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...
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...
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...
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...
— Identifying performance bottlenecks is important for microarchitects and application developers to produce high performance microprocessor designs and application software. Man...