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Melvin Leok
США
Добавлен 14 мар 2008
Melvin Leok is a professor of mathematics at the University of California, San Diego, where his research is supported by grants from NSF, AFOSR, and DoD, including the NSF CAREER Award, and the DoD Newton Award for Transformative Ideas. He is a NAS Kavli Frontiers of Science Fellow, a Simons Fellow in Mathematics, and received the SciCADE New Talent Prize, SIAM Student Paper Prize, and Leslie Fox Prize in Numerical Analysis. He gave plenary talks at Foundations of Computational Mathematics, NUMDIFF, and the IFAC Workshop on Lagrangian and Hamiltonian Methods for Nonlinear Control.
He is affiliated with the Center for Control Systems and Dynamics, the Contextual Robotics Institute, the Halicioglu Data Science Institute, and the NSF AI Institute, TILOS.
Available as a consultant for modeling, simulating, controlling, quantifying uncertainty, machine learning, and optimization for large scale interconnected systems that evolve on nonlinear configuration spaces.
He is affiliated with the Center for Control Systems and Dynamics, the Contextual Robotics Institute, the Halicioglu Data Science Institute, and the NSF AI Institute, TILOS.
Available as a consultant for modeling, simulating, controlling, quantifying uncertainty, machine learning, and optimization for large scale interconnected systems that evolve on nonlinear configuration spaces.
Lie group collision variational integrator - bouncing cube/dice simulation - Example 5
This simulation demonstrates the sensitive dependence on initial conditions of rigid body collisional dynamics, two cubes are initialized with slightly different orientations and allowed to collide with a plane, and the trajectories eventually diverge after a few collisions.
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Видео
PIMS Marsden Memorial Lecture by Melvin Leok at UNBC in March 2023
Просмотров 507Год назад
The Connections Between Discrete Geometric Mechanics, Information Geometry, Accelerated Optimization and Machine Learning Melvin Leok, University of California, San Diego Abstract: Geometric mechanics describes Lagrangian and Hamiltonian mechanics geometrically, and information geometry formulates statistical estimation, inference, and machine learning in terms of geometry. A divergence functio...
EM algorithm applied to Gaussian mixtures
Просмотров 5352 года назад
EM algorithm applied to Gaussian mixtures
Minimizing divergence between a model manifold and a data manifold
Просмотров 3532 года назад
Minimizing divergence between a model manifold and a data manifold
Gaussian mixture model as a system with hidden variables
Просмотров 2412 года назад
Gaussian mixture model as a system with hidden variables
Statistical models with hidden variables
Просмотров 2672 года назад
Statistical models with hidden variables
Asymptotic Theory of Hypothesis Testing
Просмотров 6012 года назад
Asymptotic Theory of Hypothesis Testing
Higher-order Asymptotic Theory of Estimation
Просмотров 1842 года назад
Higher-order Asymptotic Theory of Estimation
First-order Asymptotic Theory of Estimation
Просмотров 3442 года назад
First-order Asymptotic Theory of Estimation
Estimation in a Curved Exponential Family
Просмотров 4372 года назад
Estimation in a Curved Exponential Family
Estimation in the context of statistical inference
Просмотров 2632 года назад
Estimation in the context of statistical inference
Canonical divergence in dually flat manifolds
Просмотров 2202 года назад
Canonical divergence in dually flat manifolds
Metric and Cubic Tensor Derived from Divergence or Convex Functions
Просмотров 2262 года назад
Metric and Cubic Tensor Derived from Divergence or Convex Functions
Covariant derivatives using affine connections
Просмотров 3312 года назад
Covariant derivatives using affine connections
Tangent vectors under changes of coordinates
Просмотров 3212 года назад
Tangent vectors under changes of coordinates
Repeated observations and maximum likelihood estimators
Просмотров 1802 года назад
Repeated observations and maximum likelihood estimators