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» Kernels and Regularization on Graphs
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JMLR
2006
186views more  JMLR 2006»
15 years 1 months ago
Manifold Regularization: A Geometric Framework for Learning from Labeled and Unlabeled Examples
We propose a family of learning algorithms based on a new form of regularization that allows us to exploit the geometry of the marginal distribution. We focus on a semi-supervised...
Mikhail Belkin, Partha Niyogi, Vikas Sindhwani
NIPS
2008
15 years 2 months ago
Regularized Co-Clustering with Dual Supervision
By attempting to simultaneously partition both the rows (examples) and columns (features) of a data matrix, Co-clustering algorithms often demonstrate surprisingly impressive perf...
Vikas Sindhwani, Jianying Hu, Aleksandra Mojsilovi...
ICDM
2009
IEEE
197views Data Mining» more  ICDM 2009»
14 years 11 months ago
A Linear-Time Graph Kernel
The design of a good kernel is fundamental for knowledge discovery from graph-structured data. Existing graph kernels exploit only limited information about the graph structures bu...
Shohei Hido, Hisashi Kashima
ICML
2007
IEEE
16 years 1 months ago
Learning from interpretations: a rooted kernel for ordered hypergraphs
The paper presents a kernel for learning from ordered hypergraphs, a formalization that captures relational data as used in Inductive Logic Programming (ILP). The kernel generaliz...
Gabriel Wachman, Roni Khardon
NIPS
2004
15 years 2 months ago
Computing regularization paths for learning multiple kernels
The problem of learning a sparse conic combination of kernel functions or kernel matrices for classification or regression can be achieved via the regularization by a block 1-norm...
Francis R. Bach, Romain Thibaux, Michael I. Jordan