How To Find Out If You Can Get A Power Of 2 From A Powerbook



Similar documents
t := maxγ ν subject to ν {0,1,2,...} and f(x c +γ ν d) f(x c )+cγ ν f (x c ;d).

1 if 1 x 0 1 if 0 x 1

2.3 Convex Constrained Optimization Problems

Pacific Journal of Mathematics

THE BANACH CONTRACTION PRINCIPLE. Contents

MA651 Topology. Lecture 6. Separation Axioms.

Convex analysis and profit/cost/support functions

Max-Min Representation of Piecewise Linear Functions

Mathematics Course 111: Algebra I Part IV: Vector Spaces

Adaptive Online Gradient Descent

Modern Optimization Methods for Big Data Problems MATH11146 The University of Edinburgh

1 Norms and Vector Spaces

The Mean Value Theorem

GenOpt (R) Generic Optimization Program User Manual Version 3.0.0β1

BANACH AND HILBERT SPACE REVIEW

Further Study on Strong Lagrangian Duality Property for Invex Programs via Penalty Functions 1

x a x 2 (1 + x 2 ) n.

Fixed Point Theorems

Solutions of Equations in One Variable. Fixed-Point Iteration II

TD(0) Leads to Better Policies than Approximate Value Iteration

Columbia University in the City of New York New York, N.Y

Online Convex Optimization

ON FIBER DIAMETERS OF CONTINUOUS MAPS

CHAPTER II THE LIMIT OF A SEQUENCE OF NUMBERS DEFINITION OF THE NUMBER e.

JUST-IN-TIME SCHEDULING WITH PERIODIC TIME SLOTS. Received December May 12, 2003; revised February 5, 2004

Metric Spaces. Chapter 1

(Quasi-)Newton methods

Mathematical Methods of Engineering Analysis

Dedekind s forgotten axiom and why we should teach it (and why we shouldn t teach mathematical induction in our calculus classes)

Breaking The Code. Ryan Lowe. Ryan Lowe is currently a Ball State senior with a double major in Computer Science and Mathematics and

Notes V General Equilibrium: Positive Theory. 1 Walrasian Equilibrium and Excess Demand

Undergraduate Notes in Mathematics. Arkansas Tech University Department of Mathematics

10. Proximal point method

The Henstock-Kurzweil-Stieltjes type integral for real functions on a fractal subset of the real line

Continuity of the Perron Root

Properties of BMO functions whose reciprocals are also BMO

Separation Properties for Locally Convex Cones

No: Bilkent University. Monotonic Extension. Farhad Husseinov. Discussion Papers. Department of Economics

Medical School Math Requirements and Recommendations

Mathematics for Econometrics, Fourth Edition

24. The Branch and Bound Method

Follow the Perturbed Leader

F. ABTAHI and M. ZARRIN. (Communicated by J. Goldstein)

A CHARACTERIZATION OF C k (X) FOR X NORMAL AND REALCOMPACT

ON GENERALIZED RELATIVE COMMUTATIVITY DEGREE OF A FINITE GROUP. A. K. Das and R. K. Nath

Numerisches Rechnen. (für Informatiker) M. Grepl J. Berger & J.T. Frings. Institut für Geometrie und Praktische Mathematik RWTH Aachen

FACTORING POLYNOMIALS IN THE RING OF FORMAL POWER SERIES OVER Z

CHAPTER SIX IRREDUCIBILITY AND FACTORIZATION 1. BASIC DIVISIBILITY THEORY

Research Article Stability Analysis for Higher-Order Adjacent Derivative in Parametrized Vector Optimization

ON COMPLETELY CONTINUOUS INTEGRATION OPERATORS OF A VECTOR MEASURE. 1. Introduction

SHARP BOUNDS FOR THE SUM OF THE SQUARES OF THE DEGREES OF A GRAPH

FIXED POINT SETS OF FIBER-PRESERVING MAPS

Metric Spaces. Chapter Metrics

Elements of Abstract Group Theory

A PRIORI ESTIMATES FOR SEMISTABLE SOLUTIONS OF SEMILINEAR ELLIPTIC EQUATIONS. In memory of Rou-Huai Wang

An example of a computable

GI01/M055 Supervised Learning Proximal Methods

ON SEQUENTIAL CONTINUITY OF COMPOSITION MAPPING. 0. Introduction

IRREDUCIBLE OPERATOR SEMIGROUPS SUCH THAT AB AND BA ARE PROPORTIONAL. 1. Introduction

God created the integers and the rest is the work of man. (Leopold Kronecker, in an after-dinner speech at a conference, Berlin, 1886)

