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Machine learning under resource constraints Fundamentals / / edited by Katharina Morik and Peter Marwedel
| Machine learning under resource constraints Fundamentals / / edited by Katharina Morik and Peter Marwedel |
| Edizione | [1st ed.] |
| Pubbl/distr/stampa | Berlin ; ; Boston : , : De Gruyter, , [2023] |
| Descrizione fisica | 1 online resource (xiii, 491 pages) : illustrations (chiefly colour) |
| Disciplina | 006.31 |
| Collana | De Gruyter STEM |
| Soggetto topico |
Machine learning
SCIENCE / Chemistry / General |
| Soggetto non controllato |
Artificial Intelligence
Big Data and Machine Learning Cyber-physical systems Data mining for Ubiquitous System Software Embedded Systems and Machine Learning Highly Distributed Data ML on Small devices Machine learning for knowledge discovery Machine learning in high-energy physics Resource-Aware Machine Learning Resource-Constrained Data Analysis |
| ISBN | 3-11-078594-3 |
| Formato | Materiale a stampa  |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | ; 1 Introduction / Katharina Morik, Jian-Jia Chen -- ; 1.1 Embedded Systems and Sustainability -- ; 1.2 The Energy Consumption of Machine Learning -- ; 1.3 Memory Demands of Machine Learning -- ; 1.4 Structure of this Book -- ; 2 Data Gathering and Resource Measuring -- ; 2.1 Declarative Stream-Based Acquisition and Processing of OS Data with kCQL / Christoph Borchert, Jochen Streicher, Alexander Lochmann,Olaf Spinczyk -- ; 2.2 PhyNetLab Test Bed / Mojtaba Masoudinejad, Markus Buschhoff -- ; 2.3 Zero-Power/Low-Power Sensing / Andres Gomez, Lars Suter, Simon Mayer -- ; 3 Streaming Data, Small Devices -- ; 3.1 Summary Extraction from Streams / Sebastian Buschjäger, Katharina Morik -- ; 3.2 Coresets and Sketches for Regression Problems on Data Streams and Distributed Data / Alexander Munteanu -- ; 4 Structured Data -- ; 4.1 Spatio-Temporal Random Fields / Nico Piatkowski, Katharina Morik -- ; 4.2 The Weisfeiler-Leman Method for Machine Learning with Graphs / Nils Kriege, Christopher Morris -- ; 4.3 Deep Graph Representation Learning / Matthias Fey, Frank Weichert -- ; 4.4 High-Quality Parallel Max-Cut Approximation Algorithms for Shared Memory / Nico Bertram, Jonas Ellert, Johannes Fischer -- ; 4.5 Millions of Formulas / Lukas Pfahler -- ; 5 Cluster Analysis -- ; 5.1 Sparse Partitioning Around Medoids / Lars Lenssen, Erich Schubert -- ; 5.2 Clustering of Polygonal Curves and Time Series / Amer Krivošija -- ; 5.3 Data Aggregation for Hierarchical Clustering / Erich Schubert, Andreas Lang -- ; 5.4 Matrix Factorization with Binary Constraints / Sibylle Hess ; 6 Hardware-Aware Execution -- ; 6.1 FPGA-Based Backpropagation Engine for Feed-Forward Neural Networks / Wayne Luk, Ce Guo -- ; 6.2 Processor-Specific Code Transformation / Henning Funke, Jens Teubner -- ; 6.3 Extreme Multicore Classification / Erik Schultheis, Rohit Babbar -- ; 6.4 Optimization of ML on Modern Multicore Systems / Helena Kotthaus, Peter Marwedel -- 7 Memory Awareness -- ; 7.1 Efficient Memory Footprint Reduction / Helena Kotthaus, Peter Marwedel -- ; 7.2 Machine Learning Based on Emerging Memories / Mikail Yayla, Sebastian Buschjäger, Hussam Amrouch -- ; 7.3 Cache-Friendly Execution of Tree Ensembles / Sebastian Buschjäger, Kuan-Hsun Chen -- ; 8 Communication Awareness -- ; 8.1 Timing-Predictable Learning and Multiprocessor Synchronization / Kuan-Hsun Chen, Junjie Shi -- ; 8.2 Communication Architecture for Heterogeneous Hardware / Henning Funke, Jens Teubner -- ; 9 Energy Awareness -- ; 9.1 Integer Exponential Families / Nico Piatkowski -- ; 9.2 Power Consumption Analysis and Uplink Transmission Power / Robert Falkenberg. |
| Record Nr. | UNISA-996503570003316 |
| Berlin ; ; Boston : , : De Gruyter, , [2023] | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. di Salerno | ||
| ||
Machine learning under resource constraints Fundamentals / / edited by Katharina Morik and Peter Marwedel
| Machine learning under resource constraints Fundamentals / / edited by Katharina Morik and Peter Marwedel |
