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NIPS
2008
15 years 8 months ago
Robust Kernel Principal Component Analysis
Kernel Principal Component Analysis (KPCA) is a popular generalization of linear PCA that allows non-linear feature extraction. In KPCA, data in the input space is mapped to highe...
Minh Hoai Nguyen, Fernando De la Torre
ECAI
2010
Springer
15 years 6 months ago
Mining Outliers with Adaptive Cutoff Update and Space Utilization (RACAS)
Recently the efficiency of an outlier detection algorithm ORCA was improved by RCS (Randomization with faster Cutoff update and Space utilization after pruning), which changes the ...
Chi-Cheong Szeto, Edward Hung
CORR
2010
Springer
151views Education» more  CORR 2010»
15 years 6 months ago
On the Convexity of Latent Social Network Inference
In many real-world scenarios, it is nearly impossible to collect explicit social network data. In such cases, whole networks must be inferred from underlying observations. Here, w...
Seth A. Myers, Jure Leskovec
PVLDB
2008
146views more  PVLDB 2008»
15 years 6 months ago
Efficient search for the top-k probable nearest neighbors in uncertain databases
Uncertainty pervades many domains in our lives. Current real-life applications, e.g., location tracking using GPS devices or cell phones, multimedia feature extraction, and sensor...
George Beskales, Mohamed A. Soliman, Ihab F. Ilyas
CVPR
2010
IEEE
15 years 4 months ago
P-N learning: Bootstrapping binary classifiers by structural constraints
This paper shows that the performance of a binary classifier can be significantly improved by the processing of structured unlabeled data, i.e. data are structured if knowing the ...
Zdenek Kalal, Jiri Matas, Krystian Mikolajczyk