no code implementations • 3 Oct 2022 • Mohammad Taha Toghani, Soomin Lee, César A. Uribe
Our main technical contribution is a unified proof for asynchronous federated learning with bounded staleness that we apply to MAML and ME personalization frameworks.
no code implementations • 17 Sep 2022 • Soomin Lee, Le Chen, Jiahao Wang, Alexander Liniger, Suryansh Kumar, Fisher Yu
In this paper, we tackle the problem of active robotic 3D reconstruction of an object.
no code implementations • 16 Feb 2021 • Pavel Dvurechensky, Dmitry Kamzolov, Aleksandr Lukashevich, Soomin Lee, Erik Ordentlich, César A. Uribe, Alexander Gasnikov
Statistical preconditioning enables fast methods for distributed large-scale empirical risk minimization problems.
Distributed Optimization Optimization and Control
no code implementations • ACL 2021 • Wasi Uddin Ahmad, Xiao Bai, Soomin Lee, Kai-Wei Chang
Natural language processing techniques have demonstrated promising results in keyphrase generation.
no code implementations • 3 Sep 2018 • César A. Uribe, Soomin Lee, Alexander Gasnikov, Angelia Nedić
Then, we study distributed optimization algorithms for non-dual friendly functions, as well as a method to improve the dependency on the parameters of the functions involved.
no code implementations • 1 Dec 2017 • César A. Uribe, Soomin Lee, Alexander Gasnikov, Angelia Nedić
In this paper, we study the optimal convergence rate for distributed convex optimization problems in networks.
no code implementations • 14 Jan 2017 • Guanghui Lan, Soomin Lee, Yi Zhou
Our major contribution is to present a new class of decentralized primal-dual type algorithms, namely the decentralized communication sliding (DCS) methods, which can skip the inter-node communications while agents solve the primal subproblems iteratively through linearizations of their local objective functions.
no code implementations • 31 Aug 2015 • Soomin Lee, Angelia Nedić, Maxim Raginsky
In ODA-C, to mitigate the disagreements on the primal-vector updates, the agents implement a generalization of the local information-exchange dynamics recently proposed by Li and Marden over a static undirected graph.
no code implementations • 7 Jul 2013 • Angelia Nedich, Soomin Lee
This paper considers stochastic subgradient mirror-descent method for solving constrained convex minimization problems.
Optimization and Control Systems and Control