40 citations · 71 across the 7 of their papers we have counts for
7 papers
A Unified Approach to Controlling Implicit Regularization via Mirror Descent
Haoyuan Sun, Khashayar Gatmiry, Kwangjun Ahn +1
Inspired by the remarkable success of large neural networks, there has been significant interest in understanding the generalization performance of over-parameterized models. Subst…
Online Learning for Equilibrium Pricing in Markets under Incomplete Information
Devansh Jalota, Haoyuan Sun, Navid Azizan
The computation of equilibrium prices at which the supply of goods matches their demand typically relies on complete information on agents' private attributes, e.g., suppliers' cos…
Mirror Descent Maximizes Generalized Margin and Can Be Implemented Efficiently
Haoyuan Sun, Kwangjun Ahn, Christos Thrampoulidis +1
Driven by the empirical success and wide use of deep neural networks, understanding the generalization performance of overparameterized models has become an increasingly popular qu…
Perturbation-based Regret Analysis of Predictive Control in Linear Time Varying Systems
Yiheng Lin, Yang Hu, Haoyuan Sun +3
We study predictive control in a setting where the dynamics are time-varying and linear, and the costs are time-varying and well-conditioned. At each time step, the controller rece…
Distributed Submodular Maximization with Parallel Execution
Haoyuan Sun, David Grimsman, Jason R Marden
The submodular maximization problem is widely applicable in many engineering problems where objectives exhibit diminishing returns. While this problem is known to be NP-hard for ce…
Analytic Continued Fractions for Regression: A Memetic Algorithm Approach
Pablo Moscato, Haoyuan Sun, Mohammad Nazmul Haque
We present an approach for regression problems that employs analytic continued fractions as a novel representation. Comparative computational results using a memetic algorithm are…
Beyond Online Balanced Descent: An Optimal Algorithm for Smoothed Online Optimization
Gautam Goel, Yiheng Lin, Haoyuan Sun +1
We study online convex optimization in a setting where the learner seeks to minimize the sum of a per-round hitting cost and a movement cost which is incurred when changing decisio…