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We consider the problem of Bayesian optimization of a one-dimensional Brownian motion in which the $T$ adaptively chosen observations are corrupted by Gaussian noise. We show that as the smallest possible expected cumulative regret and the…

Machine Learning · Computer Science 2022-01-19 Zexin Wang , Vincent Y. F. Tan , Jonathan Scarlett

We consider the problem of detecting the locations of targets in the far field by sending probing signals from an antenna array and recording the reflected echoes. Drawing on key concepts from the area of compressive sensing, we use an…

Information Theory · Computer Science 2013-04-25 Max Hügel , Holger Rauhut , Thomas Strohmer

We define several new models for how to define anomalous regions among enormous sets of trajectories. These are based on spatial scan statistics, and identify a geometric region which captures a subset of trajectories which are…

Data Structures and Algorithms · Computer Science 2019-06-06 Michael Matheny , Dong Xie , Jeff M. Phillips

We obtain rates of convergence to stationarity in L^1-Wasserstein distance for a d-dimensional reflected Brownian motion (RBM) in the nonnegative orthant that are explicit in the dimension and the system parameters. The results are then…

Probability · Mathematics 2019-12-04 Sayan Banerjee , Amarjit Budhiraja

The study of motion in animals and robots has been aided by insights from geometric mechanics. In friction dominated systems, a mechanical "connection" can provide a high fidelity mechanical model. The connection is a co-vector (Lie…

Biological Physics · Physics 2018-01-26 Brian A. Bittner , Ross L. Hatton , Shai Revzen

Sparse reduced-rank regression is an important tool to uncover meaningful dependence structure between large numbers of predictors and responses in many big data applications such as genome-wide association studies and social media…

Methodology · Statistics 2016-08-15 Mohammad Taha Bahadori , Zemin Zheng , Yan Liu , Jinchi Lv

We study properties of the random metric space called the Brownian map. For every h>0, we consider the connected components of the complement of the open ball of radius h centered at the root, and we let N(h,r) be the number of those…

Probability · Mathematics 2013-09-02 Jean-François Le Gall

Let $\{U^N_t\}_{t\ge 0}$ be a standard Brownian motion on $\mathbb{U}(N)$. For fixed $N\in\mathbb{N}$ and $t>0$, we give explicit bounds on the $L_1$-Wasserstein distance of the empirical spectral measure of $U^N_t$ to both the…

Probability · Mathematics 2018-02-14 Elizabeth Meckes , Tai Melcher

Existing techniques for motion imitation often suffer a certain level of latency due to their computational overhead or a large set of correspondence samples to search. To achieve real-time imitation with small latency, we present a…

Robotics · Computer Science 2016-07-26 Shuo Jin , Chengkai Dai , Yang Liu , Charlie C. L. Wang

Conformal prediction constructs a confidence set for an unobserved response of a feature vector based on previous identically distributed and exchangeable observations of responses and features. It has a coverage guarantee at any nominal…

Machine Learning · Statistics 2022-12-08 Eugene Ndiaye , Ichiro Takeuchi

We develop constrained Bayesian estimation methods for small area problems: those requiring smoothness with respect to similarity across areas, such as geographic proximity or clustering by covariates; and benchmarking constraints,…

Methodology · Statistics 2014-10-28 Rebecca C. Steorts

This paper continues a study on trajectories of Brownian Motion in a field of soft trap whose radius distribution is unbounded. We show here for both point-to-point and point-to-plane model the volume exponent (the exponent associated to…

Probability · Mathematics 2015-05-28 Hubert Lacoin

Deciding what to sense is a crucial task, made harder by dependencies and by a nonadditive utility function. We develop approximation algorithms for selecting an optimal set of measurements, under a dependency structure modeled by a…

Artificial Intelligence · Computer Science 2012-06-18 Yan Radovilsky , Solomon Eyal Shimony

This paper considers an ergodic version of the bounded velocity follower problem, assuming that the decision maker lacks knowledge of the underlying system parameters and must learn them while simultaneously controlling. We propose…

Machine Learning · Statistics 2024-10-07 Stefan Ankirchner , Sören Christensen , Jan Kallsen , Philip Le Borne , Stefan Perko

The movement of a particle described by Brownian motion is quantified by a single parameter, $D$, the diffusion constant. The estimation of $D$ from a discrete sequence of noisy observations is a fundamental problem in biological single…

Subcellular Processes · Quantitative Biology 2016-04-13 Peter K. Relich , Mark J. Olah , Patrick J. Cutler , Keith A. Lidke

This paper addresses the nonparametric estimation of the drift function over a compact domain for a time-homogeneous diffusion process, based on high-frequency discrete observations from $N$ independent trajectories. We propose a neural…

Machine Learning · Statistics 2026-04-01 Yuzhen Zhao , Yating Liu , Marc Hoffmann

Consider an multidimensional obliquely reflected Brownian motion in the positive orthant, or, more generally, in a convex polyhedral cone. We find sufficient conditions for existence of a stationary distribution and convergence to this…

Probability · Mathematics 2016-04-04 Andrey Sarantsev

The quality of numerically simulated spectra using real-time evolution methods for strongly correlated systems is affected by both the length of simulation time and the system size, limiting resolution in both frequency and momentum. In…

Strongly Correlated Electrons · Physics 2025-09-22 Ta Tang , Chunjing Jia , Brian Moritz , Thomas P. Devereaux

We prove the existence of the reflected diffusion on a complex of an arbitrary size for a large class of planar simple nested fractals. Such a process is obtained as a folding projection of the free Brownian motion from the unbounded…

Probability · Mathematics 2020-01-08 Kamil Kaleta , Mariusz Olszewski , Katarzyna Pietruska-Pałuba

In this work, we consider the detection of manoeuvring small objects with radars. Such objects induce low signal to noise ratio (SNR) reflections in the received signal. We consider both co-located and separated transmitter/receiver pairs,…

Systems and Control · Computer Science 2025-07-08 Kimin Kim , Murat Uney , Bernard Mulgrew