We analyze algorithms to learn Gaussian Bayesian networks with known structure up to a bounded error in total variation distance.
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Jul 27, 2021 - Python
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sample-complexity
Here are 7 public repositories matching this topic...
OSRL (Optimal Representation Learning in Multi-Task Bandits) comprises an algorithm that addresses the problem of sample complexity with fixed confidence in Multi-Task Bandit problems. Published at the Thirty-Seventh AAAI Conference on Artificial Intelligence (AAAI23)
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Nov 28, 2022 - Python
Python implementation of algorithms for Best Policy Identification in Markov Decision Processes
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Jan 23, 2023 - Python
Code, data, and analysis for "Two spectral functionals set the exponential cost of shadow moment estimation" (Messerlian & Gu).
reproducible-researchquantum-computingquantum-informationquantum-tomographyqiskitrandomized-measurementssample-complexityu-statisticsclassical-shadowspurity-estimation
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Aug 15, 2026 - Python
Reproduction code for the paper 'Structure, Not Size: The Sample and Parameter Complexity of State Tracking in Selective State-Space Models' (selective PD-SSM / diagonal SSM / GRU state-tracking, MLX).
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Jul 2, 2026 - Python
An MLP hits a real sample-complexity wall learning sparse parities, with a Fourier-basis progress measure that sees it coming before the loss does
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Jul 10, 2026 - Python
Python utilities to compute a lower bound of the expected sample complexity to identify the best arm in a bandit model
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Sep 8, 2021 - Python
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