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ICML
2010
IEEE
15 years 5 months ago
Multiple Non-Redundant Spectral Clustering Views
Many clustering algorithms only find one clustering solution. However, data can often be grouped and interpreted in many different ways. This is particularly true in the high-dim...
Donglin Niu, Jennifer G. Dy, Michael I. Jordan
COOPIS
2004
IEEE
15 years 10 months ago
Learning Classifiers from Semantically Heterogeneous Data
Semantically heterogeneous and distributed data sources are quite common in several application domains such as bioinformatics and security informatics. In such a setting, each dat...
Doina Caragea, Jyotishman Pathak, Vasant Honavar
KI
2002
Springer
15 years 6 months ago
Advantages, Opportunities and Limits of Empirical Evaluations: Evaluating Adaptive Systems
While empirical evaluations are a common research method in some areas of Artificial Intelligence (AI), others still neglect this approach. This article outlines both the opportun...
Stephan Weibelzahl, Gerhard Weber
STOC
1993
ACM
117views Algorithms» more  STOC 1993»
15 years 10 months ago
Efficient noise-tolerant learning from statistical queries
In this paper, we study the problem of learning in the presence of classification noise in the probabilistic learning model of Valiant and its variants. In order to identify the cl...
Michael J. Kearns
ICML
2010
IEEE
15 years 7 months ago
Mixed Membership Matrix Factorization
Discrete mixed membership modeling and continuous latent factor modeling (also known as matrix factorization) are two popular, complementary approaches to dyadic data analysis. In...
Lester W. Mackey, David Weiss, Michael I. Jordan