| Edizione | [1st ed.] |
| Pubbl/distr/stampa | Berlin ; ; Boston : , : De Gruyter, , [2023] |
| Descrizione fisica | 1 online resource (xiii, 491 pages) : illustrations (chiefly colour) |
| Disciplina | 006.31 |
| Collana | De Gruyter STEM |
| Soggetto topico |
Machine learning
SCIENCE / Chemistry / General |
| Soggetto non controllato |
Artificial Intelligence
Big Data and Machine Learning Cyber-physical systems Data mining for Ubiquitous System Software Embedded Systems and Machine Learning Highly Distributed Data ML on Small devices Machine learning for knowledge discovery Machine learning in high-energy physics Resource-Aware Machine Learning Resource-Constrained Data Analysis |
| ISBN | 3-11-078594-3 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | ; 1 Introduction / Katharina Morik, Jian-Jia Chen -- ; 1.1 Embedded Systems and Sustainability -- ; 1.2 The Energy Consumption of Machine Learning -- ; 1.3 Memory Demands of Machine Learning -- ; 1.4 Structure of this Book -- ; 2 Data Gathering and Resource Measuring -- ; 2.1 Declarative Stream-Based Acquisition and Processing of OS Data with kCQL / Christoph Borchert, Jochen Streicher, Alexander Lochmann,Olaf Spinczyk -- ; 2.2 PhyNetLab Test Bed / Mojtaba Masoudinejad, Markus Buschhoff -- ; 2.3 Zero-Power/Low-Power Sensing / Andres Gomez, Lars Suter, Simon Mayer -- ; 3 Streaming Data, Small Devices -- ; 3.1 Summary Extraction from Streams / Sebastian Buschjäger, Katharina Morik -- ; 3.2 Coresets and Sketches for Regression Problems on Data Streams and Distributed Data / Alexander Munteanu -- ; 4 Structured Data -- ; 4.1 Spatio-Temporal Random Fields / Nico Piatkowski, Katharina Morik -- ; 4.2 The Weisfeiler-Leman Method for Machine Learning with Graphs / Nils Kriege, Christopher Morris -- ; 4.3 Deep Graph Representation Learning / Matthias Fey, Frank Weichert -- ; 4.4 High-Quality Parallel Max-Cut Approximation Algorithms for Shared Memory / Nico Bertram, Jonas Ellert, Johannes Fischer -- ; 4.5 Millions of Formulas / Lukas Pfahler -- ; 5 Cluster Analysis -- ; 5.1 Sparse Partitioning Around Medoids / Lars Lenssen, Erich Schubert -- ; 5.2 Clustering of Polygonal Curves and Time Series / Amer Krivošija -- ; 5.3 Data Aggregation for Hierarchical Clustering / Erich Schubert, Andreas Lang -- ; 5.4 Matrix Factorization with Binary Constraints / Sibylle Hess ; 6 Hardware-Aware Execution -- ; 6.1 FPGA-Based Backpropagation Engine for Feed-Forward Neural Networks / Wayne Luk, Ce Guo -- ; 6.2 Processor-Specific Code Transformation / Henning Funke, Jens Teubner -- ; 6.3 Extreme Multicore Classification / Erik Schultheis, Rohit Babbar -- ; 6.4 Optimization of ML on Modern Multicore Systems / Helena Kotthaus, Peter Marwedel -- 7 Memory Awareness -- ; 7.1 Efficient Memory Footprint Reduction / Helena Kotthaus, Peter Marwedel -- ; 7.2 Machine Learning Based on Emerging Memories / Mikail Yayla, Sebastian Buschjäger, Hussam Amrouch -- ; 7.3 Cache-Friendly Execution of Tree Ensembles / Sebastian Buschjäger, Kuan-Hsun Chen -- ; 8 Communication Awareness -- ; 8.1 Timing-Predictable Learning and Multiprocessor Synchronization / Kuan-Hsun Chen, Junjie Shi -- ; 8.2 Communication Architecture for Heterogeneous Hardware / Henning Funke, Jens Teubner -- ; 9 Energy Awareness -- ; 9.1 Integer Exponential Families / Nico Piatkowski -- ; 9.2 Power Consumption Analysis and Uplink Transmission Power / Robert Falkenberg. |
| Record Nr. | UNINA-9910774817103321 |
| Berlin ; ; Boston : , : De Gruyter, , [2023] | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Machine Learning under Resource Constraints. Discovery in Physics / / ed. by Katharina Morik, Wolfgang Rhode
| Machine Learning under Resource Constraints. Discovery in Physics / / ed. by Katharina Morik, Wolfgang Rhode |
| Edizione | [1st ed.] |
| Pubbl/distr/stampa | Berlin ; ; Boston : , : De Gruyter, , [2022] |
| Descrizione fisica | 1 online resource (XIV, 349 p.) |
| Disciplina | 006.31 |
| Collana | De Gruyter STEM |
