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» Learning from Highly Structured Data by Decomposition
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ICML
2010
IEEE
14 years 11 months ago
Metric Learning to Rank
We study metric learning as a problem of information retrieval. We present a general metric learning algorithm, based on the structural SVM framework, to learn a metric such that ...
Brian McFee, Gert R. G. Lanckriet
BMCBI
2006
114views more  BMCBI 2006»
14 years 9 months ago
A high level interface to SCOP and ASTRAL implemented in Python
Background: Benchmarking algorithms in structural bioinformatics often involves the construction of datasets of proteins with given sequence and structural properties. The SCOP da...
James A. Casbon, Gavin E. Crooks, Mansoor A. S. Sa...
TVLSI
2008
140views more  TVLSI 2008»
14 years 9 months ago
A Novel Mutation-Based Validation Paradigm for High-Level Hardware Descriptions
We present a Mutation-based Validation Paradigm (MVP) technology that can handle complete high-level microprocessor implementations and is based on explicit design error modeling, ...
Jorge Campos, Hussain Al-Asaad
SOFSEM
2000
Springer
15 years 1 months ago
Towards High Speed Grammar Induction on Large Text Corpora
Abstract. In this paper we describe an e cient and scalable implementation for grammar induction based on the EMILE approach ( 2], 3], 4], 5], 6]). The current EMILE 4.1 implementa...
Pieter W. Adriaans, Marten Trautwein, Marco Vervoo...
NIPS
2000
14 years 11 months ago
Structure Learning in Human Causal Induction
We use graphical models to explore the question of how people learn simple causal relationships from data. The two leading psychological theories can both be seen as estimating th...
Joshua B. Tenenbaum, Thomas L. Griffiths