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Theory

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Papers

Deep Layer-wise Networks Have Closed-Form Weights AISTATS 2022
Analysis of a Target-Based Actor-Critic Algorithm with Linear Function Approximation AISTATS 2022
A Complete Characterisation of ReLU-Invariant Distributions AISTATS 2022
Standardisation-function Kernel Stein Discrepancy: A Unifying View on Kernel Stein Discrepancy Tests for Goodness-of-fit AISTATS 2022
Feature screening with kernel knockoffs AISTATS 2022
The Curse Revisited: When are Distances Informative for the Ground Truth in Noisy High-Dimensional Data? AISTATS 2022
Conditionally Gaussian PAC-Bayes AISTATS 2022
Randomized Stochastic Gradient Descent Ascent AISTATS 2022
Embedded Ensembles: infinite width limit and operating regimes AISTATS 2022
Finding Nearly Everything within Random Binary Networks AISTATS 2022
On Margins and Derandomisation in PAC-Bayes AISTATS 2022
An Information-Theoretic Justification for Model Pruning AISTATS 2022
How and When Random Feedback Works: A Case Study of Low-Rank Matrix Factorization AISTATS 2022
Denoising and change point localisation in piecewise-constant high-dimensional regression coefficients AISTATS 2022
Exploring Counterfactual Explanations Through the Lens of Adversarial Examples: A Theoretical and Empirical Analysis AISTATS 2022
Variational Autoencoders: A Harmonic Perspective AISTATS 2022
On the Consistency of Max-Margin Losses AISTATS 2022
A prior-based approximate latent Riemannian metric AISTATS 2022
On the Interplay between Information Loss and Operation Loss in Representations for Classification AISTATS 2022
Pulling back information geometry AISTATS 2022
Variational Gaussian Processes: A Functional Analysis View AISTATS 2022
How to scale hyperparameters for quickshift image segmentation AISTATS 2022
Weak Separation in Mixture Models and Implications for Principal Stratification AISTATS 2022
Almost Optimal Universal Lower Bound for Learning Causal DAGs with Atomic Interventions AISTATS 2022
Harmless interpolation in regression and classification with structured features AISTATS 2022