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ICTAI
2005
IEEE
15 years 3 months ago
ACE: An Aggressive Classifier Ensemble with Error Detection, Correction, and Cleansing
Learning from noisy data is a challenging and reality issue for real-world data mining applications. Common practices include data cleansing, error detection and classifier ensemb...
Yan Zhang, Xingquan Zhu, Xindong Wu, Jeffrey P. Bo...
PAKDD
2011
ACM
245views Data Mining» more  PAKDD 2011»
14 years 22 days ago
Finding Rare Classes: Adapting Generative and Discriminative Models in Active Learning
Discovering rare categories and classifying new instances of them is an important data mining issue in many fields, but fully supervised learning of a rare class classifier is pr...
Timothy M. Hospedales, Shaogang Gong, Tao Xiang
PKDD
2005
Springer
129views Data Mining» more  PKDD 2005»
15 years 3 months ago
Interestingness is Not a Dichotomy: Introducing Softness in Constrained Pattern Mining
Abstract. The paradigm of pattern discovery based on constraints was introduced with the aim of providing to the user a tool to drive the discovery process towards potentially inte...
Stefano Bistarelli, Francesco Bonchi
SIGMOD
2010
ACM
236views Database» more  SIGMOD 2010»
15 years 2 months ago
Differentially private aggregation of distributed time-series with transformation and encryption
We propose PASTE, the first differentially private aggregation algorithms for distributed time-series data that offer good practical utility without any trusted server. PASTE add...
Vibhor Rastogi, Suman Nath
IEAAIE
2009
Springer
15 years 4 months ago
Incremental Mining of Ontological Association Rules in Evolving Environments
The process of knowledge discovery from databases is a knowledge intensive, highly user-oriented practice, thus has recently heralded the development of ontology-incorporated data ...
Ming-Cheng Tseng, Wen-Yang Lin