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ICML
2009
IEEE
16 years 7 months ago
On primal and dual sparsity of Markov networks
Sparsity is a desirable property in high dimensional learning. The 1-norm regularization can lead to primal sparsity, while max-margin methods achieve dual sparsity. Combining the...
Jun Zhu, Eric P. Xing
CHI
2009
ACM
16 years 7 months ago
Learning to predict information needs: context-aware display as a cognitive aid and an assessment tool
We discuss the problem of assessing and aiding user performance in dynamic tasks that require rapid selection among multiple information sources. Motivated by research in human se...
Bradley C. Love, Matt Jones, Marc T. Tomlinson, Mi...
KDD
2003
ACM
175views Data Mining» more  KDD 2003»
16 years 7 months ago
Weighted Association Rule Mining using weighted support and significance framework
We address the issues of discovering significant binary relationships in transaction datasets in a weighted setting. Traditional model of association rule mining is adapted to han...
Feng Tao, Fionn Murtagh, Mohsen Farid
CHI
2008
ACM
16 years 7 months ago
Feasibility and pragmatics of classifying working memory load with an electroencephalograph
A reliable and unobtrusive measurement of working memory load could be used to evaluate the efficacy of interfaces and to provide real-time user-state information to adaptive syst...
David B. Grimes, Desney S. Tan, Scott E. Hudson, P...
ICCD
2006
IEEE
115views Hardware» more  ICCD 2006»
16 years 3 months ago
Long-term Performance Bottleneck Analysis and Prediction
— Identifying performance bottlenecks is important for microarchitects and application developers to produce high performance microprocessor designs and application software. Man...
Fei Gao, Suleyman Sair