Results 121 to 130 of about 7,174 (250)

Sparse Causal Dynamic Linear Regression

Journal of Time Series Analysis, EarlyView.
ABSTRACT We develop a sparse causal dynamic regression framework for long multivariate time series. With very long time series, the potentially large number of lags and leads in a dynamic regression model often makes time‐domain estimation numerically unstable or intractable.
Rui Huang, Kung‐Sik Chan
wiley   +1 more source

Log-based sparse nonnegative matrix factorization for data representation. [PDF]

Knowl Based Syst, 2022
Peng C, Zhang Y, Chen Y, Kang Z, Chen C, Cheng Q.   +5 more
europepmc   +1 more source

Low-rank matrix approximation with weights or missing data is NP-hard [PDF]

Weighted low-rank approximation (WLRA), a dimensionality reduction technique for data analysis, has been successfully used in several applications, such as in collaborative filtering to design recommender systems or in computer vision to recover ...
GILLIS, Nicolas, GLINEUR, François
core  

Measure‐valued processes for energy markets

Mathematical Finance, Volume 35, Issue 2, Page 520-566, April 2025.
Abstract We introduce a framework that allows to employ (non‐negative) measure‐valued processes for energy market modeling, in particular for electricity and gas futures. Interpreting the process' spatial structure as time to maturity, we show how the Heath–Jarrow–Morton approach can be translated to this framework, thus guaranteeing arbitrage free ...
Christa Cuchiero, Luca Di Persio, Francesco Guida, Sara Svaluto‐Ferro   +3 more
wiley   +1 more source

Nonnegative matrix factorization analysis and multiple machine learning methods identified IL17C and ACOXL as novel diagnostic biomarkers for atherosclerosis. [PDF]

BMC Bioinformatics, 2023
Rao L, Peng B, Li T.
europepmc   +1 more source

Semi-Supervised Nonnegative Matrix Factorization

, 2018
Nonnegative matrix factorization (NMF) is a popular method for low-rank approximation of nonnegative matrix, providing a useful tool for representation learning that is valuable for clustering and classification.
Yoo, J, Lee, H, Choi, S
core   +1 more source

Optimal Portfolio Choice With Cross‐Impact Propagators

Mathematical Finance, EarlyView.
ABSTRACT We consider a class of optimal portfolio choice problems in continuous time where the agent's transactions create both transient cross‐impact driven by a matrix‐valued Volterra propagator, as well as temporary price impact. We formulate this problem as the maximization of a revenue‐risk functional, where the agent also exploits available ...
Eduardo Abi Jaber, Eyal Neuman, Sturmius Tuschmann   +2 more
wiley   +1 more source

Two-Dimensional Semi-Nonnegative Matrix Factorization for Clustering. [PDF]

Inf Sci (N Y), 2022
Peng C, Zhang Z, Chen C, Kang Z, Cheng Q.   +4 more
europepmc   +1 more source

Towards Evolutionary Nonnegative Matrix Factorization

, 2011
Nonnegative Matrix Factorization (NMF) techniques has aroused considerable interests from the field of artificial intelligence in recent years because of its good interpretability and computational efficiency.
Tong, Hanghang, Wang, Fei, Lin, Ching-Yung   +2 more
core   +1 more source

Reinforcement Learning for Jump‐Diffusions, With Financial Applications

Mathematical Finance, EarlyView.
ABSTRACT We study continuous‐time reinforcement learning (RL) for stochastic control in which system dynamics are governed by jump‐diffusion processes. We formulate an entropy‐regularized exploratory control problem with stochastic policies to capture the exploration–exploitation balance essential for RL.
Xuefeng Gao, Lingfei Li, Xun Yu Zhou
wiley   +1 more source