ML
- Monograph on Linearised Neural Networks (fantastic exposition of fundamentals of kernel ridge regression along the way)
- Diffusion models on the simplex
- Tensor Decomposition with individual heterogeneity
- Inference via randomised algorithms (eg sketching) - is this basically subsampling?
- adaptive estimation of density ratios
- adaptive experimentation under nonstationarity