Results 71 to 80 of about 7,409 (173)

Overfitting Reduction of Text Classification Based on AdaBELM

Entropy, 2017
Overfitting is an important problem in machine learning. Several algorithms, such as the extreme learning machine (ELM), suffer from this issue when facing high-dimensional sparse data, e.g., in text classification. One common issue is that the extent of
Xiaoyue Feng, Yanchun Liang, Xiaohu Shi, Dong Xu, Xu Wang, Renchu Guan   +5 more
doaj   +1 more source

A Parallel Extension Rule-Based Algorithm for #SAT Problem Using Model-Counting Tree

IEEE Access, 2018
The #SAT problem, which is also called model counting, is one of the most important problems in artificial intelligence and is challenging to the researchers.
Naiyu Tian, Dantong Ouyang, Fengyu Jia, Meng Liu, Liming Zhang   +4 more
doaj   +1 more source

Deep Residual Convolutional Neural Network for Protein-Protein Interaction Extraction

IEEE Access, 2019
Knowledge extracted from the protein-protein interaction (PPI) network can help researchers reveal the molecular mechanisms of biological processes. With the rapid growth in the volume of the biomedical literature, manually detecting and annotating PPIs ...
Hao Zhang, Renchu Guan, Fengfeng Zhou, Yanchun Liang, Zhi-Hui Zhan, Lan Huang, Xiaoyue Feng   +6 more
doaj   +1 more source

K-Dependence Bayesian Classifier Ensemble

Entropy, 2017
To maximize the benefit that can be derived from the information implicit in big data, ensemble methods generate multiple models with sufficient diversity through randomization or perturbation.
Zhiyi Duan, Limin Wang
doaj   +1 more source

The 3-loop non-singlet heavy flavor contributions and anomalous dimensions for the structure function F2(x,Q2) and transversity

Nuclear Physics B, 2014
We calculate the massive flavor non-singlet Wilson coefficient for the heavy flavor contributions to the structure function F2(x,Q2) in the asymptotic region Q2≫m2 and the associated operator matrix element Aqq,Q(3),NS(N) to 3-loop order in Quantum ...
J. Ablinger, A. Behring, J. Blümlein, A. De Freitas, A. Hasselhuhn, A. von Manteuffel, M. Round, C. Schneider, F. Wißbrock   +8 more
doaj   +1 more source

DMfold: A Novel Method to Predict RNA Secondary Structure With Pseudoknots Based on Deep Learning and Improved Base Pair Maximization Principle

Frontiers in Genetics, 2019
While predicting the secondary structure of RNA is vital for researching its function, determining RNA secondary structure is challenging, especially for that with pseudoknots. Typically, several excellent computational methods can be utilized to predict
Linyu Wang, Linyu Wang, Yuanning Liu, Yuanning Liu, Xiaodan Zhong, Xiaodan Zhong, Xiaodan Zhong, Haiming Liu, Haiming Liu, Chao Lu, Chao Lu, Cong Li, Cong Li, Hao Zhang, Hao Zhang   +14 more
doaj   +1 more source

Symbolic computation: systems and applications

Nonlinear Analysis: Modelling and Control, 1998
The article presents an overview of symbolic computation systems, their classification-in-history, the most popular CAS, examples of systems and some of their applications. Symbolics versus numeric, enhancement in mathematics, computing nature of CAS, related projects, networks, references are discussed.
openaire   +3 more sources

SeqHIVE: a Python package to convert the biological sequences to informative vectors for sequence property predictions

BioData Mining
Sequence-based analysis and prediction form a cornerstone of bioinformatics investigations of the sequence-structure-function paradigm across DNA, RNA, and proteins.
Xin Feng, Cheng Gao, Sudan Bai, Jiaxin Zheng, Cuinan Yu, Kewei Li, Lan Huang, Bo Han, Tao You, Jun Zhang, Fengfeng Zhou   +10 more
doaj   +1 more source

Enhancing dynamical signatures of complex systems through symbolic computation. [PDF]

Philos Trans A Math Phys Eng Sci, 2015
Porta A, Baumert M, Cysarz D, Wessel N.
europepmc   +1 more source

Automatic Controversy Detection Based on Heterogeneous Signed Attributed Network and Deep Dual-Layer Self-Supervised Community Analysis

Entropy
In this study, we propose a computational approach that applies text mining and deep learning to conduct controversy detection on social media platforms.
Ying Li, Xiao Zhang, Yu Liang, Qianqian Li   +3 more
doaj   +1 more source