Results 11 to 20 of about 6,889,955 (273)
Remote Sensing, 2022 In multi-sensor systems (MSSs), sensor selection is a critical technique for obtaining high-quality sensing data. However, when the number of sensors to be selected is unknown in advance, sensor selection is essentially non-deterministic polynomial-hard (
Shuang Liang +3 more
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Hyperspectral Anomaly Detection with Auto-Encoder and Independent Target
Remote Sensing, 2023 As an unsupervised data representation neural network, auto-encoder (AE) has shown great potential in denoising, dimensionality reduction, and data reconstruction.
Shuhan Chen, Xiaorun Li, Yunfeng Yan
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On Multistage Multiscale Stochastic Capacitated Multiple Allocation Hub Network Expansion Planning
Mathematics, 2021 The hub location problem (HLP) basically consists of selecting nodes from a network to act as hubs to be used for flow traffic directioning, i.e., flow collection from some origin nodes, probably transfer it to other hubs, and distributing it to ...
Laureano F. Escudero, Juan F. Monge
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Entropy, 2020 Quantifying uncertainty is a hot topic for uncertain information processing in the framework of evidence theory, but there is limited research on belief entropy in the open world assumption.
Bin Yang +3 more
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Multi-Period Portfolio Optimization Using Dynamic Programming Approach [PDF]
Muṭāli̒āt-i Mudīriyyat-i Ṣan̒atī, 2018 Portfolio selection has always been one of the important issues in the field of investment management, which discusses how to allocate an investor's capital to different assets and form an efficient portfolio.
Negin Mohebbi, Amir Abbas Najafi
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On Classification of High-Cardinality Data Streams
SDM, 2010 The problem of massive-domain stream classification is one in which each attribute can take on one of a large number of possible values. Such streams often arise in applications such as IP monitoring, super-store transactions and financial data.
C. Aggarwal, Philip S. Yu
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Scalable aggregation predictive analytics: a query-driven machine learning approach [PDF]
, 2017 We introduce a predictive modeling solution that provides high quality predictive analytics over aggregation queries in Big Data environments. Our predictive methodology is generally applicable in environments in which large-scale data owners may or may ...
Anagnostopoulos, Christos +2 more
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Advances and Challenges in Machine Learning-Based Cardinality Estimation for Database Query Optimization [PDF]
ITM Web of ConferencesAccurate cardinality estimation is critical for optimizing database queries, yet traditional methods often fail to provide reliable predictions in the face of complex queries, skewed data distributions, and high-dimensional schemas.
Guan Zhibin
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New cardinality notations and styles for modeling NoSQL document-store databases
IEEE Region 10 Conference, 2017 Nowadays, data with several characteristics such as volume, variety etc. are generated daily, i.e. big data; its complexity cannot be overemphasized. On the other hand, schema free NoSQL databases keep emerging at almost the same phase to accommodate ...
A. A. Imam +4 more
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Subsystem identification of feedback and feedforward systems with time delay
Results in Control and Optimization, 2020 We present an algorithm for identifying discrete-time feedback-and-feedforward subsystems with time delay that are interconnected in closed loop with a known subsystem.
S. Alireza Seyyed Mousavi +3 more
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