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2. Linear Dynamical Systems Lecture 2
science, electrical, engineering, technology, linear, dynamical, system, vector, matrix, Fourier, transform, gain, factor, signal, circuit, function, research
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What is Science for?
What is science for, what good does it do and should it do good? In this lecture, Sulston and Harris will attempt to identify some of the most urgent ethical and regulatory problems raised by contemporary science, and suggest some possible solutions. They will discuss some key cutting edge scientific problems, and debate how we can assess their impact. Where do the significant ethical and regulatory dilemmas for science lie? Are we worrying about the right things? They will also address the cru
Author(s): John Sulston, John Harris, Richard Dawkins

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Asia Forum 2006 Opening Session
Discussions were led by LSE academics: Professor Danny Quah, Head of Economics Department; Dr Razeen Sally, senior lecturer in international political economy and head of the international trade policy unit and Professor Robert Wade, professor of political economy and development at DESTIN. Other speakers included: Sheila Dikshit, chief minister of Delhi; Nandan M Nilekani, chief executive officer of Infosys; Mr Sun Yuxi, Chinese Ambassador to India, and Dr YV Reddy, governor of the Reserve Bank
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Site Epiphys
Epiphys est un espace d'apprentissage numérique transdisciplinaire pour comprendre et apprendre à manipuler des objets mathématiques en s'appuyant sur leurs interprétations en Sciences Physiques. Les connaissances sont organisées en un réseau de concepts parcourus au travers de six types d'articles : observer, analyser, synthétiser, transposer, calculer, pratiquer. Les contenus sont basés sur le questionnement et la mise en situation invitant le visiteur à renforcer sa compréhension du
Author(s): Michel Pavageau

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Cette ressource peut être utilisée librement dans les limites de la licence Creative Commons Paternité - Partage des conditions Initiales à l'identique 2.0 France http://creativecommons.org/licens

13. Convex Optimization II Lecture 13
Math, Technology, Algebra, calculus, geometry, electrical engineering, convex optimization, subgradient calculus, derivatives, basic inequality, function, algorithms, trust region, nonlinear optimal control, discretization, SCP, torque residuals, convex-c
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12. Convex Optimization II Lecture 12
Math, Technology, Algebra, calculus, geometry, electrical engineering, convex optimization, subgradient calculus, derivatives, basic inequality, function, algorithms, sequential convex programming, alternating convex optimization, convex-concave, nonnegat
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10. Convex Optimization II Lecture 10
Math, Technology, Algebra, calculus, geometry, electrical engineering, convex optimization, subgradient calculus, derivatives, basic inequality, function, algorithms, rate control, single commodity network flow, convex problem, dual decomposition, lagrang
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9. Convex Optimization II Lecture 9
Math, Technology, Algebra, calculus, geometry, electrical engineering, convex optimization, subgradient calculus, derivatives, basic inequality, function, algorithms, separable problems, complicating variables, primal decomposition, dual, complicating con
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8. Convex Optimization II Lecture 8
Math, Technology, Algebra, calculus, geometry, electrical engineering, convex optimization, subgradient calculus, derivatives, basic inequality, function, algorithms, ellipsoid method, convergence proof, inequality constraints, feasibility problems, deep
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7. Convex Optimization II Lecture 7
Math, Technology, Algebra, calculus, geometry, electrical engineering, convex optimization, subgradient calculus, derivatives, basic inequality, function, algorithms, subgradient method,cutting plane, cutting plane method, analytic center, pruning constra
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6. Convex Optimization II Lecture 6
Math, Technology, Algebra, calculus, geometry, electrical engineering, convex optimization, subgradient calculus, derivatives, basic inequality, function, algorithms, subgradient method,cutting plane, localization algorithms, lower bounds, stopping criter
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5. Convex Optimization II Lecture 5
Math, Technology, Algebra, calculus, geometry, electrical engineering, convex optimization, subgradient calculus, derivatives, basic inequality, function, algorithms, subgradient method, stochastic programing, convergence proof, convex functions, adaptive
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4. Convex Optimization II Lecture 4
Math, Technology, Algebra, calculus, geometry, electrical engineering, convex optimization, subgradient calculus, derivatives, basic inequality, function, algorithms, subgradient method, dual, constrained optimization, linear equality constraints, negativ
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2. Convex Optimization II Lecture 2
Math, Technology, Algebra, calculus, geometry, electrical engineering, convex optimization, subgradient calculus, derivatives, basic inequality, function, algorithms, stepsize rules, convergence results, proofs, optimal step size, alternating projections,
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1. Convex Optimization II Lecture 1
Math, Technology, Algebra, calculus, geometry, electrical engineering, convex optimization, subgradient calculus, derivatives, basic inequality, function, algorithms, convex analysis, nondifferentiable, subdifferential, weak subgradient calculus, strong s
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18. Convex Optimization I Lecture 18
science, electrical, engineering, technology, convex, optimization, logarithmic barrier, reformulation, indicator, function, KKT, Lagrangian, Lipschitz, condition, geometric program, phase I
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10. Convex Optimization I Lecture 10
science, electrical, engineering, technology, convex, optimization, estimation, approximation, norm, least-squares, Chebyshev, Huber, penalty, function, Tikhonov, regularization, linear, dynamical, system
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3. Convex Optimization I Lecture 3
science, electrical, engineering, technology, convex, optimization, affine, eigenvalue, extended-value, extension, quadratic, function, epigraph, Jensen, inequality
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4. Convex Optimization I Lecture 4
science, electrical, engineering, technology, convex, optimization, scalar, vector, Schur, complement, logarithm, quadratic, IRR, Jensen, inequality, Gaussian, integration, property, yield function
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1. Convex Optimization I Lecture 1
science, electrical, engineering, technology, convex, optimization, least, squares, constraint, function, portfolio, circuit, data, fitting, ellipsoid, control, signal, processing
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