196,264 research outputs found
L1 Regression with Lewis Weights Subsampling
No full textWe consider the problem of finding an approximate solution to ₁ regression while only observing a small number of labels. Given an n × d unlabeled data matrix X, we must choose a small set of m ≪ n rows to observe the labels of, then output an estimate β̂ whose error on the original problem is within a 1 + ε factor of optimal. We show that sampling from X according to its Lewis weights and outputting the empirical minimizer succeeds with probability 1-δ for m > O(1/(ε²) d log d/(ε δ)). This is analogous to the performance of sampling according to leverage scores for ₂ regression, but with exponentially better dependence on δ. We also give a corresponding lower bound of Ω(d/(ε²) + (d + 1/(ε²)) log 1/(δ))
Dr. Duane M. Jackson, Morehouse College, July 2011
No full textThis video is a conversation with Dr. Duane M. Jackson. Dr. Jackson talks about his paper, "Recall and the Serial Position Effect: The Role of Primacy and Recency on Accounting Students' Performance." Jackie Daniel, AUC Woodruff Library, is the interviewer
"Reflections on the subject of Emigration from Europe with a view to Settlement in the United States" By M. Carey.
No full text"Reflections on the subject of Emigration from Europe with a view to Settlement in the United States: containing bried sketches of the moral and political character of those states.
By M. Carey, member of the American philosophical, and of the American Antiquarian Society, and author of The Olive Branch, Cindiciae Hibernicae, essays on banking, on political economy, and on internal improvement.
To which are now added the English editor's comments on the subject; together with Important Advice to Emigrants, and Cautions Against Impositions Practiced in the Outports
Dispelling the Myths Behind First-author Citation Counts
No full textWe conducted a full-scale evaluative citation analysis study of scholars in the XML research field to explore just how different from each other author rankings resulting from different citation counting methods actually are, and to demonstrate the capability of emerging data and tools on the Web in supporting more realistic citation counting methods. Our results contest some common arguments for the continued
use of first-author citation counts in the evaluation of scholars, such as high correlations between author rankings by first-author citation counts and other citation
counting methods, and high costs of using more realistic citation counting methods that are not well-supported by the ISI databases. It is argued that increasingly available digital full text research papers make it possible for citation analysis studies to go beyond what the ISI databases have directly supported and to employ more
sophisticated methods
Dr. Glendon Swarthout
No full textHosted by Roger M. Busfield, MSU Assistant Professor of Speech and Theater, Meet the Author is designed to introduce a general audience to a contemporary author and their work through in-depth interviews. This episode features a conversation between Dr. Glendon Swarthout, prolific author and English professor at MSU, and assistant professors Sam S. Baskett and Theodore B. Strandness
Overall survival of men with metachronous metastatic hormone-sensitive prostate cancer treated with enzalutamide and androgen deprivation therapy
No full textAbstract not available.Christopher J. Sweeney, Andrew J. Martin, Martin R. Stockler, Stephen Begbie, Kim N. Chi, Simon Chowdhury, Xanthi Coskinas, Mark Frydenberg, Wendy E. Hague, Lisa G. Horvath, Anthony M. Joshua, Nicola J. Lawrence, Gavin M. Marx, John McCaffrey, Ray McDermott, Margaret McJannett, Scott A. North, Francis Parnis, Wendy Parulekar, David W. Pook, M. Neil Reaume, Shahneen K. Sandhu, Alvin Tan, Thean Hsiang Tan, Alastair Thomson, Emily Tu, Francisco Vera-Badillo, Scott G. Williams, Sonia Yip, Alison Y. Zhang, Robert R. Zielinski, Ian D. Davis, for the ENZAMET Trial Investigators and the Australian and New Zealand Urogenital and Prostate Cancer Trials Group (ANZUP)
M|G|Input Processes: A versatile class of models for network traffic
No full textWe suggest the M|G|input process as a viable model for network traffic due to its versatility and tractability. To gauge its performance, we study the large buffer asymptotics of a multiplexer driven by an M|G|input process. We identify the process as short or long-range dependent by means of simple tests. The decay rate of the tail probabilities for the buffer content (in steady-state) at the multiplexer is investigated using large deviation techniques suggested by Duffield and O'Connell. The appropriate large deviations scaling is found to be related to the forward recurrence time for the service time distribution, and a closed-form expression is derived for the corresponding generalized limiting log-moment generating function associated with the input process. Two very different regimes are identified. We apply our results to cases where the service time distribution in the M|G|input model is (i) Rayleigh (ii) Gamma (iii) Geometric (iv) Weibull (v) Log-Normal and (vi) Pareto - cases (v) and (vi) have recently been found adequate for modeling packet traffic streams in certain networking applications. Finally, we comment on the insufficiency of the short or long- range dependence in the process in clearly describing buffer dynamics
