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ML
2002
ACM
163views Machine Learning» more  ML 2002»
14 years 11 months ago
Structural Modelling with Sparse Kernels
A widely acknowledged drawback of many statistical modelling techniques, commonly used in machine learning, is that the resulting model is extremely difficult to interpret. A numb...
Steve R. Gunn, Jaz S. Kandola
EMNLP
2007
15 years 1 months ago
Structural Correspondence Learning for Dependency Parsing
Following (Blitzer et al., 2006), we present an application of structural correspondence learning to non-projective dependency parsing (McDonald et al., 2005). To induce the corre...
Nobuyuki Shimizu, Hiroshi Nakagawa
SDM
2011
SIAM
414views Data Mining» more  SDM 2011»
14 years 2 months ago
Clustered low rank approximation of graphs in information science applications
In this paper we present a fast and accurate procedure called clustered low rank matrix approximation for massive graphs. The procedure involves a fast clustering of the graph and...
Berkant Savas, Inderjit S. Dhillon
CICLING
2012
Springer
13 years 7 months ago
Core-Periphery Organization of Graphemes in Written Sequences: Decreasing Positional Rigidity with Increasing Core Order
The positional rigidity of graphemes (as well as words considered as single units) in written sequences has been analyzed in this paper using complex network methodology. In partic...
Md. Izhar Ashraf, Sitabhra Sinha
CVPR
2012
IEEE
13 years 5 months ago
Branch-and-price global optimization for multi-view multi-object tracking
We present a new algorithm to jointly track multiple objects in multi-view images. While this has been typically addressed separately in the past, we tackle the problem as a single...
Laura Leal-Taixe, Gerard Pons-Moll, Bodo Rosenhahn