The sample complexity of a machine learning algorithm represents the number of training-samples that it needs in order to successfully learn a target...
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Daniel J. Russo and Benjamin Van Roy (2013), "Eluder Dimension and the Sample Complexity of Optimistic Exploration", Advances in Neural Information Processing...
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young vs. old bidders). The sample complexity of a random-sampling mechanism is the number of agents it needs to sample in order to attain a reasonable...
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quality assurance, and survey methodology, sampling is the selection of a subset or a statistical sample (termed sample for short) of individuals from within...
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the time complexity is the computational complexity that describes the amount of computer time it takes to run an algorithm. Time complexity is commonly...
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total variation distance between two sequences of n {\displaystyle n} samples is at least 1 − 2 δ {\displaystyle 1-2\delta } . This is because the total...
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Warmuth Occam learning Data mining Error tolerance (PAC learning) Sample complexity L. Valiant. A theory of the learnable. Communications of the ACM,...
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smallest and largest Ws. List of datasets for machine learning research Sample complexity Bayesian Optimization Reinforcement learning Improving Generalization...
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Z} . The Rademacher complexity of the function class F {\displaystyle {\mathcal {F}}} with respect to P {\displaystyle P} for sample size m {\displaystyle...
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(2013). "Boson-Sampling in the light of sample complexity". arXiv:1306.3995 [quant-ph]. Aaronson, Scott; Arkhipov, Alex (2013). "BosonSampling is far from...
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theory (a subfield of computer science and mathematics), the Kolmogorov complexity of an object, such as a piece of text, is the length of a shortest computer...
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BIC's penalty for model complexity is ln ( n ) k {\displaystyle \ln(n)k} , while AIC's is 2 k {\displaystyle 2k} . Large-sample asymptotic theory establishes...
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the Occam framework can be used to produce tighter bounds on the sample complexity of classical problems including conjunctions, conjunctions with few...
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from within each cluster (i.e. two-stage cluster sampling). Complexity. Cluster sampling is more sophisticated and requires more attention with how to...
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returns a sample from the distribution D {\displaystyle \textstyle D} . Sometimes the interest is, apart from measuring the time complexity, to measure...
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its policy immediately, have been mathematically studied proving sample complexity bounds for RLHF under different feedback models. In the offline data...
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Computational learning theory can assess learners by computational complexity, by sample complexity (how much data is required), or by other notions of optimization...
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2014). He received the best paper award at NeurIPS 2018. for work on sample complexity of distribution learning problems. He was the President of the Association...
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Vapnik–Chervonenkis dimension (category Measures of complexity)
Vapnik–Chervonenkis (VC) dimension is a measure of the size (capacity, complexity, expressive power, richness, or flexibility) of a class of sets. The notion...
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of examples needed: for every concept class, classical and quantum sample complexity are the same up to constant factors. However, for learning under some...
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The NASA-ESA Mars Sample Return is a proposed Flagship-class Mars sample return (MSR) mission to collect Martian rock and soil samples in 43 small, cylindrical...
118 KB (11,589 words) - 19:46, 3 August 2024
Prior-independent mechanism (category Sampling (statistics))
question in PIM design is: what is the sample complexity of the mechanism? I.e, how many agents it needs to sample in order to attain a reasonable approximation...
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Complex system (redirect from Complexity science)
and Complexity", exploring the diversity of problem types by contrasting problems of simplicity, disorganized complexity, and organized complexity. Weaver...
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of sparse (mostly zero) factors. As a result, it manages to reduce the complexity of computing the DFT from O ( n 2 ) {\textstyle O(n^{2})} , which arises...
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Sample entropy (SampEn) is a modification of approximate entropy (ApEn), used for assessing the complexity of physiological time-series signals, diagnosing...
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Proteomics (section Complexity of the problem)
analysis (see below). For the analysis of complex biological samples, a reduction of sample complexity is required. This may be performed off-line by one-dimensional...
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Standard deviation (redirect from Sample standard deviation)
not the number of samples N. The incremental method with reduced rounding errors can also be applied, with some additional complexity. A running sum of...
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In theoretical computer science, communication complexity studies the amount of communication required to solve a problem when the input to the problem...
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methods for obtaining random samples from a sequence of probability distributions with an increasing level of sampling complexity. These probabilistic models...
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Randomized algorithm (redirect from Randomized complexity)
Carlo algorithms are considered, and several complexity classes are studied. The most basic randomized complexity class is RP, which is the class of decision...
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