Výsledky vyhľadávania - Computing methodologies Machine learning Machine learning approaches Markov decision processes

  1. 1

    A Machine Learning Approach for offload Decision Making in Mobile Cloud Computing Autor Mathur, Robin Prakash, Sharma, Manmohan

    ISBN: 9781665405201, 1665405201
    ISSN: 2575-7288
    Vydavateľské údaje: IEEE 19.03.2021
    “… A technique has been proposed by performing a stack ensemble approach on machine learning techniques like the Gaussian approach, multi-layer perceptron, k-nearest neighbors, and linear regression…”
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  2. 2

    Decision Support Platform for Production of Chili using IoT, Cloud Computing, and Machine Learning Approach Autor Elijah, Olakunle, Rahim, Sharul K. A., Abioye, Emmanuel A., Musa, Mu'Azu Jibrin, Salihu, Yahaya Otuoze, Oremeyi, Abubakar Abisetu

    ISSN: 2377-2697
    Vydavateľské údaje: IEEE 17.04.2022
    “… It is a major source of income for both small- and large-scale farmers. Unfortunately, chili farmers have to contend with the challenge of pests and diseases and the need for timely decisions to have a bountiful production…”
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  3. 3

    Diversity Drives Fairness: Ensemble of Higher Order Mutants for Intersectional Fairness of Machine Learning Software Autor Chen, Zhenpeng, Li, Xinyue, Zhang, Jie M., Sarro, Federica, Liu, Yang

    ISSN: 1558-1225
    Vydavateľské údaje: IEEE 26.04.2025
    “…Intersectional fairness is a critical requirement for Machine Learning (ML) software, demanding fairness across subgroups defined by multiple protected attributes…”
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  4. 4

    PolyGym: Polyhedral Optimizations as an Environment for Reinforcement Learning Autor Brauckmann, Alexander, Goens, Andres, Castrillon, Jeronimo

    Vydavateľské údaje: IEEE 01.09.2021
    “… In this paper, we propose a shape-agnostic formulation for the space of legal transformations in the polyhedral model as a Markov Decision Process (MDP…”
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  5. 5

    Orbit-Finite-Dimensional Vector Spaces and Weighted Register Automata Autor Bojanczyk, Mikolaj, Klin, Bartek, Moerman, Joshua

    Vydavateľské údaje: IEEE 29.06.2021
    “…We develop a theory of vector spaces spanned by orbit-finite sets. Using this theory, we give a decision procedure for equivalence of weighted register automata…”
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  6. 6

    Learning Pareto-Frontier Resource Management Policies for Heterogeneous SoCs: An Information-Theoretic Approach Autor Deshwal, Aryan, Belakaria, Syrine, Bhat, Ganapati, Doppa, Janardhan Rao, Pande, Partha Pratim

    Vydavateľské údaje: IEEE 05.12.2021
    “…Mobile system-on-chips (SoCs) are growing in their complexity and heterogeneity (e.g., Arm's Big-Little architecture) to meet the needs of emerging…”
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  7. 7

    Improving Robot Controller Transparency Through Autonomous Policy Explanation Autor Hayes, Bradley, Shah, Julie A.

    ISBN: 9781450343367, 1450343368
    ISSN: 2167-2148
    Vydavateľské údaje: New York, NY, USA ACM 06.03.2017
    “…Shared expectations and mutual understanding are critical facets of teamwork. Achieving these in human-robot collaborative contexts can be especially…”
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  8. 8

    Continuous One-Counter Automata Autor Blondin, Michael, Leys, Tim, Mazowiecki, Filip, Offtermatt, Philip, Perez, Guillermo A.

    Vydavateľské údaje: IEEE 29.06.2021
    “…We study the reachability problem for continuous one-counter automata, COCA for short. In such automata, transitions are guarded by upper and lower bound tests…”
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  9. 9

    Exploiting learning and scenario-based specification languages for the verification and validation of highly automated driving Autor Damm, Werner, Galbas, Roland

    ISBN: 1450357393, 9781450357395
    Vydavateľské údaje: New York, NY, USA ACM 28.05.2018
    “…We propose a series of methods based on learning key structural properties from traffic data-basis and on statistical model checking, ultimately leading to the construction of a scenario catalogue…”
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  10. 10

    DiffSAT: Differential MaxSAT Layer for SAT Solving Autor Zhang, Yu, Zhen, Hui-Ling, Yuan, Mingxuan, Yu, Bei

    ISSN: 1558-2434
    Vydavateľské údaje: ACM 27.10.2024
    “… To address this issue, numerous learning-driven methods have been proposed. However, these methods primarily focus on utilizing data-driven approaches to enhance…”
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  11. 11

    Navigational Instruction Generation as Inverse Reinforcement Learning with Neural Machine Translation Autor Daniele, Andrea F., Bansal, Mohit, Walter, Matthew R.

