v2010.10.26 - Convex Optimization
v2010.10.26 - Convex Optimization v2010.10.26 - Convex Optimization
584 CHAPTER 7. PROXIMITY PROBLEMSprojection on a positive semidefinite cone (1336); zeroing those eigenvalueshere in Problem 3 would place an elbow in the projection path (Figure 153)thereby producing a result that is necessarily suboptimal. Problem 3 isinstead a projection on the EDM cone whose associated spectral cone isconsiderably different. (5.11.2.3) Proper choice of spectral cone is demandedby diagonalization of that variable argument to the objective:7.3.3.1 Cayley-Menger formWe use Cayley-Menger composition of the Euclidean distance matrix to solvea problem that is the same as Problem 3 (1383): (5.7.3.0.1)[ ] [ ]∥ minimize0 1T 0 1T ∥∥∥2D∥ −1 −D 1 −H[ ]F0 1T(1401)subject to rank≤ ρ + 21 −DD ∈ EDM Na projection of H on a generally nonconvex subset (when ρ < N −1) of theEuclidean distance matrix cone boundary rel∂EDM N ; id est, projectionfrom the EDM cone interior or exterior on a subset of its relative boundary(6.5, (1179)).Rank of an optimal solution is intrinsically bounded above and below;[ ] 0 1T2 ≤ rank1 −D ⋆ ≤ ρ + 2 ≤ N + 1 (1402)Our proposed strategy ([ for low-rank ]) solution is projection on that subset0 1Tof a spectral cone λ1 −EDM N (5.11.2.3) corresponding to affinedimension not in excess of that ρ desired; id est, spectral projection on⎡ ⎤⎣ Rρ+1 +0 ⎦ ∩ ∂H ⊂ R N+1 (1403)R −where∂H = {λ ∈ R N+1 | 1 T λ = 0} (1112)is a hyperplane through the origin. This pointed polyhedral cone (1403), towhich membership subsumes the rank constraint, is not full-dimensional.
7.3. THIRD PREVALENT PROBLEM: 585Given desired affine dimension 0 ≤ ρ ≤ N −1 and diagonalization (A.5)of unknown EDM D [ ] 0 1T UΥU T ∈ S N+11 −Dh(1404)and given symmetric H in diagonalization[ ] 0 1T QΛQ T ∈ S N+1 (1405)1 −Hhaving eigenvalues arranged in nonincreasing order, then by (1125) problem(1401) is equivalent to∥minimize ∥δ(Υ) − π ( δ(R T ΛR) )∥ ∥ 2Υ , R⎡ ⎤subject to δ(Υ) ∈ ⎣ Rρ+1 +0 ⎦ ∩ ∂H(1406)R −δ(QRΥR T Q T ) = 0R −1 = R Twhere π is the permutation operator from7.1.3 arranging its vectorargument in nonincreasing order, 7.20 whereR Q T U ∈ R N+1×N+1 (1407)in U on the set of orthogonal matrices is a bijection, and where ∂H insuresone negative eigenvalue. Hollowness constraint δ(QRΥR T Q T ) = 0 makesproblem (1406) difficult by making the two variables dependent.Our plan is to instead divide problem (1406) into two and then iteratetheir solution:minimizeΥsubject to δ(Υ) ∈(∥ δ(Υ) − π δ(R T ΛR) )∥ ∥ 2⎡ ⎤⎣ Rρ+1 +0 ⎦ ∩ ∂HR −(a)(1408)minimize ‖R Υ ⋆ R T − Λ‖ 2 FRsubject to δ(QR Υ ⋆ R T Q T ) = 0R −1 = R T(b)7.20 Recall, any permutation matrix is an orthogonal matrix.
- Page 533 and 534: 6.8. DUAL EDM CONE 533EDM 2 = S 2 h
- Page 535 and 536: 6.8. DUAL EDM CONE 535therefore the
- Page 537 and 538: 6.8. DUAL EDM CONE 537Elegance of t
- Page 539 and 540: 6.8. DUAL EDM CONE 5396.8.1.5 Affin
- Page 541 and 542: 6.8. DUAL EDM CONE 5416.8.1.7 Schoe
- Page 543 and 544: 6.8. DUAL EDM CONE 5430dvec rel ∂
- Page 545 and 546: 6.10. POSTSCRIPT 5456.10 Postscript
- Page 547 and 548: Chapter 7Proximity problemsIn the
- Page 549 and 550: 549project on the subspace, then pr
- Page 551 and 552: 551HS N h0EDM NK = S N h ∩ R N×N
- Page 553 and 554: 5537.0.3 Problem approachProblems t
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- Page 589 and 590: 7.4. CONCLUSION 589filtering, multi
- Page 591 and 592: Appendix ALinear algebraA.1 Main-di
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- Page 603 and 604: A.3. PROPER STATEMENTS 603For A dia
- Page 605 and 606: A.3. PROPER STATEMENTS 605Diagonali
- Page 607 and 608: A.3. PROPER STATEMENTS 607For A,B
- Page 609 and 610: A.3. PROPER STATEMENTS 609When B is
- Page 611 and 612: A.4. SCHUR COMPLEMENT 611A.4 Schur
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- Page 615 and 616: A.4. SCHUR COMPLEMENT 615From Corol
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- Page 625 and 626: A.7. ZEROS 625A.6.5SVD of symmetric
- Page 627 and 628: A.7. ZEROS 627(Transpose.)Likewise,
- Page 629 and 630: A.7. ZEROS 629For X,A∈ S M +[34,2
- Page 631 and 632: A.7. ZEROS 631A.7.5.0.1 Proposition
- Page 633 and 634: Appendix BSimple matricesMathematic
7.3. THIRD PREVALENT PROBLEM: 585Given desired affine dimension 0 ≤ ρ ≤ N −1 and diagonalization (A.5)of unknown EDM D [ ] 0 1T UΥU T ∈ S N+11 −Dh(1404)and given symmetric H in diagonalization[ ] 0 1T QΛQ T ∈ S N+1 (1405)1 −Hhaving eigenvalues arranged in nonincreasing order, then by (1125) problem(1401) is equivalent to∥minimize ∥δ(Υ) − π ( δ(R T ΛR) )∥ ∥ 2Υ , R⎡ ⎤subject to δ(Υ) ∈ ⎣ Rρ+1 +0 ⎦ ∩ ∂H(1406)R −δ(QRΥR T Q T ) = 0R −1 = R Twhere π is the permutation operator from7.1.3 arranging its vectorargument in nonincreasing order, 7.20 whereR Q T U ∈ R N+1×N+1 (1407)in U on the set of orthogonal matrices is a bijection, and where ∂H insuresone negative eigenvalue. Hollowness constraint δ(QRΥR T Q T ) = 0 makesproblem (1406) difficult by making the two variables dependent.Our plan is to instead divide problem (1406) into two and then iteratetheir solution:minimizeΥsubject to δ(Υ) ∈(∥ δ(Υ) − π δ(R T ΛR) )∥ ∥ 2⎡ ⎤⎣ Rρ+1 +0 ⎦ ∩ ∂HR −(a)(1408)minimize ‖R Υ ⋆ R T − Λ‖ 2 FRsubject to δ(QR Υ ⋆ R T Q T ) = 0R −1 = R T(b)7.20 Recall, any permutation matrix is an orthogonal matrix.