Simulation of thermal plant optimization and hydraulic aspects of thermal distribution loops for large campuses
No full textFollowing an introduction, the author describes Texas A&M University and its utilities system. After that, the author presents how to construct simulation models for chilled water and heating hot water distribution systems. The simulation model was used in a $2.3 million Ross Street chilled water pipe replacement project at Texas A&M University. A second project conducted at the University of Texas at San Antonio was used as an example to demonstrate how to identify and design an optimal distribution system by using a simulation model. The author found that the minor losses of these closed loop thermal distribution systems are significantly higher than potable water distribution systems. In the second part of the report, the author presents the latest development of software called the Plant Optimization Program, which can simulate cogeneration plant operation, estimate its operation cost and provide optimized operation suggestions. The author also developed detailed simulation models for a gas turbine and heat recovery steam generator and identified significant potential savings. Finally, the author also used a steam turbine as an example to present a multi-regression method on constructing simulation models by using basic statistics and optimization algorithms. This report presents a survey of the author??s working experience at the Energy Systems Laboratory (ESL) at Texas A&M University during the period of January 2002 through March 2004. The purpose of the above work was to allow the author to become familiar with the practice of engineering. The result is that the author knows how to complete a project from start to finish and understands how both technical and nontechnical aspects of a project need to be considered in order to ensure a quality deliverable and bring a project to successful completion. This report concludes that the objectives of the internship were successfully accomplished and that the requirements for the degree of Degree of Engineering have been satisfied
Buffer Engineering for M|G|infinity Input Processes
No full textWe suggest the input process as a viable model forrepresenting the heavy correlations observed in network traffic.Originally introduced by Cox, this model represents the busy-serverprocess of an queue with Poisson inputs and generalservice times distributed according to , and provides a large andversatile class of traffic models. We examine various properties ofthe process, focusing particularly on its richcorrelation structure. The process is shown to effectively portrayshort or long-range dependence simply by controlling the tail of thedistribution .In an effort to understand the dynamics of a system supporting traffic, we study the large buffer asymptotics of amultiplexer driven by an input process. Using the largedeviations framework developed by Duffield and O'Connell, weinvestigate the tail probabilities for the steady-state buffercontent. The key step in this approach is the identification of theappropriate large deviations scaling. This scaling is shown to beclosely related to the forward recurrence time of the service timedistribution, and a closed form expression is derived for thecorresponding limiting log-moment generating functionassociated with the input process. Three different regimes areidentified.The results are then applied to obtain the large bufferasymptotics under a variety of service time distributions. In eachcase, the derived asymptotics are compared with simulation results. While the general functional form of buffer asymptotics may be derivedvia large deviations techniques, direct arguments often provide a moreprecise description when the input traffic is heavily correlated.Even so, several significant inferences may be drawn from thefunctional dependencies of the tail buffer probabilities. Theasymptotics already indicate a sub-exponential behavior in the caseof heavily-correlated traffic, in sharp contrast to the geometricdecay usually observed for Markovian input streams. This difference,along with a shift in the explicit dependence of the asymptotics onthe input and output rates and , from when is exponential, to when issub--exponential, clearly delineates the heavy and light tailed cases.Finally, comparison with similar asymptotics for a different class ofinput processes indicates that buffer sizing cannot be adequatelydetermined by appealing solely to the short versus long-rangedependence characterization of the input model used
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