Zobrazeno 1 - 10
of 31
pro vyhledávání: '"Van Scoy, Bryan"'
Autor:
Bianchin, Gianluca, Van Scoy, Bryan
Time-varying optimization problems are central to many engineering applications, where performance metrics and system constraints evolve dynamically with time. A number of algorithms have been proposed in recent years to solve such problems; a common
Externí odkaz:
http://arxiv.org/abs/2407.08037
Autor:
Van Scoy, Bryan, Lessard, Laurent
We consider the distributed optimization problem for a multi-agent system. Here, multiple agents cooperatively optimize an objective by sharing information through a communication network and performing computations. In this tutorial, we provide an o
Externí odkaz:
http://arxiv.org/abs/2309.11393
Autor:
Van Scoy, Bryan, Lessard, Laurent
Iterative gradient-based optimization algorithms are widely used to solve difficult or large-scale optimization problems. There are many algorithms to choose from, such as gradient descent and its accelerated variants such as Polyak's Heavy Ball meth
Externí odkaz:
http://arxiv.org/abs/2309.11377
Primal-dual algorithms are frequently used for iteratively solving large-scale convex optimization problems. The analysis of such algorithms is usually done on a case-by-case basis, and the resulting guaranteed rates of convergence can be conservativ
Externí odkaz:
http://arxiv.org/abs/2309.11365
Autor:
Van Scoy, Bryan, Lessard, Laurent
We revisit the classical problem of absolute stability; assessing the robust stability of a given linear time-invariant (LTI) plant in feedback with a nonlinearity belonging to some given function class. Standard results typically take the form of su
Externí odkaz:
http://arxiv.org/abs/2209.06412
Autor:
Van Scoy, Bryan, Lessard, Laurent
In the distributed optimization problem for a multi-agent system, each agent knows a local function and must find a minimizer of the sum of all agents' local functions by performing a combination of local gradient evaluations and communicating inform
Externí odkaz:
http://arxiv.org/abs/2206.07096
Publikováno v:
In Franklin Open September 2024 8
Autor:
Van Scoy, Bryan, Lessard, Laurent
We study the trade-off between convergence rate and sensitivity to stochastic additive gradient noise for first-order optimization methods. Ordinary Gradient Descent (GD) can be made fast-and-sensitive or slow-and-robust by increasing or decreasing t
Externí odkaz:
http://arxiv.org/abs/2109.05059
Autor:
Van Scoy, Bryan, Lessard, Laurent
We consider the distributed optimization problem, where a group of agents work together to optimize a common objective by communicating with neighboring agents and performing local computations. For a given algorithm, we use tools from robust control
Externí odkaz:
http://arxiv.org/abs/2003.10500
This work concerns the analysis and design of distributed first-order optimization algorithms over time-varying graphs. The goal of such algorithms is to optimize a global function that is the average of local functions using only local computations
Externí odkaz:
http://arxiv.org/abs/1907.05448