15 citations · 22 across the 12 of their papers we have counts for
13 papers
Spherical-Design Oracles for Zeroth-Order Optimisation: Deterministic, Variance-Free Gradient Estimation
Amir Ali Farzin, Yuen-Man Pun, Philipp Braun +1
In this work, we develop a zeroth-order (ZO) method that estimates the gradient with minimal bias and variance. Instead of the random directions often used in the ZO literature, we…
Online Sketched Newton-Raphson
Jean-Luc Lupien, Yuen-Man Pun, Youssef Diouane +2
In online convex optimization (OCO), a decision-maker is confronted with an unknown environment and seeks to play an optimal sequence of decisions on a short time-scale using only…
On the Stability Connection Between Discrete-Time Algorithms and Their Resolution ODEs: Applications to Min-Max Optimisation
Amir Ali Farzin, Yuen-Man Pun, Philipp Braun +1
This work establishes a rigorous connection between stability properties of discrete-time algorithms (DTAs) and corresponding continuous-time dynamical systems derived through $ O(…
Solving the Offline and Online Min-Max Problem of Non-smooth Submodular-Concave Functions: A Zeroth-Order Approach
Amir Ali Farzin, Yuen-Man Pun, Philipp Braun +2
We consider max-min and min-max problems with objective functions that are possibly non-smooth, submodular with respect to the minimiser and concave with respect to the maximiser.…
Taking the Road Less Scheduled with Adaptive Polyak Steps
Dimitris Oikonomou, Matthew Buchholz, Yuen-Man Pun +2
Schedule-Free SGD, proposed in [Defazio et al., 2024], achieves optimal convergence rates without requiring the training horizon in advance, by replacing learning rate schedules wi…
Minimisation of Submodular Functions Using Gaussian Zeroth-Order Random Oracles
Amir Ali Farzin, Yuen-Man Pun, Philipp Braun +2
We consider the minimisation problem of submodular functions and investigate the application of a zeroth-order method to this problem. The method is based on exploiting a Gaussian…
Minimisation of Quasar-Convex Functions Using Random Zeroth-Order Oracles
Amir Ali Farzin, Yuen-Man Pun, Philipp Braun +1
This paper explores the performance of a random Gaussian smoothing zeroth-order (ZO) scheme for minimising quasar-convex (QC) and strongly quasar-convex (SQC) functions in both unc…
Properties of Fixed Points of Generalised Extra Gradient Methods Applied to Min-Max Problems
Amir Ali Farzin, Yuen-Man Pun, Philipp Braun +1
This paper studies properties of fixed points of generalised Extra-gradient (GEG) algorithms applied to min-max problems. We discuss connections between saddle points of the object…
Online Non-Stationary Stochastic Quasar-Convex Optimization
Yuen-Man Pun, Iman Shames
Recent research has shown that quasar-convexity can be found in applications such as identification of linear dynamical systems and generalized linear models. Such observations hav…
Distributionally Time-Varying Online Stochastic Optimization under Polyak-Łojasiewicz Condition with Application in Conditional Value-at-Risk Statistical Learning
Yuen-Man Pun, Farhad Farokhi, Iman Shames
In this work, we consider a sequence of stochastic optimization problems following a time-varying distribution via the lens of online optimization. Assuming that the loss function…
Projected Tensor Power Method for Hypergraph Community Recovery
Jinxin Wang, Yuen-Man Pun, Xiaolu Wang +2
This paper investigates the problem of exact community recovery in the symmetric -uniform hypergraph stochastic block model (-HSBM). In this model, a -uniform…
Local Strong Convexity of Source Localization and Error Bound for Target Tracking under Time-of-Arrival Measurements
Yuen-Man Pun, Anthony Man-Cho So
In this paper, we consider a time-varying optimization approach to the problem of tracking a moving target using noisy time-of-arrival (TOA) measurements. Specifically, we formulat…
Distributionally Robust Graph Learning from Smooth Signals under Moment Uncertainty
Xiaolu Wang, Yuen-Man Pun, Anthony Man-Cho So
We consider the problem of learning a graph from a finite set of noisy graph signal observations, the goal of which is to find a smooth representation of the graph signal. Such a p…