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Concise Comparative Summaries (CCS) of Large Text Corpora with a Human Experiment
text summarization high-dimensional analysis sparse model- ing, Lasso L1 regularized logistic regression co-occurrence tf-idf
2016/1/20
In this paper, we propose a general framework for topic-specific summarization of large text corpora, and illustrate how it can be used for the analysis of news databases. Our framework, concise compa...
An Efficient Method for Large-scale Slack Allocation
timing graph, slack allocation delay budgeting convex optimization
2015/7/9
We consider a timing or project graph, with given delays on the edges and given arrival times at the source and sink nodes. We are to find the arrival times at the other nodes; these determine the tim...
Optimal Periodic Sensor Scheduling in Large-Scale Dynamical Networks
Dynamic system state estimation sensor scheduling sparsity sensor networks
2013/6/14
We consider the problem of finding optimal time-periodic sensor schedules for estimating the state of a large-scale dynamical system. We assume that a large number of sensors have been deployed and th...
On the sphericity test with large-dimensional observations
Large-dimensional data Sphericity test John’stest CLT for linear spectral statistics Large-dimensional sample covariance matrix
2013/4/27
In this paper, we propose corrections to LRT and John's test for sphericity in large-dimension. New formula for the limiting parameters in the CLT for linear spectral statistics of sample covariance m...
Local Gaussian process approximation for large computer experiments
sequential design sequential updating active learning surrogate model emulator compactly supported covariance local kriging neighborhoods
2013/4/27
We provide a new approach to approximate emulation of large computer experiments. By focusing expressly on desirable properties of the predictive equations, we derive a family of local sequential desi...
In this paper, we first demonstrate that b-bit minwise hashing, whose estimators are positive definite kernels, can be naturally integrated with learning algorithms such as SVM and logistic regression...