24 papers · ranked by Valyu relevance
Tomokaze Shiratori, Yuichi Takano, Jianchao Bai
Sparse estimation of a Gaussian graphical model (GGM) is an important technique for making relationships between observed variables more interpretable. Various methods have been proposed for sparse GGM estimation, including the graphical lasso that uses the ℓ1 norm regularization term, and other methods that use…
Mahdi Moeini
In this paper we consider a generalization of the Markowitz's Mean-Variance model under linear transaction costs and cardinality constraints. The cardinality constraints are used to limit the number of assets in the optimal portfolio. The generalized model is formulated as a mixed integer quadratic programming (MIP)…
Fahaar Mansoor Pirani, Fırdevs Ulus
There is an existing exact algorithm that solves DC programming problems if one component of the DC function is polyhedral convex [16]. Motivated by this, first, we consider two cutting-plane algorithms for generating an ǫ-polyhedral underestimator of a convex function g. The algorithms start with a polyhedral…
F. J. Aragón Artacho, R. Campoy, P. T. Vuong
The Difference of Convex functions Algorithm (DCA) is widely used for minimizing the difference of two convex functions. A recently proposed accelerated version, termed BDCA for Boosted DC Algorithm, incorporates a line search step to achieve a larger decrease of the objective value at each iteration. Thanks to this…
R. Cameron Craddock, Daniel J. Clark
Degree centrality (DC) and local functional connectivity density (lFCD) are statistics calculated from brain connectivity graphs that measure how important a brain region is to the graph. DC (a.k.a. global functional connectivity density) is calculated as the number of connections a region has with the rest of the…
Tyler C. Shimko, Polly M. Fordyce, Yaron Orenstein
High-throughput protein screening is a critical technique for dissecting and designing protein function. Libraries for these assays can be created through a number of means, including targeted or random mutagenesis of a template protein sequence or direct DNA synthesis. However, mutagenic library construction methods…
Huajuan Huang, Hao Wu, Xiuxi Wei, Yongquan Zhou + 1 more
Clustering is an unsupervised learning method. Density Peak Clustering (DPC), a density-based algorithm, intuitively determines the number of clusters and identifies clusters of arbitrary shapes. However, it cannot function effectively without the correct parameter, referred to as the cutoff distance (dc). The…
Yanxin Li, Joan H. Knoll, Ruth Wilkins, Farrah N. Flegal + 1 more
Dose from radiation exposure can be estimated from dicentric chromosome (DC) frequencies in metaphase cells of peripheral blood lymphocytes. We automated DC detection by extracting features in Giemsa-stained metaphase chromosome images and classifying objects by machine learning (ML). DC detection involves i) intensity…
Yi-Shuai Niu, You Yu
In this paper, we propose a cutting plane algorithm based on DC (Difference-of-Convex) programming and DC cut for globally solving Mixed-Binary Linear Program (MBLP). We first use a classical DC programming formulation via the exact penalization to formulate MBLP as a DC program, which can be solved by DCA algorithm.…
Yi-Shuai Niu, Joaquím J. Júdice, Hoai An Lethi, Tao Pham Dinh
In this paper, we discuss the solution of a Quadratic Eigenvalue Complementarity Problem (QEiCP) by using Difference of Convex (DC) programming approaches. We first show that QEiCP can be represented as dc programming problem. Then we investigate different dc programming formulations of QEiCP and discuss their dc…
Xin Zhang, Jia Liu, Zhengyuan Zhu, Elizabeth Serena Bentley
—Network-distributed optimization has attracted significant attention in recent years due to its ever-increasing applications. However, the classic decentralized gradient descent (DGD) algorithm is communication-inefficient for large-scale and high-dimensional network-distributed optimization problems. To address this…
Qiang Gao, Qin-Qin Gao, Zhong-Yang Xiong, Yu-Fang Zhang + 1 more
Clustering analysis is an unsupervised learning method, which has applications across many fields such as pattern recognition, machine learning, information security, and image segmentation. The density-based method, as one of the various clustering algorithms, has achieved good performance. However, it works poor in…
