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» Kernels for Semi-Structured Data
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ICML
2007
IEEE
15 years 2 hour ago
Simpler core vector machines with enclosing balls
The core vector machine (CVM) is a recent approach for scaling up kernel methods based on the notion of minimum enclosing ball (MEB). Though conceptually simple, an efficient impl...
András Kocsor, Ivor W. Tsang, James T. Kwok
ICML
2008
IEEE
15 years 2 hour ago
Sparse multiscale gaussian process regression
Most existing sparse Gaussian process (g.p.) models seek computational advantages by basing their computations on a set of m basis functions that are the covariance function of th...
Bernhard Schölkopf, Christian Walder, Kwang I...
ICML
2004
IEEE
15 years 1 hour ago
Large margin hierarchical classification
We present an algorithmic framework for supervised classification learning where the set of labels is organized in a predefined hierarchical structure. This structure is encoded b...
Ofer Dekel, Joseph Keshet, Yoram Singer
PPOPP
2009
ACM
14 years 11 months ago
Comparability graph coloring for optimizing utilization of stream register files in stream processors
A stream processor executes an application that has been decomposed into a sequence of kernels that operate on streams of data elements. During the execution of a kernel, all stre...
Xuejun Yang, Li Wang, Jingling Xue, Yu Deng, Ying ...
CVPR
2010
IEEE
14 years 7 months ago
Connecting Modalities: Semi-supervised Segmentation and Annotation of Images Using Unaligned Text Corpora
We propose a semi-supervised model which segments and annotates images using very few labeled images and a large unaligned text corpus to relate image regions to text labels. Give...
Richard Socher, Li Fei-Fei