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Martin Wahl

  1. Non-asymptotic upper bounds for the reconstruction error of PCA
    2016/09/13 by Markus Reiß, Martin Wahl, Reiß, Markus +1 · 3 citations
    Mathematics · #15A42 #60F10 (secondary) #62H25 (Primary) #FOS: Mathematics #Statistics Theory (math.ST) #math.ST #msc:15A42 #msc:60F10 #msc:62H25 #stat.TH
  2. Perturbation bounds for eigenspaces under a relative gap condition
    2018/03/10 by Moritz Jirak, Martin Wahl, Jirak, Moritz +1 · 3 citations
    Mathematics · #15A42 #47A55 #62H25 #FOS: Mathematics #Functional Analysis (math.FA) #Probability (math.PR) #math.FA #math.PR #msc:15A42 #msc:47A55 #msc:62H25
  3. Relative perturbation bounds with applications to empirical covariance operators
    2018/02/08 by Moritz Jirak, Martin Wahl, Jirak, Moritz +1 · 2 citations
    Medicine · Mathematics · #Bone health and treatments #Spectral Theory in Mathematical Physics #Mathematical Approximation and Integration
  4. Quantitative limit theorems and bootstrap approximations for empirical spectral projectors
    2022/08/26 by Moritz Jirak, Martin Wahl, Jirak, Moritz +1 · 2 citations
    Mathematics · #FOS: Mathematics #Mathematical Analysis and Transform Methods #Numerical methods in inverse problems #Probability (math.PR) #Spectral Theory in Mathematical Physics #Statistics Theory (math.ST)
  5. Optimal parameter estimation for linear SPDEs from multiple measurements
    2022/11/04 by Randolf Altmeyer, Altmeyer, Randolf, Anton Tiepner +3 · 2 citations
    Economics, Econometrics and Finance · Environmental Science · #60F05 #60H15 #62F12 #62F35 #Atmospheric and Environmental Gas Dynamics #FOS: Mathematics #Probability (math.PR) #Statistics Theory (math.ST) #Stochastic processes and financial applications
  6. Analyzing the discrepancy principle for kernelized spectral filter learning algorithms
    2020/04/10 by Alain Célisse, Celisse, Alain, Martin Wahl +1 · 1 citation
    Computer Science · Engineering · Mathematics · #FOS: Computer and information sciences #FOS: Mathematics #Machine Learning (stat.ML) #Machine Learning and ELM #Sparse and Compressive Sensing Techniques #Statistical Methods and Inference #Statistics Theory (math.ST) #Stochastic Gradient Optimization Techniques
  7. Van Trees inequality, group equivariance, and estimation of principal subspaces
    2021/07/19 by Martin Wahl, Wahl, Martin · 1 citation
    Mathematics · #62B10 #62H25 #FOS: Mathematics #Graph theory and applications #Point processes and geometric inequalities #Statistical Methods and Inference #Statistics Theory (math.ST)
  8. Variable selection in high-dimensional additive models based on norms of projections
    2014/05/31 by Martin Wahl, Wahl, Martin · 1 citation
    Computer Science · Mathematics · #Advanced Statistical Methods and Models #Bayesian Methods and Mixture Models #Statistical Methods and Inference #math.ST #msc:62G05 #msc:62G08 #msc:94A12 #stat.TH
  9. Concentration and moment inequalities for sums of independent heavy-tailed random matrices
    2024/07/17 by Moritz Jirak, Jirak, Moritz, Stanislav Minsker +5 · 1 citation
    Mathematics · Decision Sciences · #Random Matrices and Applications #Probability and Risk Models #Stochastic processes and statistical mechanics