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» Analyzing the Errors of Unsupervised Learning
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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
IJVR
2008
118views more  IJVR 2008»
14 years 9 months ago
HERA: Learner Tracking in a Virtual Environment
The main goals of using simulations and Virtual Environments for Training/Learning (VET/L) are to avoid risks and unwanted consequences, to reduce training costs, and to promote tr...
Kahina Amokrane, Domitile Lourdeaux, Jean-Marie Bu...
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NIPS
2008
14 years 11 months ago
Exact Convex Confidence-Weighted Learning
Confidence-weighted (CW) learning [6], an online learning method for linear classifiers, maintains a Gaussian distributions over weight vectors, with a covariance matrix that repr...
Koby Crammer, Mark Dredze, Fernando Pereira
AAAI
2000
14 years 11 months ago
A Quantitative Study of Small Disjuncts
Systems that learn from examples often express the learned concept in the form of a disjunctive description. Disjuncts that correctly classify few training examples are known as s...
Gary M. Weiss, Haym Hirsh
ACL
2006
14 years 11 months ago
Boosting Statistical Word Alignment Using Labeled and Unlabeled Data
This paper proposes a semi-supervised boosting approach to improve statistical word alignment with limited labeled data and large amounts of unlabeled data. The proposed approach ...
Hua Wu, Haifeng Wang, Zhan-yi Liu