The CCIMI blog

[Special Statslab Seminar] Scalable methods for machine learning optimisation

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On the Consistency of Supervised Learning with Missing Values

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[Special Statslab Seminar] Scalable stochastic optimization and large-scale data

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Nuisance parameters

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Explicit stabilised Runge-Kutta methods and their application to Bayesian inverse problems

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Analysis of Networks via the Sparse β-Model

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High-dimensional sign tests for the direction of a skewed single-spiked distribution

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On the fundamental understanding of distributed computation

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Post-selection confidence intervals and confidence curves

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Model selection with Lasso-Zero and a robust extension with an application to the problem of missing covariates

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