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» On the Learnability of Vector Spaces
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NIPS
2007
14 years 11 months ago
Kernels on Attributed Pointsets with Applications
This paper introduces kernels on attributed pointsets, which are sets of vectors embedded in an euclidean space. The embedding gives the notion of neighborhood, which is used to d...
Mehul Parsana, Sourangshu Bhattacharya, Chiru Bhat...
AAAI
2006
14 years 11 months ago
kFOIL: Learning Simple Relational Kernels
A novel and simple combination of inductive logic programming with kernel methods is presented. The kFOIL algorithm integrates the well-known inductive logic programming system FO...
Niels Landwehr, Andrea Passerini, Luc De Raedt, Pa...
EMNLP
2004
14 years 11 months ago
Max-Margin Parsing
We present a novel discriminative approach to parsing inspired by the large-margin criterion underlying support vector machines. Our formulation uses a factorization analogous to ...
Ben Taskar, Dan Klein, Mike Collins, Daphne Koller...
ESANN
2004
14 years 11 months ago
Neural methods for non-standard data
Standard pattern recognition provides effective and noise-tolerant tools for machine learning tasks; however, most approaches only deal with real vectors of a finite and fixed dime...
Barbara Hammer, Brijnesh J. Jain
ECIR
2006
Springer
14 years 11 months ago
An Efficient Computation of the Multiple-Bernoulli Language Model
Abstract. The Multiple Bernoulli (MB) Language Model has been generally considered too computationally expensive for practical purposes and superseded by the more efficient multino...
Leif Azzopardi, David E. Losada