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» Labeling Points with Weights
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PAKDD
2010
ACM
169views Data Mining» more  PAKDD 2010»
15 years 11 months ago
oddball: Spotting Anomalies in Weighted Graphs
Given a large, weighted graph, how can we find anomalies? Which rules should be violated, before we label a node as an anomaly? We propose the OddBall algorithm, to find such nod...
Leman Akoglu, Mary McGlohon, Christos Faloutsos
ICML
2010
IEEE
15 years 7 months ago
Random Spanning Trees and the Prediction of Weighted Graphs
We show that the mistake bound for predicting the nodes of an arbitrary weighted graph is characterized (up to logarithmic factors) by the cutsize of a random spanning tree of the...
Nicolò Cesa-Bianchi, Claudio Gentile, Fabio...
ICASSP
2011
IEEE
14 years 10 months ago
Estimation of ordinal approach-avoidance labels in dyadic interactions: Ordinal logistic regression approach
Behavioral Signal Processing aims at automating behavioral coding schemes such as those prevalent in psychology and mental health research. This paper describes methods to quantif...
Viktor Rozgic, Bo Xiao, Athanasios Katsamanis, Bri...
FOIKS
2008
Springer
15 years 7 months ago
Cost-Minimising Strategies for Data Labelling: Optimal Stopping and Active Learning
Supervised learning deals with the inference of a distribution over an output or label space Y conditioned on points in an observation space X , given a training dataset D of pair...
Christos Dimitrakakis, Christian Savu-Krohn
EMNLP
2010
15 years 4 months ago
Confidence in Structured-Prediction Using Confidence-Weighted Models
Confidence-Weighted linear classifiers (CW) and its successors were shown to perform well on binary and multiclass NLP problems. In this paper we extend the CW approach for sequen...
Avihai Mejer, Koby Crammer