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Lecture 8: Semidefinite Programming Magnus M. Halldorsson Based on s by Uri Zwick Outline of talk Semidefinite programming MAX CUT (Goemans, Williamson 95 ...

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From Support Vector Machines (SVMs) to Semidefinite Programming Machines (SDPMs) ... Toy Features for Handwritten Digits 1 =0.48 3=0.37 2=0.58. Microsoft Research Ltd. ...

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MAX CUT (Goemans, Williamson '95) MAX 2-SAT and MAX DI-CUT (FG'95, MM'01, LLZ'02) ... An SDP Relaxation of MAX CUT. Geometric intuition ...

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On linear and semidefinite programming relaxations for ... Linear Programming Relaxation No ... On linear and semidefinite programming relaxations ...

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Workshop on Uncertain Dynamical Systems Robust Semidefinite Programming and Its Application to Sampled-Data Control Yasuaki Oishi (Nanzan University)

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the code for the creation of the cells is packed in a molecule called DNA. ... a minimum size set of haplotypes which conflate to produce the given genotypes ...

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Repeat a few times to get a good approximation with high probability. ... That is, it is NP-hard to find a better approximation algorithm! ...

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Workshop on Uncertain Dynamical Systems Robust Semidefinite Programming and Its Application to Sampled-Data Control Yasuaki Oishi (Nanzan University)

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Semidefinite Programming Application: Truss Topology Design. Jean-Christophe Lilot ... CAS735, Friday 2nd & 9th April 2004. Outline. Basic TTD problem (Assignment 2) ...

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Accelerated search using LP-based bound strengthening. Can use PENBMI to find upper bounds. ... Given : system to stabilize. Desired: Controller with at most r ...

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Relax variables to get mathematical program. Solve program optimally. Round fractional solution ... Use relaxations of cut metrics. Distance function from LPs ...

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SDPs arisen from... Control Theory. Combinatorial Optimization. Data Mining. Quantum Chemistry ... for SDPs arisen from Quantum Chemistry -153.2449 0.0028 -0. ...

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Graph coloring. Random instances of 3SAT. My feeling: Interesting algorithms remain undiscovered; ... cannot be colored with 100 colors yet. every subgraph on ...

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discovery of low dimensional representations of high-dimensional data ... a quadratic function where its Hessian matrix (matrix of second partial ...

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Department of Information Engineering. The Chinese University of Hong Kong. 2. Outline ... implicitly obtain the feature map by explicitly pursuing the ...

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Duality and optimality conditions revisited ... f(x) is a convex function if and only if for any given two points x1 and x2 in ...

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Region above a convex function is a convex set. Convex Set ... Subject to || Ai x bi || = ciT x di. i = 1, ... , L. Linear Objective Function ...

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Title: The Use of Semidefinite Programming in Approximation Algorithms Author: Magnus Halldorsson Last modified by: Magn s M r Halld rsson Created Date

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Assuming the 'unique games conjecture', this algorithm is the best possible! ... Useful to know geometry and algebra. Semidefinite Programming. What is ...

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Multiplicative weights method: ... Potential: t = Sum of weights= i wit (initially n) ... Payoff: (for weights di,j on experts) ...

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Solving Markov Random Fields using Second Order Cone Programming Andrew Zisserman http://www.robots.ox.ac.uk/~vgg M. Pawan Kumar Philip H.S. Torr

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Probability edge is cut=1/2. State of the art until 1993. 25% error ... Cuts are hyperplanes in RV. Algorithm 2: Goemans-Williamson ...

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Tomorrow is deadline for CS grad student conference (CSUSC) ... Constructing Ensembles of Decision Trees: Bagging, Boosting, and Randomization. ...

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SDP (SemiDefinite Program) has many applications. SDPs become ... Lagrangian Methods (PENNON) Spectral Bundle Methods (SBMethod) Low accuracy (large scale) ...

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Previous approximation algorithms for expansion problems ... O( ) -approximation to sparsest cut ... New approximation algorithm via semidefinite programming ...

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Aim: To obtain accurate MAP estimate of. Markov Random Fields. Markov Random Field (MRF) ... MAP - accurate. Complexity - high. Y - y yT 0. Objective function ...

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A Second Course Jean Walrand Department of EECS University of California at Berkeley Optimization Motivation Optimization of networks Mathematics Convex Programming ...

