Results 41 to 50 of about 13,867 (163)
IEEE AccessTo 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
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Nonnegative Tensor Factorization, Completely Positive Tensors and an Hierarchical Elimination Algorithm [PDF]
, 2013 Nonnegative tensor factorization has applications in statistics, computer vision, exploratory multiway data analysis and blind source separation. A symmetric nonnegative tensor, which has a symmetric nonnegative factorization, is called a completely ...
Qi, Liqun, Xu, Changqing, Xu, Yi
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 +4 more
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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 +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
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
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
, 2014 Olshausen and Field (OF) proposed that neural computations in the primary visual cortex (V1) can be partially modeled by sparse dictionary learning. By minimizing the regularized representation error they derived an online algorithm, which learns Gabor ...
Chklovskii, Dmitri B. +2 more
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Efficient First‐Principles Inverse Design of Nanolasers
Laser &Photonics Reviews, EarlyView.This article introduces a first‐principles inverse‐design framework for nanolasers that directly incorporates nonlinear lasing physics. By unifying steady‐state ab‐initio laser theory (SALT) with topology optimization, it reveals how spatial hole burning, gain saturation, and cavity‐emitter coupling shape laser performance, enabling efficient discovery
Beñat Martinez de Aguirre Jokisch +5 more
wiley +1 more source
Polytopes of Minimum Positive Semidefinite Rank
, 2013 The positive semidefinite (psd) rank of a polytope is the smallest $k$ for which the cone of $k \times k$ real symmetric psd matrices admits an affine slice that projects onto the polytope.
Gouveia, João +2 more
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