Search Results for author:
Found 8 papers, 2 papers with code
Quick Adaptive Ternary Segmentation: An Efficient Decoding Procedure For Hidden Markov Models
Hidden Markov models (HMMs) are characterized by an unobservable (hidden) Markov chain and an observable process, which is a noisy version of the hidden chain.
Optimistic search: Change point estimation for large-scale data via adaptive logarithmic queries
Change point estimation is often formulated as a search for the maximum of a gain function describing improved fits when segmenting the data.
Variational multiscale nonparametric regression: Algorithms
Many modern statistically efficient methods come with tremendous computational challenges, often leading to large scale optimization problems.
Computation Optimization and Control 62G05, 68U10
Seeded intervals and noise level estimation in change point detection: A discussion of Fryzlewicz (2020)
In this discussion, we compare the choice of seeded intervals and that of random intervals for change point segmentation from practical, statistical and computational perspectives.
Methodology Computation
Frame-constrained Total Variation Regularization for White Noise Regression
Despite the popularity and practical success of total variation (TV) regularization for function estimation, surprisingly little is known about its theoretical performance in a statistical setting.
Statistics Theory Statistics Theory 62G05, 62M40, 62G20
NETT: Solving Inverse Problems with Deep Neural Networks
Our theoretical results and framework are different from any previous work using neural networks for solving inverse problems.
The Essential Histogram
We define the essential histogram as the histogram in the confidence set with the fewest bins.
Statistics Theory Methodology Statistics Theory 62G10, 62H30
FDR-Control in Multiscale Change-point Segmentation
In this paper, we propose a multiscale segmentation method, FDRSeg, which controls the false discovery rate (FDR) in the sense that the number of false jumps is bounded linearly by the number of true jumps.
Statistics Theory Statistics Theory
