42,918 research outputs found
Exit polling and racial bloc voting: Combining individual-level and RC ecological data
Despite its shortcomings, cross-level or ecological inference remains a
necessary part of some areas of quantitative inference, including in United
States voting rights litigation. Ecological inference suffers from a lack of
identification that, most agree, is best addressed by incorporating
individual-level data into the model. In this paper we test the limits of such
an incorporation by attempting it in the context of drawing inferences about
racial voting patterns using a combination of an exit poll and precinct-level
ecological data; accurate information about racial voting patterns is needed to
assess triggers in voting rights laws that can determine the composition of
United States legislative bodies. Specifically, we extend and study a hybrid
model that addresses two-way tables of arbitrary dimension. We apply the hybrid
model to an exit poll we administered in the City of Boston in 2008. Using the
resulting data as well as simulation, we compare the performance of a pure
ecological estimator, pure survey estimators using various sampling schemes and
our hybrid. We conclude that the hybrid estimator offers substantial benefits
by enabling substantive inferences about voting patterns not practicably
available without its use.Comment: Published in at http://dx.doi.org/10.1214/10-AOAS353 the Annals of
Applied Statistics (http://www.imstat.org/aoas/) by the Institute of
Mathematical Statistics (http://www.imstat.org
Economical (k,m)-threshold controlled quantum teleportation
We study a (k,m)-threshold controlling scheme for controlled quantum
teleportation. A standard polynomial coding over GF(p) with prime p > m-1 needs
to distribute a d-dimensional qudit with d >= p to each controller for this
purpose. We propose a scheme using m qubits (two-dimensional qudits) for the
controllers' portion, following a discussion on the benefit of a quantum
control in comparison to a classical control of a quantum teleportation.Comment: 11 pages, 2 figures, v2: minor revision, discussions improved, an
equation corrected in procedure (A) of section 4.3, v3: major revision,
protocols extended, citations added, v4: minor grammatical revision, v5:
minor revision, discussions extende
A Subband-Based SVM Front-End for Robust ASR
This work proposes a novel support vector machine (SVM) based robust
automatic speech recognition (ASR) front-end that operates on an ensemble of
the subband components of high-dimensional acoustic waveforms. The key issues
of selecting the appropriate SVM kernels for classification in frequency
subbands and the combination of individual subband classifiers using ensemble
methods are addressed. The proposed front-end is compared with state-of-the-art
ASR front-ends in terms of robustness to additive noise and linear filtering.
Experiments performed on the TIMIT phoneme classification task demonstrate the
benefits of the proposed subband based SVM front-end: it outperforms the
standard cepstral front-end in the presence of noise and linear filtering for
signal-to-noise ratio (SNR) below 12-dB. A combination of the proposed
front-end with a conventional front-end such as MFCC yields further
improvements over the individual front ends across the full range of noise
levels
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