77 citations · 219 across the 17 of their papers we have counts for
18 papers
A scalable clustering algorithm to approximate graph cuts
Leo Suchan, Housen Li, Axel Munk
Due to their computational complexity, graph cuts for cluster detection and identification are used mostly in the form of convex relaxations. We propose to utilize the original gra…
Quick Adaptive Ternary Segmentation: An Efficient Decoding Procedure For Hidden Markov Models
Alexandre Mösching, Housen Li, Axel Munk
Hidden Markov models (HMMs) are characterized by an unobservable Markov chain and an observable process -- a noisy version of the hidden chain. Decoding the original signal from th…
Adaptive minimax optimality in statistical inverse problems via SOLIT -- Sharp Optimal Lepskii-Inspired Tuning
Housen Li, Frank Werner
We consider statistical linear inverse problems in separable Hilbert spaces and filter-based reconstruction methods of the form , where is t…
A Variational View on Statistical Multiscale Estimation
Markus Haltmeier, Housen Li, Axel Munk
We present a unifying view on various statistical estimation techniques including penalization, variational and thresholding methods. These estimators will be analyzed in the conte…
Variational Multiscale Nonparametric Regression: Algorithms and Implementation
Miguel del Alamo, Housen Li, Axel Munk +1
Many modern statistically efficient methods come with tremendous computational challenges, often leading to large-scale optimisation problems. In this work, we examine such computa…
Optimistic search: Change point estimation for large-scale data via adaptive logarithmic queries
Solt Kovács, Housen Li, Lorenz Haubner +2
Change point estimation is often formulated as a search for the maximum of a gain function describing improved fits when segmenting the data. Searching through all candidates requi…
Seeded intervals and noise level estimation in change point detection: A discussion of Fryzlewicz (2020)
Solt Kovács, Housen Li, Peter Bühlmann
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.…
Seeded Binary Segmentation: A general methodology for fast and optimal change point detection
Solt Kovács, Housen Li, Peter Bühlmann +1
In recent years, there has been an increasing demand on efficient algorithms for large scale change point detection problems. To this end, we propose seeded binary segmentation, an…
Frame-constrained Total Variation Regularization for White Noise Regression
Miguel del Álamo, Housen Li, Axel Munk
Despite the popularity and practical success of total variation (TV) regularization for function estimation, surprisingly little is known about its theoretical performance in a sta…
A linear time algorithm for multiscale quantile simulation
Chengcheng Huang, Housen Li, Lizhi Cheng +1
Change-point problems have appeared in a great many applications for example cancer genetics, econometrics and climate change. Modern multiscale type segmentation methods are consi…
NETT: Solving Inverse Problems with Deep Neural Networks
Housen Li, Johannes Schwab, Stephan Antholzer +1
Recovering a function or high-dimensional parameter vector from indirect measurements is a central task in various scientific areas. Several methods for solving such inverse proble…
The Averaged Kaczmarz Iteration for Solving Inverse Problems
Housen Li, Markus Haltmeier
We introduce a new iterative regularization method for solving inverse problems that can be written as systems of linear or non-linear equations in Hilbert spaces. The proposed ave…
Multiscale Change-point Segmentation: Beyond Step Functions
Housen Li, Qinghai Guo, Axel Munk
Modern multiscale type segmentation methods are known to detect multiple change-points with high statistical accuracy, while allowing for fast computation. Underpinning theory has…
Empirical Risk Minimization as Parameter Choice Rule for General Linear Regularization Methods
Housen Li, Frank Werner
We consider the statistical inverse problem to recover from noisy measurements where is Gaussian white noise and a compact operator between Hilbert spaces…
The Essential Histogram
Housen Li, Axel Munk, Hannes Sieling +1
The histogram is widely used as a simple, exploratory display of data, but it is usually not clear how to choose the number and size of bins. We construct a confidence set of distr…
Variational Multiscale Nonparametric Regression: Smooth Functions
Markus Grasmair, Housen Li, Axel Munk
For the problem of nonparametric regression of smooth functions, we reconsider and analyze a constrained variational approach, which we call the MultIscale Nemirovski-Dantzig (MIND…
FDR-Control in Multiscale Change-point Segmentation
Housen Li, Axel Munk, Hannes Sieling
Fast multiple change-point segmentation methods, which additionally provide faithful statistical statements on the number, locations and sizes of the segments, have recently receiv…
Aggregated motion estimation for real-time MRI reconstruction
Housen Li, Markus Haltmeier, Shuo Zhang +2
Real-time magnetic resonance imaging (MRI) methods generally shorten the measuring time by acquiring less data than needed according to the sampling theorem. In order to obtain a p…