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» Issues in Developing Very Large Data Warehouses
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ICCV
2011
IEEE
12 years 7 months ago
RECON: Scale-Adaptive Robust Estimation via Residual Consensus
In this paper, we present a novel, threshold-free robust estimation framework capable of efficiently fitting models to contaminated data. While RANSAC and its many variants have...
Rahul Raguram, Jan-Michael Frahm
ESORICS
2012
Springer
11 years 10 months ago
X.509 Forensics: Detecting and Localising the SSL/TLS Men-in-the-Middle
Although recent compromises and admissions have given new credibility to claimed encounters of Man-in-the-middle (MitM) attacks on SSL/TLS, very little proof exists in the public r...
Ralph Holz, Thomas Riedmaier, Nils Kammenhuber, Ge...
KDD
2008
ACM
140views Data Mining» more  KDD 2008»
14 years 8 months ago
On updates that constrain the features' connections during learning
In many multiclass learning scenarios, the number of classes is relatively large (thousands,...), or the space and time efficiency of the learning system can be crucial. We invest...
Omid Madani, Jian Huang 0002
SIGMOD
2004
ACM
157views Database» more  SIGMOD 2004»
14 years 7 months ago
Adaptive Ordering of Pipelined Stream Filters
We consider the problem of pipelined filters, where a continuous stream of tuples is processed by a set of commutative filters. Pipelined filters are common in stream applications...
Shivnath Babu, Rajeev Motwani, Kamesh Munagala, It...
SDM
2009
SIAM
114views Data Mining» more  SDM 2009»
14 years 4 months ago
Top-k Correlative Graph Mining.
Correlation mining has been widely studied due to its ability for discovering the underlying occurrence dependency between objects. However, correlation mining in graph databases ...
Yiping Ke, James Cheng, Jeffrey Xu Yu