Dynamical, Symplectic and Stochastic Perspectives on Gradient-Based Optimization Michael I. Jordan University of California, Berkeley March 3, 2018

First Page		Document Content
Date: 2018-07-28 17:09:47 Numerical analysis Dynamical systems Classical mechanics Hamiltonian mechanics Symplectic integrator Mathematical optimization Gradient descent Leapfrog integration Bregman Lagrangian Lagrangian mechanics Bregman divergence		Dynamical, Symplectic and Stochastic Perspectives on Gradient-Based Optimization Michael I. Jordan University of California, Berkeley March 3, 2018 Add to Reading List Source URL: eta.impa.br Download Document from Source Website File Size: 991,89 KB Share Document on Facebook

	Microsoft PowerPoint - simplectic_integration DocID: 1ovkD - View Document
	mwre_130_904.2088_2097.tp DocID: 10RLE - View Document
	Explicit Euler Initial Conditions: P0 - initial position V0 - initial veclocity Global Conditions: DocID: RB22 - View Document
	U.S. DEPARTMENT OF COMMERCE NATIONAL OCEANIC AND ATMOSPHERIC ADMINISTRATION NATIONAL WEATHER SERVICE JANUARY DocID: rKR8 - View Document
	U.S. Department of Commerce National Oceanic and Atmospheric Administration National Weather Service National Centers for Environmental Prediction 5200 Auth Road Camp Springs, MD[removed] DocID: qwqc - View Document