1,077 research outputs found
An Accelerated Block Proximal Framework with Adaptive Momentum for Nonconvex and Nonsmooth Optimization
We propose an accelerated block proximal linear framework with adaptive
momentum (ABPL) for nonconvex and nonsmooth optimization. We analyze the
potential causes of the extrapolation step failing in some algorithms, and
resolve this issue by enhancing the comparison process that evaluates the
trade-off between the proximal gradient step and the linear extrapolation step
in our algorithm. Furthermore, we extends our algorithm to any scenario
involving updating block variables with positive integers, allowing each cycle
to randomly shuffle the update order of the variable blocks. Additionally,
under mild assumptions, we prove that ABPL can monotonically decrease the
function value without strictly restricting the extrapolation parameters and
step size, demonstrates the viability and effectiveness of updating these
blocks in a random order, and we also more obviously and intuitively
demonstrate that the derivative set of the sequence generated by our algorithm
is a critical point set. Moreover, we demonstrate the global convergence as
well as the linear and sublinear convergence rates of our algorithm by
utilizing the Kurdyka-Lojasiewicz (K{\L}) condition. To enhance the
effectiveness and flexibility of our algorithm, we also expand the study to the
imprecise version of our algorithm and construct an adaptive extrapolation
parameter strategy, which improving its overall performance. We apply our
algorithm to multiple non-negative matrix factorization with the norm,
nonnegative tensor decomposition with the norm, and perform extensive
numerical experiments to validate its effectiveness and efficiency
Globally Convergent Accelerated Algorithms for Multilinear Sparse Logistic Regression with -constraints
Tensor data represents a multidimensional array. Regression methods based on
low-rank tensor decomposition leverage structural information to reduce the
parameter count. Multilinear logistic regression serves as a powerful tool for
the analysis of multidimensional data. To improve its efficacy and
interpretability, we present a Multilinear Sparse Logistic Regression model
with -constraints (-MLSR). In contrast to the -norm and
-norm, the -norm constraint is better suited for feature
selection. However, due to its nonconvex and nonsmooth properties, solving it
is challenging and convergence guarantees are lacking. Additionally, the
multilinear operation in -MLSR also brings non-convexity. To tackle
these challenges, we propose an Accelerated Proximal Alternating Linearized
Minimization with Adaptive Momentum (APALM) method to solve the
-MLSR model. We provide a proof that APALM can ensure the
convergence of the objective function of -MLSR. We also demonstrate
that APALM is globally convergent to a first-order critical point as well
as establish convergence rate by using the Kurdyka-Lojasiewicz property.
Empirical results obtained from synthetic and real-world datasets validate the
superior performance of our algorithm in terms of both accuracy and speed
compared to other state-of-the-art methods.Comment: arXiv admin note: text overlap with arXiv:2308.1212
Understanding Usersβ Continuance Usage for Social Network Services: A Theoretical Model And Empirical Assessment
As a newly emerged e-business model, Social Network Services (SNS) has encouraged new ways of communication and relationship building, also viewed as βthe next big thing after Googleβ. This study draws attention to the substantive differences between adoption and continuance behaviors in the context of SNS, develops the usage continuance model of SNS to investigate continued usage behavior and underlying factors through literature review and theoretical analysis, verified by an empirical test that involved structural equation modeling. This study will advance the theory of IS continuance, provide a comprehensive research model to investigate the post-adoptive behaviors of SNS and help SNS-empowered businesses and organizations to identify critical factors fundamental to long-term viability and the eventual success of their businesses
Unveiling Real Triple Degeneracies in Crystals: Exploring Link and Compound Structures
With their non-Abelian topological charges, real multi-bandgap systems
challenge the conventional topological phase classifications. As the minimal
sector of multi-bandgap systems, real triple degeneracies (RTPs), which serves