Mahdi Moeini, Hoai An Le Thi
We investigate a new application of DC (Difference of Convex functions) programming and DCA (DC Algorithm) in solving the constrained two-dimensional non-guillotine cutting problem. This problem consists of cutting a number of rectangular pieces from a large rectangular object. The cuts are done under some constraints…
S. Faazila Fathima, L. Premalatha
Multi-microgrid systems offer a versatile solution to many of the challenges including issues on power glitches, grid flow optimization, stability and protection system malfunction faced by traditional centralized power grids. By enhancing resilience, integrating renewable energy, improving efficiency, and supporting…
Krishna Saha Purnita, M. Rubaiyat Hossain Mondal, Lisu Yu
Light fidelity (LiFi) uses different forms of orthogonal frequency division multiplexing (OFDM), including DC biased optical OFDM (DCO-OFDM). In DCO-OFDM, the use of a large DC bias causes optical power inefficiency, while a small bias leads to higher clipping noise. Hence, finding an appropriate DC bias level for…
Yang Yu, Lingyang Chu, Yanyan Zhang, Zhefeng Wang + 2 more
'Enhong Chen'] Abstract—Dense subgraph discovery is a key primitive in many graph mining applications, such as detecting communities in social networks and mining gene correlation from biological data. Most studies on dense subgraph mining only deal with one graph. However, in many applications, we have more than one…
Dayou Zhang, Yinan Shu, Donald G. Truhlar
In this study, we explored several alternative functional forms to construct more accurate and more physical density coherence functionals for multiconfiguration density-coherence functional theory. Each functional is parameterized against the same database as used in our previous work. The best density coherence…
Authors not listed
Computer-Assisted Synthesis Programs are increasingly employed by organic chemists. Often, these tools combine neural networks for policy prediction with heuristic search algorithms. We propose two novel enhancements, which we call eUCT and dUCT, to the Monte Carlo tree search (MCTS) algorithm. The enhancements were…
Mohamed Abdullah J, Sumathi V
Integrating renewable energy generation with the conventional grid supports reduces carbon emissions in the atmosphere. Despite technical advancements in protection strategies, critical issues concerning renewable integration in microgrid structures require standardized solutions. The essential aspects that need to be…
Bhaskar Rana, Gregory Beran, John Herbert
We consider several molecules characterized by pi-electron conjugation whose extent changes along a flexible torsional coordinate, and which represent the monomer units of polymorphic molecular crystals. Delocalization error in density functional theory (DFT) adversely impacts conformational energies in these species…
Bhaskar Rana, Marc Coons, John Herbert
Modeling of polaron defects is an important aspect of computational materials science but the description of unpaired spins in density functional theory (DFT) suffers from delocalization error. To diagnose and correct the over-delocalization of unpaired spins, we report an implementation of density-corrected (DC-)DFT…
Corby Fink, Julia J. Gevaert, John W. Barrett, Jimmy D. Dikeakos + 2 more
Despite widespread study of dendritic cell (DC)-based cancer immunotherapies, the in vivo post-injection fate of DC remains largely unknown. Due in part to a lack of quantifiable imaging modalities, this is troubling as the amount of DC migration to secondary lymphoid organs correlates with therapeutic efficacy.…
Authors not listed
Multivalent lectin-glycan interactions (MLGIs) are widespread and vital for pathogen infection, cell-cell communication and immune regulation, making them attractive therapeutic targets. Despite significant efforts, research progress in MLGI targeting therapeutics remain limited, due to incomplete understanding of the…
Rahman Basaran, Darshita Budhadev, Amy Kempf, Inga Nehlmeier + 4 more
Multivalent lectin-glycan interactions (MLGIs) are pivotal for viral infections and immune regulation. Their structural and biophysical data are thus highly valuable, not only for the understanding of basic mechanisms but also for designing potent glycoconjugate therapeutics against target MLGIs. However, such…