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The basic variety (or: Couldn't natural languages be much simpler
 Second Language Research
, 1997
"... In this article, we discuss the implications of the fact that adult second language learners (outside the classroom) universally develop a wellstructured, efficient and simple form of language – the Basic Variety (BV). Three questions are asked as to (1) the structural properties of the BV, (2) the ..."
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Cited by 54 (2 self)
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In this article, we discuss the implications of the fact that adult second language learners (outside the classroom) universally develop a wellstructured, efficient and simple form of language – the Basic Variety (BV). Three questions are asked as to (1) the structural properties of the BV, (2) the status of these properties and (3) why some structural properties of ‘fully fledged ’ languages are more complex. First, we characterize the BV in four respects: its lexical repertoire, the principles according to which utterances are structured, and temporality and spatiality expressed. The organizational principles proposed are small in number, and interact. We analyse this interaction, describing how the BV is put to use in various complex verbal tasks, in order to establish both what its communicative potentialities are, and also those discourse contexts where the constraints come into conflict and where the variety breaks down. This latter phenomenon provides a partial answer to the third question,concerning the relative complexity of ‘fully fledged ’ languages – they have devices to deal
Reality for current Windows and Linux systems is much simplerWindows: IA32
"... Twolevel page table page directory – 1024 page directory entries page table – 1024 page table entries page – 4 K Virtual address space of an application: – 1024 * 1024 * 4 K = 4 GB Each PDE or PTE is 4 bytes (32 bits) – 1024 entries per level because each page directory or page table must fit in on ..."
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Twolevel page table page directory – 1024 page directory entries page table – 1024 page table entries page – 4 K Virtual address space of an application: – 1024 * 1024 * 4 K = 4 GB Each PDE or PTE is 4 bytes (32 bits) – 1024 entries per level because each page directory or page table must fit in one 4 K pageWindows: IA32Address Translation 10 bits to index into page directory 10 bits to index into page table – 1024 possible indices 12 bits to index into page – 4096 (4 K) possible indicesIA64 64bit addresses 8 K pages Softwareloaded TLB – OS can choose page table structure – Windows chooses a threelevel page table Top page directory
Faster and simpler algorithms for multicommodity flow and other fractional packing problems
"... This paper considers the problem of designing fast, approximate, combinatorial algorithms for multicommodity flows and other fractional packing problems. We present new faster and much simpler algorithms for these problems. ..."
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Cited by 325 (5 self)
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This paper considers the problem of designing fast, approximate, combinatorial algorithms for multicommodity flows and other fractional packing problems. We present new faster and much simpler algorithms for these problems.
How Much Training is Needed in MultipleAntenna Wireless Links?
 IEEE Trans. Inform. Theory
, 2000
"... .... ..."
How much should we trust differencesindifferences estimates? Quarterly Journal of Economics 119:249–75
, 2004
"... Most papers that employ DifferencesinDifferences estimation (DD) use many years of data and focus on serially correlated outcomes but ignore that the resulting standard errors are inconsistent. To illustrate the severity of this issue, we randomly generate placebo laws in statelevel data on fema ..."
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Cited by 775 (1 self)
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Most papers that employ DifferencesinDifferences estimation (DD) use many years of data and focus on serially correlated outcomes but ignore that the resulting standard errors are inconsistent. To illustrate the severity of this issue, we randomly generate placebo laws in statelevel data on female wages from the Current Population Survey. For each law, we use OLS to compute the DD estimate of its “effect ” as well as the standard error of this estimate. These conventional DD standard errors severely understate the standard deviation of the estimators: we find an “effect ” significant at the 5 percent level for up to 45 percent of the placebo interventions. We use Monte Carlo simulations to investigate how well existing methods help solve this problem. Econometric corrections that place a specific parametric form on the timeseries process do not perform well. Bootstrap (taking into account the autocorrelation of the data) works well when the number of states is large enough. Two corrections based on asymptotic approximation of the variancecovariance matrix work well for moderate numbers of states and one correction that collapses the time series information into a “pre ” and “post ” period and explicitly takes into account the effective sample size works well even for small numbers of states.
Compositional Model Checking
, 1999
"... We describe a method for reducing the complexity of temporal logic model checking in systems composed of many parallel processes. The goal is to check properties of the components of a system and then deduce global properties from these local properties. The main difficulty with this type of approac ..."
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Cited by 3218 (68 self)
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of approach is that local properties are often not preserved at the global level. We present a general framework for using additional interface processes to model the environment for a component. These interface processes are typically much simpler than the full environment of the component. By composing a
Large Margin Classification Using the Perceptron Algorithm
 Machine Learning
, 1998
"... We introduce and analyze a new algorithm for linear classification which combines Rosenblatt 's perceptron algorithm with Helmbold and Warmuth's leaveoneout method. Like Vapnik 's maximalmargin classifier, our algorithm takes advantage of data that are linearly separable with large ..."
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Cited by 518 (2 self)
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with large margins. Compared to Vapnik's algorithm, however, ours is much simpler to implement, and much more efficient in terms of computation time. We also show that our algorithm can be efficiently used in very high dimensional spaces using kernel functions. We performed some experiments using our
Skip Lists: A Probabilistic Alternative to Balanced Trees
, 1990
"... Skip lists are data structures thla t use probabilistic balancing rather than strictly enforced balancing. As a result, the algorithms for insertion and deletion in skip lists are much simpler and significantly faster than equivalent algorithms for balanced trees. ..."
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Cited by 410 (1 self)
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Skip lists are data structures thla t use probabilistic balancing rather than strictly enforced balancing. As a result, the algorithms for insertion and deletion in skip lists are much simpler and significantly faster than equivalent algorithms for balanced trees.
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