Results 1  10
of
3,713,865
Additional Detail on Methods
"... Figure SIS1 has a map of the study sites and a schematic detailing the relative location of the sites and major tributaries. Table SIS1 has detail on the characteristics of the study sites, including U.S. Geological Survey site number, drainage area, and model calibration period. ..."
Abstract
 Add to MetaCart
Figure SIS1 has a map of the study sites and a schematic detailing the relative location of the sites and major tributaries. Table SIS1 has detail on the characteristics of the study sites, including U.S. Geological Survey site number, drainage area, and model calibration period.
Additive Logistic Regression: a Statistical View of Boosting
 Annals of Statistics
, 1998
"... Boosting (Freund & Schapire 1996, Schapire & Singer 1998) is one of the most important recent developments in classification methodology. The performance of many classification algorithms can often be dramatically improved by sequentially applying them to reweighted versions of the input dat ..."
Abstract

Cited by 1719 (25 self)
 Add to MetaCart
data, and taking a weighted majority vote of the sequence of classifiers thereby produced. We show that this seemingly mysterious phenomenon can be understood in terms of well known statistical principles, namely additive modeling and maximum likelihood. For the twoclass problem, boosting can
Improving DirectMapped Cache Performance by the Addition of a Small FullyAssociative Cache and Prefetch Buffers
, 1990
"... ..."
Text S1: Additional details on methods Probability
"... of an active promoter We assume that promoters are in thermodynamics equilibrium with transcription factors, and given concentrations of transcription factors the probability of a specific configuration is constant. Table S1 and Table S2 list all the possible configurations of promoters. The probabi ..."
Abstract
 Add to MetaCart
of an active promoter We assume that promoters are in thermodynamics equilibrium with transcription factors, and given concentrations of transcription factors the probability of a specific configuration is constant. Table S1 and Table S2 list all the possible configurations of promoters. The probability of the ith configuration is given as fi = gi = exp(−∆Gi/RT)[CI2] ki [RNAP] ji [CRO2] li
19. Additional details are available as supplemental information
"... values by referring the AD values on each chip to a calibration curve constructed from the AD values for the 11 control transcripts with known abundances that were spiked into each hybridization (9). This “frequency normalization ” allowed comparison of transcript measurements across multiple array ..."
Abstract
 Add to MetaCart
values by referring the AD values on each chip to a calibration curve constructed from the AD values for the 11 control transcripts with known abundances that were spiked into each hybridization (9). This “frequency normalization ” allowed comparison of transcript measurements across multiple array experiments. Frequency values for each gene were expressed in number concentrations (transcripts per million, or ppm), under the assumptions described (9).
19. Additional details are available as supplemental in
"... abundance (3). We normalized the AD values to ÒfrequencyÓ values by referring the AD values on each chip to a calibration curve constructed from the AD values for the 11 control transcripts with known abundances that were spiked into each hybridization (9). This Òfrequency normalizationÓ allowed c ..."
Abstract
 Add to MetaCart
abundance (3). We normalized the AD values to ÒfrequencyÓ values by referring the AD values on each chip to a calibration curve constructed from the AD values for the 11 control transcripts with known abundances that were spiked into each hybridization (9). This Òfrequency normalizationÓ allowed comparison of transcript measurements across multiple array experiments. Frequency values for each gene were expressed in number concentrations (transcripts per million, or ppm), under the assumptions described (9).
A Additional Details A.1 Consumer Demand
, 2013
"... Estimation and Computation Recall that ι ∈ I ≡ {0, 1} 3 denotes a consumer’s inventory state. Slightly abusing notation, also let ι = 1P S2 + 1XB × 2 + 1GC × 4, where 1j is an indicator for console j being owned. I discretize the distributions of αp and αγ to model consumer heterogeneity: consumers ..."
Abstract
 Add to MetaCart
Estimation and Computation Recall that ι ∈ I ≡ {0, 1} 3 denotes a consumer’s inventory state. Slightly abusing notation, also let ι = 1P S2 + 1XB × 2 + 1GC × 4, where 1j is an indicator for console j being owned. I discretize the distributions of αp and αγ to model consumer heterogeneity: consumers are divided among R groups indexed by i, each with pricesensitivity and gamingpreference coefficients (α p i, αγ i) and initial population shares λi,t=0,ι=0 obtained via independent univariate GaussHermite quadrature (c.f. Judd (1998); Heiss and Winschel (2007)). In estimation, αγ was allowed to take on 11 distinct values and αp 5 values, resulting in R = 55 distinct consumer types. However, due to the difficulty in identifying heterogeneity in αp, only heterogeneity in αγ was ultimately allowed. Let λi,t,ι represent the share of the population comprising a consumer of type i with inventory ι at time t. An overview of the estimation routine is: • For a candidate θ, iterate on the following until convergence is obtained on {Γj,t(α γ i, αp,hw i; ι), λi,t,ι}∀t,i,ι (where a tolerance of 10−6 in the supnorm was used for Γ): i Hardware Adoption: At iteration n, for a given {Γ n j,t (αγ i, αp,hw i; ι)}∀j∈Jt,t,i,ι, determine mean console utilities {δ n+1 i,j,t,ι}∀i,j∈Jt,t,ι which match observed shares in data with those predicted by the model. Update the distribution of consumer types with each inventory {λ n+1 i,t,ι}∀t,i,ι. ii Software Adoption: Given the distribution of consumers onboard any hardware platform, compute mean software utilities {ζj,k,t}j∈Jt,k∈Kj,t,t for every software title on every platform that, again, match observed shares in data with those predicted by the model. Update implied software utilities {Γ n+1 j,t (αγ i, αp,hw
Face Recognition: A Literature Survey
, 2000
"... ... This paper provides an uptodate critical survey of still and videobased face recognition research. There are two underlying motivations for us to write this survey paper: the first is to provide an uptodate review of the existing literature, and the second is to offer some insights into ..."
Abstract

Cited by 1363 (21 self)
 Add to MetaCart
into the studies of machine recognition of faces. To provide a comprehensive survey, we not only categorize existing recognition techniques but also present detailed descriptions of representative methods within each category. In addition,
Progressive Meshes
"... Highly detailed geometric models are rapidly becoming commonplace in computer graphics. These models, often represented as complex triangle meshes, challenge rendering performance, transmission bandwidth, and storage capacities. This paper introduces the progressive mesh (PM) representation, a new s ..."
Abstract

Cited by 1321 (11 self)
 Add to MetaCart
Highly detailed geometric models are rapidly becoming commonplace in computer graphics. These models, often represented as complex triangle meshes, challenge rendering performance, transmission bandwidth, and storage capacities. This paper introduces the progressive mesh (PM) representation, a new
Information Technology, Workplace Organization, and the Demand for Skilled Labor: FirmLevel Evidence
 Journal of Economics
, 2002
"... We investigate the hypothesis that the combination of three related innovations—1) information technology (IT), 2) complementary workplace reorganization, and 3) new products and services — constitute a signi�cant skillbiased technical change affecting labor demand in the United States. Using detai ..."
Abstract

Cited by 589 (15 self)
 Add to MetaCart
detailed �rmlevel data, we �nd evidence of complementarities among all three of these innovations in factor demand and productivity regressions. In addition, �rms that adopt these innovations tend to use more skilled labor. The effects of IT on labor demand are greater when IT is combined
Results 1  10
of
3,713,865