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The Adaptive sampling revisited [PDF]
Discrete Mathematics & Theoretical Computer Science, 2019 The problem of estimating the number n of distinct keys of a large collection of N data is well known in computer science. A classical algorithm is the adaptive sampling (AS).
Matthew Drescher +2 more
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Computer-Vision-Oriented Adaptive Sampling in Compressive Sensing [PDF]
SensorsCompressive sensing (CS) is recognized for its adeptness at compressing signals, making it a pivotal technology in the context of sensor data acquisition.
Luyang Liu +4 more
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Application and comparison of several adaptive sampling algorithms in reduced order modeling [PDF]
HeliyonModel Order Reduction (MOR) techniques have extensive applications across scientific and engineering disciplines, such as neutron field reconstruction of nuclear reactor cores, thermoelastic field reconstruction, fluid, and solid mechanics.
Xirui Liu +3 more
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Nanopore adaptive sampling accurately detects nucleotide variants and improves the characterization of large‐scale rearrangement for the diagnosis of cancer predisposition [PDF]
Clinical and Translational MedicineBackground Molecular diagnosis has become highly significant for patient management in oncology. Methods Here, 30 well‐characterized clinical germline samples were studied with adaptive sampling to enrich the full sequence of 152 cancer predisposition ...
Sandy Chevrier +4 more
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Comparative evaluation of Oxford Nanopore Technologies’ adaptive sampling and the Twist long-read PGx panel for pharmacogenomic profiling [PDF]
Frontiers in PharmacologyClinical pharmacogenomics (PGx) testing strategies are mainly based on targeted PCR, microarrays, or short-read sequencing. These methods perform well for detecting known single-nucleotide variants (SNVs), small insertions/deletions (indels), and certain
Koen Deserranno +3 more
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Space-Fluid Adaptive Sampling by Self-Organisation [PDF]
Logical Methods in Computer Science, 2023 A recurrent task in coordinated systems is managing (estimating, predicting, or controlling) signals that vary in space, such as distributed sensed data or computation outcomes.
Roberto Casadei +4 more
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Adaptive Metrics for Adaptive Samples [PDF]
Algorithms, 2020 We generalize the local-feature size definition of adaptive sampling used in surface reconstruction to relate it to an alternative metric on Euclidean space. In the new metric, adaptive samples become uniform samples, making it simpler both to give adaptive sampling versions of homological inference results and to prove topological guarantees using the
Nicholas J. Cavanna, Donald R. Sheehy
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Non-adaptive adaptive sampling on turnstile streams [PDF]
Proceedings of the 52nd Annual ACM SIGACT Symposium on Theory of Computing, 2020 To appear at STOC ...
Sepideh Mahabadi +3 more
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Adaptive Sampling for Discovery
Advances in Neural Information Processing Systems 35, 2022 In this paper, we study a sequential decision-making problem, called Adaptive Sampling for Discovery (ASD). Starting with a large unlabeled dataset, algorithms for ASD adaptively label the points with the goal to maximize the sum of responses. This problem has wide applications to real-world discovery problems, for example drug discovery with the help ...
Ziping Xu +3 more
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Implicitly adaptive importance sampling [PDF]
Statistics and Computing, 2021 AbstractAdaptive importance sampling is a class of techniques for finding good proposal distributions for importance sampling. Often the proposal distributions are standard probability distributions whose parameters are adapted based on the mismatch between the current proposal and a target distribution.
Topi Paananen +3 more
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