Search Results - computer program based data processing.

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Table of Contents: “.... -- 6.1 Introduction -- 6.1.1 Background -- 6.1.2 Literature review and classification of scheduling problems -- 6.1.3 The scheduling problems -- 6.1.4 Integrating scheduling in the big data environment -- 6.2 Satellite scheduling problems -- 6.2.1 Satellite range scheduling -- 6.2.2 Satellite downlink scheduling -- 6.2.3 Satellite broadcast scheduling -- 6.2.4 Satellite scheduling data download -- 6.2.5 Satellite scheduling at large scale -- 6.2.6 Satellite scheduling at small scale -- 6.2.7 Multisatellite scheduling -- 6.2.8 Multisatellite, multistation TT andamp -- C scheduling -- 6.2.9 Ground station scheduling -- 6.2.10 Low-earth-orbit satellite scheduling -- 6.2.11 Computational complexity of satellites scheduling -- 6.2.12 Satellite deployment systems -- 6.3 Spacecraft optimization problems -- 6.4 Computational complexity resolution methods -- 6.4.1 Local search methods -- 6.4.1.1 Hill climbing -- 6.4.1.2 Simulated annealing -- 6.4.1.3 Tabu search method -- 6.4.1.4 Genetic algorithms -- 6.4.1.5 Two-stage heuristic -- 6.4.1.6 An Improved differential evolution algorithm -- 6.4.1.6.1 Symbol definition -- 6.4.1.7 Multisatellite task prescheduling algorithm based on conflict imaging probability -- 6.5 Future trend of algorithms and models and solutions of satellite scheduling problem -- 6.6 Benchmarking and simulation platforms -- 6.7 Conclusions and future work -- Acknowledgments -- References -- 7 Colored Petri net modeling of the manufacturing processes of space instruments -- 7.1 Introduction -- 7.1.1 Development of Petri net....”
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Table of Contents: “...Proficiency Testing, Interlaboratory Comparisons, and Measurement Assurance Programs -- Proficiency Testing -- Measurement Assurance Programs -- Part IV. ...”
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Table of Contents: “...116 5.9.6 Limitation of quantum machine learning 116 5.9.7 Hardware constraints 117 5.9.8 Program restrictions 117 5.10 More on Quantum Computing and Machine Learning Connections 118 5.10.1 Wavefunction 118 5.10.2 The significance of accuracy 119 5.10.3 Data power and quantum machine learning 121 5.11 Case Study 123 5.11.1 Q-SVM (quantum support vector machine algorithm) 123 5.11.2 Why did they need Q-SVM? ...”
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Table of Contents: “...14 Certified robustness training -- 14.1 A framework for certified robust training -- 14.2 Existing algorithms and their performances -- Interval bound propagation (IBP) -- Linear relaxation-based training -- 14.3 Empirical comparison -- 14.4 Extended reading -- 15 Adversary detection -- 15.1 Detecting adversarial inputs -- 15.2 Detecting adversarial audio inputs -- 15.3 Detecting Trojan models -- 15.4 Extended reading -- 16 Adversarial robustness of beyond neural network models -- 16.1 Evaluating the robustness of K-nearest-neighbor models -- A primal-dual quadratic programming formulation -- Dual quadratic programming problems -- Robustness verification for 1-NN models -- Efficient algorithms for computing 1-NN robustness -- Extending beyond 1-NN -- Robustness of KNN vs neural network on simple problems -- 16.2 Defenses with nearest-neighbor classifiers -- 16.3 Evaluating the robustness of decision tree ensembles -- Robustness of a single decision tree -- Robustness of ensemble decision stumps -- Robustness of ensemble decision trees -- Training robust tree ensembles -- 17 Adversarial robustness in meta-learning and contrastive learning -- 17.1 Fast adversarial robustness adaptation in model-agnostic meta-learning -- When and how to incorporate robust regularization in MAML? ...”
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