as real "Weyl points", lay the foundation for the research on real topological
phases. However, experimental observation of RTP and physical systems with
global band configuration consisting of multiple RTPs in crystals has not been
reported. In this study, we employ Euler number to characterize RTPs, establish
their connection with both Abelian and non-Abelian charges, and provide
experimental evidence for the existence of RTPs in photonic meta-crystals. By
considering RTPs as the basic elements, we further propose the concept of a
topological compound, akin to a chemical compound, where we find that certain
phases are not topologically allowed. The topological classification of RTPs in
crystals demonstrated in our work plays a similar role as the "no-go" theorem
in the Weyl system.Comment: 14 pages, 4 figure
Quasar Photometric Redshifts and Candidate Selection: A New Algorithm Based on Optical and Mid-Infrared Photometric Data
We present a new algorithm to estimate quasar photometric redshifts
(photo-s), by considering the asymmetries in the relative flux distributions
of quasars. The relative flux models are built with multivariate Skew-t
distributions in the multi-dimensional space of relative fluxes as a function
of redshift and magnitude. For 151,392 quasars in the SDSS, we achieve a
photo- accuracy, defined as the fraction of quasars with the difference
between the photo- and the spectroscopic redshift , within 0.1, of 74%. Combining the WISE W1 and W2 infrared
data with the SDSS data, the photo- accuracy is enhanced to 87%. Using the
Pan-STARRS1 or DECaLS photometry with WISE W1 and W2 data, the photo-
accuracies are 79% and 72%, respectively. The prior probabilities as a function
of magnitude for quasars, stars and galaxies are calculated respectively based
on (1) the quasar luminosity function; (2) the Milky Way synthetic simulation
with the Besan\c{c}on model; (3) the Bayesian Galaxy Photometric Redshift
estimation. The relative fluxes of stars are obtained with the Padova
isochrones, and the relative fluxes of galaxies are modeled through galaxy
templates. We test our classification method to select quasars using the DECaLS
, , , and WISE W1 and W2 photometry. The quasar selection completeness
is higher than 70% for a wide redshift range , and a wide magnitude
range mag. Our photo- regression and classification method has
the potential to extend to future surveys. The photo- code will be publicly
available.Comment: 22 pages, 17 figure, accepted by AJ. The code is available at
https://doi.org/10.5281/zenodo.101440
The Development and Application of Cellulose-Based Stationary Phases in Stereoselective Separation of Chiral Pesticides
Spectroscopy of broad absorption line quasars at -- I: evidence for quasar winds shaping broad/narrow emission line regions
We present an observational study of 22 broad absorption line quasars (BAL
QSOs) at based on optical/near-IR spectroscopy, aiming
to investigate quasar winds and their effects. The near-IR spectroscopy covers
the \hb\ and/or \mgii\ broad emission lines (BELs) for these quasars, allowing
us to estimate their central black hole (BH) masses in a robust way. We found
that our BAL QSOs on average do not have a higher Eddington ratio than that
from non-BAL QSOs matched in redshift and/or luminosity. In a subset consisting
of seven strong BAL QSOs possessing sub-relativistic BAL outflows, we see the
prevalence of large \civ-BEL blueshift (3100 km s) and weak \oiii\
emission (particularly the narrow \oiii5007 component), indicative of
nuclear outflows affecting the narrow emission-line (NEL) regions. In another
subset consisting of thirteen BAL QSOs having simultaneous observations of
\mgii\ and \hb, we found a strong correlation between 3000~\AA\ and 5000~\AA\
monochromatic luminosity, consistent with that from non-BAL QSOs matched in
redshift and luminosity; however, there is no correlation between \mgii\ and
\hb\ in FWHM, likely due to nuclear outflows influencing the BEL regions. Our
spectroscopic investigations offer strong evidence that the presence of nuclear
outflows plays an important role in shaping the BEL/NEL regions of these
quasars and possibly, regulating the growth of central supermassive black holes
(SMBHs). We propose that BEL blueshift and BAL could be different
manifestations of the same outflow system viewed at different sightlines and/or
phases.Comment: 13 pages, 10 figures. Accepted for publication in Ap
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