    ISBN: 9781450343367, 1450343368
    ISSN: 2167-2148
    Vydavateľské údaje: New York, NY, USA ACM 06.03.2017
    “…Modern robotics applications that involve human-robot interaction require robots to be able to communicate with humans seamlessly and effectively. Natural…”
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  12. 12

    LICS: Logic in Computer Security -- Some Attacker's Models and Related Decision Problems Autor Comon-Lundh, Hubert

    ISBN: 1479904139, 9781479904136
    ISSN: 1043-6871
    Vydavateľské údaje: IEEE 01.06.2013
    “…Logic plays an important role in formal aspects of computer security, for instance in access control, security of communications or even intrusion detection…”
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  13. 13

    Distributed regression: an efficient framework for modeling sensor network data Autor Guestrin, Carlos, Bodik, Peter, Thibaux, Romain, Paskin, Mark, Madden, Samuel

    ISBN: 1581138466, 9781581138467
    Vydavateľské údaje: New York, NY, USA ACM 26.04.2004
    “…We present distributed regression, an efficient and general framework for in-network modeling of sensor data. In this framework, the nodes of the sensor…”
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  14. 14

    Specification Test Compaction for Analog Circuits and MEMS Autor Biswas, Sounil, Li, Peng, Blanton, R. D. (Shawn), Pileggi, Larry T.

    ISBN: 9780769522883, 0769522882
    ISSN: 1530-1591
    Vydavateľské údaje: Washington, DC, USA IEEE Computer Society 07.03.2005
    Vydané v Design, Automation and Test in Europe (07.03.2005)
    “… required.We propose to eliminate redundant tests by employing ε-SVM based statistical learning.Application of the proposed methodology to an operational amplifier…”
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    Pueblo: A Modern Pseudo-Boolean SAT Solver Autor Sheini, Hossein M., Sakallah, Karem A.

    ISBN: 9780769522883, 0769522882
    ISSN: 1530-1591
    Vydavateľské údaje: Washington, DC, USA IEEE Computer Society 07.03.2005
    Vydané v Design, Automation and Test in Europe (07.03.2005)
    “… Its novel features include an efficient PB literal watching strategy and several PB learning methods that take advantage of the pruning power of PB constraints…”
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  16. 16

    DistHD: A Learner-Aware Dynamic Encoding Method for Hyperdimensional Classification Autor Wang, Junyao, Huang, Sitao, Imani, Mohsen

    Vydavateľské údaje: IEEE 09.07.2023
    “… Many applications exploit machine learning methodology to dissect collected data, and edge computing was introduced to enhance the efficiency and scalability in resource-constrained computing environments…”
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  17. 17

    Can Wear-Aware Memory Allocation be Intelligent? Autor Hakert, Christian, Chen, Kuan-Hsun, Chen, Jian-Jia

    Vydavateľské údaje: ACM 16.11.2020
    “… Therefore, we investigate the employment of a reinforcement learning agent as a substitute for such a strategy in this paper…”
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    DARL: Distributed Reconfigurable Accelerator for Hyperdimensional Reinforcement Learning Autor Chen, Hanning, Issa, Mariam, Ni, Yang, Imani, Mohsen

    ISSN: 1558-2434
    Vydavateľské údaje: ACM 29.10.2022
    “…Reinforcement Learning (RL) is a powerful technology to solve decision-making problems such as robotics control…”
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    Considering Circuit Observability Don't Cares in CNF Satisfiability Autor Fu, Zhaohui, Yu, Yinlei, Malik, Sharad

    ISBN: 9780769522883, 0769522882
    ISSN: 1530-1591
    Vydavateľské údaje: Washington, DC, USA IEEE Computer Society 07.03.2005
    Vydané v Design, Automation and Test in Europe (07.03.2005)
    “… However, this process loses some information regarding the structure of the circuit. One example of such structural information is the Circuit…”
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    A3C-S: Automated Agent Accelerator Co-Search towards Efficient Deep Reinforcement Learning Autor Fu, Yonggan, Zhang, Yongan, Li, Chaojian, Yu, Zhongzhi, Lin, Yingyan

    Vydavateľské údaje: IEEE 05.12.2021
    “…Driven by the explosive interest in applying deep reinforcement learning (DRL) agents to numerous real-time control and decision-making applications…”
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