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03/20/2022
Geometric Methods for Sampling, Optimisation, Inference and Adaptive Agents
In this chapter, we identify fundamental geometric structures that under...
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07/23/2021
Optimization on manifolds: A symplectic approach
There has been great interest in using tools from dynamical systems and ...
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09/05/2020
Distributed Optimization, Averaging via ADMM, and Network Topology
There has been an increasing necessity for scalable optimization methods...
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04/15/2020
On Dissipative Symplectic Integration with Applications to Gradient-Based Optimization
Continuous-time dynamical systems have proved useful in providing concep...
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08/02/2019
Gradient Flows and Accelerated Proximal Splitting Methods
Proximal based methods are well-suited to nonsmooth optimization problem...
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03/11/2019
Conformal Symplectic and Relativistic Optimization
Although momentum-based optimization methods have had a remarkable impac...
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08/13/2018
Relax, and Accelerate: A Continuous Perspective on ADMM
The acceleration technique first introduced by Nesterov for gradient des...
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01/13/2018
An Explicit Convergence Rate for Nesterov's Method from SDP
The framework of Integral Quadratic Constraints (IQC) introduced by Less...
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10/26/2017
Energy Clustering
Energy statistics was proposed by Székely in the 80's inspired by the Ne...
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10/02/2017
How is Distributed ADMM Affected by Network Topology?
When solving consensus optimization problems over a graph, there is ofte...
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03/10/2017
Tuning Over-Relaxed ADMM
The framework of Integral Quadratic Constraints (IQC) reduces the comput...
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03/10/2017
Markov Chain Lifting and Distributed ADMM
The time to converge to the steady state of a finite Markov chain can be...
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12/07/2015