| Soggetto topico | SCIENCE / Chemistry / General |
| Soggetto non controllato |
Artificial Intelligence
Big Data and Machine Learning Cyber-physical systems Data mining for Ubiquitous System Software Embedded Systems and Machine Learning Highly Distributed Data ML on Small devices Machine learning for knowledge discovery Machine learning in high-energy physics Resource-Aware Machine Learning Resource-Constrained Data Analysis |
| ISBN | 3-11-078596-X |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Frontmatter -- Contents -- 1 Introduction -- 2 Challenges in Particle and Astroparticle Physics -- 3 Key Concepts in Machine Learning and Data Analysis -- 4 Data Acquisition and Data Structure -- 5 Monte Carlo Simulations -- 6 Data Storage and Access -- 7 Monitoring and Feature Extraction -- 8 Event Property Estimation and Signal Background Separation -- 9 Deep Learning Applications -- 10 Inverse Problems -- Bibliography -- Index -- List of Contributors |
| Record Nr. | UNISA-996503570203316 |
| Berlin ; ; Boston : , : De Gruyter, , [2022] | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. di Salerno | ||
| ||
Machine Learning under Resource Constraints. Applications / / ed. by Katharina Morik, Christian Wietfeld, Jörg Rahnenführer
| Machine Learning under Resource Constraints. Applications / / ed. by Katharina Morik, Christian Wietfeld, Jörg Rahnenführer |
| Edizione | [1st ed.] |
| Pubbl/distr/stampa | Berlin ; ; Boston : , : De Gruyter, , [2022] |
| Descrizione fisica | 1 online resource (VIII, 470 p.) |
| Disciplina | 006.31 |
| Collana | De Gruyter STEM |
| Soggetto topico | SCIENCE / Chemistry / General |
| Soggetto non controllato |
Artificial Intelligence
Big Data and Machine Learning Cyber-physical systems Data mining for Ubiquitous System Software Embedded Systems and Machine Learning Highly Distributed Data ML on Small devices Machine learning for knowledge discovery Machine learning in high-energy physics Resource-Aware Machine Learning Resource-Constrained Data Analysis |
| ISBN | 3-11-078598-6 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Frontmatter -- Contents -- 1 Editorial -- 2 Health / Medicine -- 2.1 Machine Learning in Medicine -- 2.2 Virus Detection -- 2.3 Cancer Diagnostics and Therapy from Molecular Data -- 2.4 Bayesian Analysis for Dimensionality and Complexity Reduction -- 2.5 Survival Prediction and Model Selection -- 2.6 Protein Complex Similarity -- 3 Industry 4.0 -- 3.1 Keynote on Industry 4.0 -- 3.2 Quality Assurance in Interlinked Manufacturing Processes -- 3.3 Label Proportion Learning -- 3.4 Simulation and Machine Learning -- 3.5 High-Precision Wireless Localization -- 3.6 Indoor Photovoltaic Energy Harvesting -- 3.7 Micro-UAV Swarm Testbed for Indoor Applications -- 4 Smart City and Traffic -- 4.1 Inner-City Traffic Flow Prediction with Sparse Sensors -- 4.2 Privacy-Preserving Detection of Persons and Classification of Vehicle Flows -- 4.3 Green Networking and Resource Constrained Clients for Smart Cities -- 4.4 Vehicle to Vehicle Communications: Machine Learning-Enabled Predictive Routing -- 4.5 Modelling of Hybrid Vehicular Traffic with Extended Cellular Automata -- 4.6 Embedded Crowdsensing for Pavement Monitoring and its Incentive Mechanisms -- 5 Communication Networks -- 5.1 Capacity Analysis of IoT Networks in the Unlicensed Spectrum -- 5.2 Resource-Efficient Vehicle-to-Cloud Communications -- 5.3 Mobile-Data Network Analytics Highly Reliable Networks -- 5.4 Machine Learning-Enabled 5G Network Slicing -- 5.5 Potential of Millimeter Wave Communications -- 6 Privacy -- 6.1 Keynote: Construction of Inference-Proof Agent Interactions -- Bibliography -- Index -- List of Contributors |
| Record Nr. | UNISA-996503570503316 |
| Berlin ; ; Boston : , : De Gruyter, , [2022] | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. di Salerno | ||
| ||
Machine Learning under Resource Constraints. Discovery in Physics / / ed. by Katharina Morik, Wolfgang Rhode
| Machine Learning under Resource Constraints. Discovery in Physics / / ed. by Katharina Morik, Wolfgang Rhode |
