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Showing 1 to 4 of 4 for “"Computational lower bounds"”.
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Reducibility and computational lower bounds for problems with planted sparse structure
… has gravitated towards exploring statistical-computational gaps induced by sparsity. A line of work initiated by Berthet and Rigollet has aimed to explain these gaps through reductions to conjecturally hard problems from complexity theory. However, the delicate nature of average-case …
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Statistical Inference and the Sum of Squares Method
… Often, the main challenges are inherently computational: the problems are well understood from a purely statistical perspective, but key statistical primitives -- likelihood ratios, Bayes-optimal estimators, etc. -- are intractable to compute on large and high-dimensional data sets. We …
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Reducibility and Statistical-Computational Gaps from Secret Leakage
Inference problems with conjectured statistical-computational gaps are ubiquitous throughout modern statistics, computer science, statistical physics and discrete probability. While there has been success evidencing these gaps from the failure of restricted classes of algorithms, progress towards a …
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Optimal estimation in high-dimensional and nonparametric models
… these methods and establishes whether those are computationally tractable. In the first chapter, a new estimator for the volume of a convex set is proposed. The estimator is minimax optimal and also efficient non-asymptotically: it is nearly unbiased with minimal variance among all unbiased …