we tackle the problem of coordinating multiple decentralised agents with continuous state variables. Specifically we propose a hybrid approach, which combin...
Thomas Voice, Ruben Stranders, Alex Rogers, Nichol...
ESANN
2006
13 years 8 months ago
Using Regression Error Characteristic Curves for Model Selection in Ensembles of Neural Networks
Regression Error Characteristic (REC) analysis is a technique for evaluation and comparison of regression models that facilitates the visualization of the performance of many regre...
Aloísio Carlos de Pina, Gerson Zaverucha
CIKM
2008
Springer
13 years 9 months ago
Classifying networked entities with modularity kernels
Statistical machine learning techniques for data classification usually assume that all entities are i.i.d. (independent and identically distributed). However, real-world entities...
Dell Zhang, Robert Mao
NIPS
2004
13 years 8 months ago
Worst-Case Analysis of Selective Sampling for Linear-Threshold Algorithms
We provide a worst-case analysis of selective sampling algorithms for learning linear threshold functions. The algorithms considered in this paper are Perceptron-like algorithms, ...
Nicolò Cesa-Bianchi, Claudio Gentile, Luca ...