| Edizione | [1st ed.] |
| Pubbl/distr/stampa | Berlin ; ; Boston : , : De Gruyter, , [2022] |
| Descrizione fisica | 1 online resource (XIV, 349 p.) |
| Disciplina | 006.31 |
| Collana | De Gruyter STEM |
| Soggetto topico | SCIENCE / Chemistry / General |
| Soggetto non controllato |
Artificial Intelligence
Big Data and Machine Learning Cyber-physical systems Data mining for Ubiquitous System Software Embedded Systems and Machine Learning Highly Distributed Data ML on Small devices Machine learning for knowledge discovery Machine learning in high-energy physics Resource-Aware Machine Learning Resource-Constrained Data Analysis |
| ISBN | 3-11-078596-X |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Frontmatter -- Contents -- 1 Introduction -- 2 Challenges in Particle and Astroparticle Physics -- 3 Key Concepts in Machine Learning and Data Analysis -- 4 Data Acquisition and Data Structure -- 5 Monte Carlo Simulations -- 6 Data Storage and Access -- 7 Monitoring and Feature Extraction -- 8 Event Property Estimation and Signal Background Separation -- 9 Deep Learning Applications -- 10 Inverse Problems -- Bibliography -- Index -- List of Contributors |
| Record Nr. | UNINA-9910774815003321 |
| Berlin ; ; Boston : , : De Gruyter, , [2022] | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Machine Learning under Resource Constraints. Applications / / ed. by Katharina Morik, Christian Wietfeld, Jörg Rahnenführer
| Machine Learning under Resource Constraints. Applications / / ed. by Katharina Morik, Christian Wietfeld, Jörg Rahnenführer |
| Edizione | [1st ed.] |
| Pubbl/distr/stampa | Berlin ; ; Boston : , : De Gruyter, , [2022] |
| Descrizione fisica | 1 online resource (VIII, 470 p.) |
| Disciplina | 006.31 |
| Collana | De Gruyter STEM |
| Soggetto topico | SCIENCE / Chemistry / General |
| Soggetto non controllato |
Artificial Intelligence
Big Data and Machine Learning Cyber-physical systems Data mining for Ubiquitous System Software Embedded Systems and Machine Learning Highly Distributed Data ML on Small devices Machine learning for knowledge discovery Machine learning in high-energy physics Resource-Aware Machine Learning Resource-Constrained Data Analysis |
| ISBN | 3-11-078598-6 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Frontmatter -- Contents -- 1 Editorial -- 2 Health / Medicine -- 2.1 Machine Learning in Medicine -- 2.2 Virus Detection -- 2.3 Cancer Diagnostics and Therapy from Molecular Data -- 2.4 Bayesian Analysis for Dimensionality and Complexity Reduction -- 2.5 Survival Prediction and Model Selection -- 2.6 Protein Complex Similarity -- 3 Industry 4.0 -- 3.1 Keynote on Industry 4.0 -- 3.2 Quality Assurance in Interlinked Manufacturing Processes -- 3.3 Label Proportion Learning -- 3.4 Simulation and Machine Learning -- 3.5 High-Precision Wireless Localization -- 3.6 Indoor Photovoltaic Energy Harvesting -- 3.7 Micro-UAV Swarm Testbed for Indoor Applications -- 4 Smart City and Traffic -- 4.1 Inner-City Traffic Flow Prediction with Sparse Sensors -- 4.2 Privacy-Preserving Detection of Persons and Classification of Vehicle Flows -- 4.3 Green Networking and Resource Constrained Clients for Smart Cities -- 4.4 Vehicle to Vehicle Communications: Machine Learning-Enabled Predictive Routing -- 4.5 Modelling of Hybrid Vehicular Traffic with Extended Cellular Automata -- 4.6 Embedded Crowdsensing for Pavement Monitoring and its Incentive Mechanisms -- 5 Communication Networks -- 5.1 Capacity Analysis of IoT Networks in the Unlicensed Spectrum -- 5.2 Resource-Efficient Vehicle-to-Cloud Communications -- 5.3 Mobile-Data Network Analytics Highly Reliable Networks -- 5.4 Machine Learning-Enabled 5G Network Slicing -- 5.5 Potential of Millimeter Wave Communications -- 6 Privacy -- 6.1 Keynote: Construction of Inference-Proof Agent Interactions -- Bibliography -- Index -- List of Contributors |
| Record Nr. | UNINA-9910774815903321 |
| Berlin ; ; Boston : , : De Gruyter, , [2022] | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||