494 research outputs found
A Scalable and Extensible Framework for Superposition-Structured Models
In many learning tasks, structural models usually lead to better
interpretability and higher generalization performance. In recent years,
however, the simple structural models such as lasso are frequently proved to be
insufficient. Accordingly, there has been a lot of work on
"superposition-structured" models where multiple structural constraints are
imposed. To efficiently solve these "superposition-structured" statistical
models, we develop a framework based on a proximal Newton-type method.
Employing the smoothed conic dual approach with the LBFGS updating formula, we
propose a scalable and extensible proximal quasi-Newton (SEP-QN) framework.
Empirical analysis on various datasets shows that our framework is potentially
powerful, and achieves super-linear convergence rate for optimizing some
popular "superposition-structured" statistical models such as the fused sparse
group lasso
Wishart Mechanism for Differentially Private Principal Components Analysis
We propose a new input perturbation mechanism for publishing a covariance
matrix to achieve -differential privacy. Our mechanism uses a
Wishart distribution to generate matrix noise. In particular, We apply this
mechanism to principal component analysis. Our mechanism is able to keep the
positive semi-definiteness of the published covariance matrix. Thus, our
approach gives rise to a general publishing framework for input perturbation of
a symmetric positive semidefinite matrix. Moreover, compared with the classic
Laplace mechanism, our method has better utility guarantee. To the best of our
knowledge, Wishart mechanism is the best input perturbation approach for
-differentially private PCA. We also compare our work with
previous exponential mechanism algorithms in the literature and provide near
optimal bound while having more flexibility and less computational
intractability.Comment: A full version with technical proofs. Accepted to AAAI-1
2D Reconstruction of Small Intestine's Interior Wall
Examining and interpreting of a large number of wireless endoscopic images
from the gastrointestinal tract is a tiresome task for physicians. A practical
solution is to automatically construct a two dimensional representation of the
gastrointestinal tract for easy inspection. However, little has been done on
wireless endoscopic image stitching, let alone systematic investigation. The
proposed new wireless endoscopic image stitching method consists of two main
steps to improve the accuracy and efficiency of image registration. First, the
keypoints are extracted by Principle Component Analysis and Scale Invariant
Feature Transform (PCA-SIFT) algorithm and refined with Maximum Likelihood
Estimation SAmple Consensus (MLESAC) outlier removal to find the most reliable
keypoints. Second, the optimal transformation parameters obtained from first
step are fed to the Normalised Mutual Information (NMI) algorithm as an initial
solution. With modified Marquardt-Levenberg search strategy in a multiscale
framework, the NMI can find the optimal transformation parameters in the
shortest time. The proposed methodology has been tested on two different
datasets - one with real wireless endoscopic images and another with images
obtained from Micro-Ball (a new wireless cubic endoscopy system with six image
sensors). The results have demonstrated the accuracy and robustness of the
proposed methodology both visually and quantitatively.Comment: Journal draf
The Characteristics and Outlook on Management Accounting Practice in China
As the managerial and controlling system of enterprise, the objective of management accounting is to help managers to achieve the specific management target by a series of management activities, such as planning, decision-making, control and responsibility performance evaluation. Based on review to the history of China\u27s management accounting practice, the paper points out application depth and using field of management accounting in China, and summarizes successful experience in the application of management accounting in enterprises and reveals current application characteristics of management accounting in China. We find out the main problems on management accounting practice in China and outlook the development direction in the future.第194回公開講
Lower Complexity Bounds of Finite-Sum Optimization Problems: The Results and Construction
The contribution of this paper includes two aspects. First, we study the
lower bound complexity for the minimax optimization problem whose objective
function is the average of individual smooth component functions. We
consider Proximal Incremental First-order (PIFO) algorithms which have access
to gradient and proximal oracle for each individual component. We develop a
novel approach for constructing adversarial problems, which partitions the
tridiagonal matrix of classical examples into groups. This construction is
friendly to the analysis of incremental gradient and proximal oracle. With this
approach, we demonstrate the lower bounds of first-order algorithms for finding
an -suboptimal point and an -stationary point in
different settings. Second, we also derive the lower bounds of minimization
optimization with PIFO algorithms from our approach, which can cover the
results in \citep{woodworth2016tight} and improve the results in
\citep{zhou2019lower}
An implicit Cartesian cut-cell method for incompressible viscous flows with complex geometries
A versatile conservative three-dimensional Cartesian cut-cell method for simulation of incompressible viscous flows over complex geometries is presented in this paper. The present method is based on the finite volume method on a non-uniform staggered grid together with a consistent mass and momentum flux computation. Contrary to the commonly cut-cell methods, an implicit time integration scheme is employed in the present method, which avoids numerical instability without any additional small cut-cell treatment. Strict conservation of the mass and momentum for both fluid and cut cells is enforced through the PISO algorithm for the pressure–velocity coupling. The versatility and robustness of the present cut-cell method are demonstrated by simulating various two- and three-dimensional canonical benchmarks (flow over a circular cylinder, airfoil, sphere, pipe, and heart sculpture) and the computed results agree well with previous experimental measurements and various numerical results obtained from the boundary-fitted, immersed boundary/interface, and other cut-cell methods, verifying the accuracy of the proposed method
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