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JMLR
2002
137views more  JMLR 2002»
15 years 2 months ago
The Subspace Information Criterion for Infinite Dimensional Hypothesis Spaces
A central problem in learning is selection of an appropriate model. This is typically done by estimating the unknown generalization errors of a set of models to be selected from a...
Masashi Sugiyama, Klaus-Robert Müller
ACL
1994
15 years 4 months ago
A Markov Language Learning Model for Finite Parameter Spaces
This paper shows how to formally characterize language learning in a finite parameter space as a Markov structure, hnportant new language learning results follow directly: explici...
Partha Niyogi, Robert C. Berwick
JMLR
2006
148views more  JMLR 2006»
15 years 3 months ago
Computational and Theoretical Analysis of Null Space and Orthogonal Linear Discriminant Analysis
Dimensionality reduction is an important pre-processing step in many applications. Linear discriminant analysis (LDA) is a classical statistical approach for supervised dimensiona...
Jieping Ye, Tao Xiong
SIGIR
2008
ACM
15 years 3 months ago
Asymmetric distance estimation with sketches for similarity search in high-dimensional spaces
Efficient similarity search in high-dimensional spaces is important to content-based retrieval systems. Recent studies have shown that sketches can effectively approximate L1 dist...
Wei Dong, Moses Charikar, Kai Li
CORR
2008
Springer
105views Education» more  CORR 2008»
15 years 3 months ago
On Full Diversity Space-Time Block Codes with Partial Interference Cancellation Group Decoding
In this paper, we propose a partial interference cancellation (PIC) group decoding strategy/scheme for linear dispersive space-time block codes (STBC) and a design criterion for th...
Xiaoyong Guo, Xiang-Gen Xia