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» Constraint Programming for Data Mining and Machine Learning
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SIGKDD
2010
151views more  SIGKDD 2010»
14 years 8 months ago
Limitations of matrix completion via trace norm minimization
In recent years, compressive sensing attracts intensive attentions in the field of statistics, automatic control, data mining and machine learning. It assumes the sparsity of the ...
Xiaoxiao Shi, Philip S. Yu
ITNG
2010
IEEE
15 years 7 months ago
A Fast and Stable Incremental Clustering Algorithm
— Clustering is a pivotal building block in many data mining applications and in machine learning in general. Most clustering algorithms in the literature pertain to off-line (or...
Steven Young, Itamar Arel, Thomas P. Karnowski, De...
112
Voted
CSUR
2006
135views more  CSUR 2006»
15 years 1 months ago
Adaptive information extraction
The growing availability of on-line textual sources and the potential number of applications of knowledge acquisition from textual data has lead to an increase in Information Extr...
Jordi Turmo, Alicia Ageno, Neus Català
141
Voted
SDM
2008
SIAM
161views Data Mining» more  SDM 2008»
15 years 3 months ago
Efficient Maximum Margin Clustering via Cutting Plane Algorithm
Maximum margin clustering (MMC) is a recently proposed clustering method, which extends the theory of support vector machine to the unsupervised scenario and aims at finding the m...
Bin Zhao, Fei Wang, Changshui Zhang
TVLSI
2008
140views more  TVLSI 2008»
15 years 1 months ago
A Novel Mutation-Based Validation Paradigm for High-Level Hardware Descriptions
We present a Mutation-based Validation Paradigm (MVP) technology that can handle complete high-level microprocessor implementations and is based on explicit design error modeling, ...
Jorge Campos, Hussain Al-Asaad