Results 41 to 50 of about 13,849 (192)

The Huang–Yang Formula for the Low‐Density Fermi Gas: Upper Bound

Communications on Pure and Applied Mathematics, EarlyView.
ABSTRACT We study the ground state energy of a gas of spin 1/2$1/2$ fermions with repulsive short‐range interactions. We derive an upper bound that agrees, at low density ϱ$\varrho$, with the Huang–Yang conjecture. The latter captures the first three terms in an asymptotic low‐density expansion, and in particular the Huang–Yang correction term of order
Emanuela L. Giacomelli, Christian Hainzl, Phan Thành Nam, Robert Seiringer   +3 more
wiley   +1 more source

Constrained Symmetric Non-Negative Matrix Factorization Guided by Pairwise Constraint Propagation for Image Clustering

IEEE Access
To address the clustering of high-dimensional data, this paper proposes a novel semi-supervised clustering method named Constrained Symmetric Non-negative Matrix Factorization guided by Pairwise Constraint Propagation (PCSNMF).
Weiqian Zhang
doaj   +1 more source

Total positivity in loop groups I: whirls and curls [PDF]

, 2008
This is the first of a series of papers where we develop a theory of total positivity for loop groups. In this paper, we completely describe the totally nonnegative part of the polynomial loop group GL_n(\R[t,t^{-1}]), and for the formal loop group GL_n(\
Lam, Thomas, Pylyavskyy, Pavlo
core  

Lower bounds on the size of semidefinite programming relaxations

, 2014
We introduce a method for proving lower bounds on the efficacy of semidefinite programming (SDP) relaxations for combinatorial problems. In particular, we show that the cut, TSP, and stable set polytopes on $n$-vertex graphs are not the linear image of ...
Briët Jop, Carlen Eric, Nemirovsky A. S., Parrilo Pablo, Vazirani Vijay V.   +4 more
core   +1 more source

On Mixed Memberships and Symmetric Nonnegative Matrix Factorizations

, 2016
The problem of finding overlapping communities in networks has gained much attention recently. Optimization-based approaches use non-negative matrix factorization (NMF) or variants, but the global optimum cannot be provably attained in general. Model-based approaches, such as the popular mixed-membership stochastic blockmodel or MMSB (Airoldi et al ...
Mao, Xueyu, Sarkar, Purnamrita, Chakrabarti, Deepayan   +2 more
openaire   +2 more sources

Quantifying Model Selection Uncertainty in Structural Analysis: Methodology and Application

Earthquake Engineering &Structural Dynamics, EarlyView.
ABSTRACT With increasing focus on complex engineering systems under rare events, computational models are critical for predictions due to the scarcity or absence of data. However, selecting an appropriate model can be challenging. Using a single model without available test calibration could result in significant bias in performance predictions. A case
Ya‐Heng Yang, Tracy C. Becker
wiley   +1 more source

Intraday Functional PCA Forecasting of Cryptocurrency Returns

Journal of Forecasting, EarlyView.
ABSTRACT We study the functional PCA (FPCA) forecasting method in application to functions of intraday returns on Bitcoin. We show that improved interval forecasts of future return functions are obtained when the conditional heteroscedasticity of return functions is taken into account.
Joann Jasiak, Cheng Zhong
wiley   +1 more source

Hypergraph based semi-supervised symmetric nonnegative matrix factorization for image clustering

Pattern Recognition, 2023
Semi-supervised symmetric nonnegative matrix factorization (SNMF) has been shown to be a significant method for both linear and nonlinear data clustering applications. Nevertheless, existing SNMF-based methods only adopt a simple graph to construct the similarity matrix, and cannot fully use the limited supervised information for the construction of ...
Jingxing Yin, Siyuan Peng, Zhijing Yang, Badong Chen, Zhiping Lin   +4 more
openaire   +3 more sources

Joint Estimation and Bandwidth Selection in Partially Parametric Models

Journal of Applied Econometrics, EarlyView.
ABSTRACT We propose a single‐step approach to estimating a model with both a known nonlinear parametric component and an unknown nonparametric component. We study the large sample behavior of a simultaneous optimization routine that estimates both the parameter vector of the parametric component and the bandwidth vector used to smooth the unknown ...
Daniel J. Henderson, Nadine McCloud, Christopher F. Parmeter   +2 more
wiley   +1 more source

Dropping Symmetry for Fast Symmetric Nonnegative Matrix Factorization

, 2018
Accepted in NIPS ...
Zhu, Zhihui, Li, Xiao, Liu, Kai, Li, Qiuwei   +3 more
openaire   +2 more sources