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KDD
2008
ACM
178views Data Mining» more  KDD 2008»
14 years 11 months ago
Training structural svms with kernels using sampled cuts
Discriminative training for structured outputs has found increasing applications in areas such as natural language processing, bioinformatics, information retrieval, and computer ...
Chun-Nam John Yu, Thorsten Joachims
PKDD
2000
Springer
144views Data Mining» more  PKDD 2000»
14 years 2 months ago
Fast Hierarchical Clustering Based on Compressed Data and OPTICS
: One way to scale up clustering algorithms is to squash the data by some intelligent compression technique and cluster only the compressed data records. Such compressed data recor...
Markus M. Breunig, Hans-Peter Kriegel, Jörg S...
KDD
2009
ACM
159views Data Mining» more  KDD 2009»
14 years 11 months ago
Adapting the right measures for K-means clustering
Clustering validation is a long standing challenge in the clustering literature. While many validation measures have been developed for evaluating the performance of clustering al...
Junjie Wu, Hui Xiong, Jian Chen
CAV
2009
Springer
176views Hardware» more  CAV 2009»
14 years 11 months ago
PAT: Towards Flexible Verification under Fairness
Recent development on distributed systems has shown that a variety of fairness constraints (some of which are only recently defined) play vital roles in designing self-stabilizing ...
Jun Sun 0001, Yang Liu 0003, Jin Song Dong, Jun Pa...
ICASSP
2008
IEEE
14 years 5 months ago
Maximum kernel density estimator for robust fitting
Robust model fitting plays an important role in many computer vision applications. In this paper, we propose a new robust estimator — Maximum Kernel Density Estimator (MKDE) bas...
Hanzi Wang