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Lecture 8 Nonlinear Programming Models Topics General formulations Local vs. global solutions Solution characteristics Convexity and convex programming

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Lagrangian Duality. Linear Programming and Combinatorics. Non-convex quadratic programming ... Estimate the duality gap using your primal and dual solutions. ...

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A Single Nucleotide Polymorphism (SNP), pronounced snip, is a single DNA base ... Brown and Harrower (2004) proposed a new integer linear programming for this problem. ...

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The duality gap is always positive: c x - b y 0 for every couple of feasible solutions (x, y) ... General form of the duality in the conic programming: Vi if ...

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and so on, until SN 1=JN is minimised. This procedure is also known as dynamic programming. ... is minimised by u(N-m) and u(N-m) is obtained by ...

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analytical method for finding forces btw polyhedral bodies based on linear programming 89 ... primary constraints ; equality constraints btw bodies ...

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Robust Optimization and Applications in Machine Learning Laurent El Ghaoui SAC Capital and UC Berkeley elghaoui@eecs.berkeley.edu IMS Tutorial, N.U. Singapore,

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Optimization Services (OS)-- A Framework for Optimization Software-- A Computational Infrastructure-- The Next Generation NEOS-- The OR Internet

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An Analysis of Convex Relaxations (PART I) Minimizing Higher Order Energy Functions (PART 2) Philip Torr Work in collaboration with: Pushmeet Kohli, Srikumar Ramalingam

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Convex Optimization Chapter 1 Introduction What, Why and How What is convex optimization Why study convex optimization How to study convex optimization What is Convex ...

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the corresponding n - k columns of M. first order: elements on diagonal. second order: ... for small k ... H. Waki, S. Kim, M. Kojima, and M. Muramatsu. ...

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MIMO Multi-Base-Station Beamforming Design in an Interference Channel Model Hayssam Dahrouj Connections 2006 Supervisor: Prof. Wei Yu ECE Dept., University of Toronto ...

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Entanglement Fidelity via Janiolkowski isomorphism ... Maximizing the entanglement fidelity thus becomes. subject to the constraints that the recovery ...

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Optimization Assoc. Prof. Dr. Pelin G nde gundesbakir@yahoo.com

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Optimization Services (OS)-- A Framework for Optimization Software-- A Computational Infrastructure-- The Next Generation NEOS-- The OR Internet Jun Ma

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Optimization Services (OS)-- A Framework for Optimization Software-- A Computational Infrastructure-- The Next Generation NEOS-- The OR Internet

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S. A., James Lee, and Assaf Naor, STOC'05 papers that are ... General SPARSEST CUT [A., Lee, Naor '04] ... (For general SPARSEST CUT, log log n 'lowerbound' ...

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A Single Nucleotide Polymorphism (SNP) is a single DNA base variation observed ... Cystic fibrosis. 18. National Taiwan University ...

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Title: PowerPoint Presentation Last modified by: mxk Created Date: 1/1/1601 12:00:00 AM Document presentation format: On-screen Show Other titles

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Title: PowerPoint Presentation Author: Laci Lovasz Last modified by: lovasz Created Date: 6/27/2000 7:08:33 PM Document presentation format: On-screen Show

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The Potential Energy Surface. E. Glassy systems ... Icosahedron. Truncated octahedron. 08/06/05. PG Symposium. 12. Current Methods. Heuristic Approaches ...

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Proof: Exact sos decomposition, with rational coefficients. ... Rational SOS Decomposition. 21. Rational SOS Decomposition. 22. Proof: H(x)MT(x)M(x) ...

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... connectivity of graphs, paths, cycles (TSP), network flow problems ... Optimization Algorithms for Networks and Graphs, J. Evans, E. Minieka, Dekker, 1992 ...

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Laboratoire Signaux et Syst mes de Sophia Antipolis, CNRS/UNSA. Worshop SUMARE, Sophia Antipolis, December 18th, 2001. Outline. Introduction to LMI Methods ...

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EE 553 Introduction to Optimization J. McCalley * Multiple equality & 1 inequality constraint * We assume that f, h, and g are continuously differentiable.

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The tri-allele cases are usually considered to be the effect of genotyping errors. ... But we don't know the connection of alleles at different SNP loci. ...

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Original proof of PCP Thm used polynomial representations, ... Applications of PCP Techniques: Tour d'Horizon. Locally checkable / decodable codes. ...

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Primal problems: infinitely many decision variables. Introduce dual variable y. Dual problems: infinitely many constraints. PROPOSITIONS BY BERTSIMAS & POPESCU ...

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