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11
Truncation Algorithms for Markov Chains and Processes.
Truncation Algorithms for Markov Chains and Processes.
Infanger, Alexander GerdDara. | Stanford University. | 2022
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12
Fundamental Limits of Caching: Symmetry Structure and Coded Placement Schemes.
Fundamental Limits of Caching: Symmetry Structure and Coded Placement Schemes.
Zhang, Kai.Electrical and Computer Engineering. | Texas A&M University. | 2020
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13
Control, Filtering, Learning, and Multi-Robot Algorithms for Large Graph-Based Markov Decision Processes.
Control, Filtering, Learning, and Multi-Robot Algorithms for Large Graph-Based Markov Decision Processes.
Haksar, Ravi N. | Stanford University. | 2020
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14
Uniqueness for Continuous Superresolution by Means of Choquet Theory and Geometric Measure Theory.
Uniqueness for Continuous Superresolution by Means of Choquet Theory and Geometric Measure Theory.
Cinoman, Ryan M.Mathematics. | University of Maryland, College Park. | 2021
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15
Safety Enhanced Designs in UAS Risk Monitoring and Collision Resolution.
Safety Enhanced Designs in UAS Risk Monitoring and Collision Resolution.
Wang, Weichang.Electrical Engineering. | Arizona State University. | 2021
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16
Designing Scheduling Algorithms via a Mathematical Perspective.
Designing Scheduling Algorithms via a Mathematical Perspective.
Davies, Sami.Mathematics. | University of Washington. | 2021
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17
Mathematical Modeling in Dairy Cattle - Nonlinear Ration Formulation, Thermal Balance, Emission and Excretion Models.
Mathematical Modeling in Dairy Cattle - Nonlinear Ration Formulation, Thermal Balance, Emission and Excretion Models.
Li, Jinghui.Animal Biology. | University of California, Davis. | 2021
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18
Making Bayesian Optimization Practical in the Context of High Dimensional, Highly Expensive, Black­Box Functions.
Making Bayesian Optimization Practical in the Context of High Dimensional, Highly Expensive, Black­Box Functions.
Mathesen, Logan.Industrial Engineering. | Arizona State University. | 2021
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19
Can We Trust AI? Towards Practical Implementation and Theoretical Analysis in Trustworthy Machine Learning.
Can We Trust AI? Towards Practical Implementation and Theoretical Analysis in Trustworthy Machine Learning.
Xu, Kaidi.Electrical and Computer Engineering. | Northeastern University. | 2021
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20
Upper Tails of Subgraph Counts in Sparse Regular Graphs.
Upper Tails of Subgraph Counts in Sparse Regular Graphs.
Gunby, Benjamin.Mathematics. | Harvard University. | 2021
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