research
∙
05/19/2023
Multi-Objective Optimization Using the R2 Utility
The goal of multi-objective optimization is to identify a collection of ...
share
research
∙
04/30/2023
A Class of Spatial Filtering Problems with Unknown Spatial Observations
We consider a class of high-dimensional spatial filtering problems, wher...
research
∙
02/01/2023
Privacy Risk for anisotropic Langevin dynamics using relative entropy bounds
The privacy preserving properties of Langevin dynamics with additive iso...
research
∙
10/06/2022
Joint Entropy Search for Multi-objective Bayesian Optimization
Many real-world problems can be phrased as a multi-objective optimizatio...
research
∙
03/06/2022
Unbiased Estimation using a Class of Diffusion Processes
We study the problem of unbiased estimation of expectations with respect...
research
∙
11/30/2021
Optimal friction matrix for underdamped Langevin sampling
A systematic procedure for optimising the friction coefficient in underd...
research
∙
10/02/2021
A Lagged Particle Filter for Stable Filtering of certain High-Dimensional State-Space Models
We consider the problem of high-dimensional filtering of state-space mod...
research
∙
06/25/2021
Parameter Estimation for the McKean-Vlasov Stochastic Differential Equation
In this paper, we consider the problem of parameter estimation for a sto...
research
∙
09/18/2020
Joint Online Parameter Estimation and Optimal Sensor Placement for the Partially Observed Stochastic Advection-Diffusion Equation
In this paper, we consider the problem of jointly performing online para...
research
∙
08/18/2020
Score-Based Parameter Estimation for a Class of Continuous-Time State Space Models
We consider the problem of parameter estimation for a class of continuou...
research
∙
07/31/2020
Two-Timescale Stochastic Gradient Descent in Continuous Time with Applications to Joint Online Parameter Estimation and Optimal Sensor Placement
In this paper, we establish the almost sure convergence of two-timescale...
research
∙
07/15/2020
On stochastic mirror descent with interacting particles: convergence properties and variance reduction
An open problem in optimization with noisy information is the computatio...
research
∙
05/10/2019
The sharp, the flat and the shallow: Can weakly interacting agents learn to escape bad minima?
An open problem in machine learning is whether flat minima generalize be...
research
∙
12/08/2017
On Adaptive Estimation for Dynamic Bernoulli Bandits
The multi-armed bandit (MAB) problem is a classic example of the explora...
research
∙
10/12/2017