4. CLASSES OF RINGS 4.1. Classes of Rings class operator A-closed Example 1: product Example 2:

Continued Fractions. Darren C. Collins

Indiana State Core Curriculum Standards updated 2009 Algebra I

Fuzzy Differential Systems and the New Concept of Stability

Medical School Math Requirements and Recommendations

THE FUNDAMENTAL THEOREM OF ALGEBRA VIA PROPER MAPS

Numerical Verification of Optimality Conditions in Optimal Control Problems

Ideal Class Group and Units

CONSTANT-SIGN SOLUTIONS FOR A NONLINEAR NEUMANN PROBLEM INVOLVING THE DISCRETE p-laplacian. Pasquale Candito and Giuseppina D Aguí

n k=1 k=0 1/k! = e. Example 6.4. The series 1/k 2 converges in R. Indeed, if s n = n then k=1 1/k, then s 2n s n = 1 n

Linear Algebra I. Ronald van Luijk, 2012

Lecture 7: Finding Lyapunov Functions 1

ON CERTAIN DOUBLY INFINITE SYSTEMS OF CURVES ON A SURFACE

I. GROUPS: BASIC DEFINITIONS AND EXAMPLES

Continued Fractions and the Euclidean Algorithm

Bounds on the spectral radius of a Hadamard product of nonnegative or positive semidefinite matrices

Algebra Unpacked Content For the new Common Core standards that will be effective in all North Carolina schools in the school year.

MATH 304 Linear Algebra Lecture 9: Subspaces of vector spaces (continued). Span. Spanning set.

it is easy to see that α = a

CONTRIBUTIONS TO ZERO SUM PROBLEMS

INTEGER PROGRAMMING. Integer Programming. Prototype example. BIP model. BIP models

Date: April 12, Contents

Surface bundles over S 1, the Thurston norm, and the Whitehead link

arxiv: v1 [math.pr] 5 Dec 2011

Let H and J be as in the above lemma. The result of the lemma shows that the integral

CHAPTER 7 GENERAL PROOF SYSTEMS

Metric Spaces Joseph Muscat 2003 (Last revised May 2009)

Sequence of Mathematics Courses

SOLUTIONS TO EXERCISES FOR. MATHEMATICS 205A Part 3. Spaces with special properties

COLLEGES Aberdeen, University of Alabama, University of Alaska, University of at Anchorage Arizona State University Arizona, University of Arkansas,

ALMOST COMMON PRIORS 1. INTRODUCTION

The Steepest Descent Algorithm for Unconstrained Optimization and a Bisection Line-search Method

1 Introduction. 2 Prediction with Expert Advice. Online Learning Lecture 09

Transcription:

Pacific Journal of Mathematics MINIMIZATION OF FUNCTIONS HAVING LIPSCHITZ CONTINUOUS FIRST PARTIAL DERIVATIVES LARRY ARMIJO Vol. 16, No. 1 November 1966

PACIFIC JOURNAL OF MATHEMATICS Vol. 16, No. 1, 1966 MINIMIZATION OF FUNCTIONS HAVING LIPSCHITZ CONTINUOUS FIRST PARTIAL DERIVATIVES LARRY ARMIJO A general convergence theorem for the gradient method is proved under hypotheses which are given below. It is then shown that the usual steepest descent and modified steepest descent algorithms converge under the some hypotheses. The modified steepest descent algorithm allows for the possibility of variable stepsize. For a comparison of our results with results previously obtained, the reader is referred to the discussion at the end of this paper. Principal conditions* Let / be a real-valued function defined and continuous everywhere on E n (real Euclidean w-space) and bounded below E n. For fixed x 0 e E n define S(x 0 ) = {x: f(x) ^ f(x 0 )}. The function^ / satisfies: condition I if there exists a unique point x* e E n such that f(x*) = inf/(a); Condition II at x 0 if fe C 1 on S(x 0 ) and Vf(x) = 0 xee n for x e S(x 0 ) if and only if x = x*; Condition III at x 0 if /e C 1 on S(x 0 ) and Ff is Lipschitz continuous on S(x 0 ), i.e., there exists a Lipschitz constant K> 0 such that Ff(y) Ff(x) \ S K\y x\ for every pair x, yes(x 0 ); Condition IV at x 0 if fec 1 on S(x 0 ) and if r > 0 implies that m(r) > 0 where ra(r) = inf Ff(x), S r (x Q ) = S r Π S(x 0 ), S r = χes r (χ 0 ) {x : I x x* I ^r}, and #* is any point for which f(x*) inf f(x). (If xee n S r (x 0 ) is void, we define m(r) = oo.) It follows immediately from the definitions of Conditions I through IV that Condition IV implies Conditions I and II, and if S(x 0 ) is bounded, then Condition IV is equivalent to Conditions I and II. 2. The convergence theorem* In the convergence theorem and its corollaries, we will assume that / is a real-valued function defined and continuous everywhere on E n, bounded below on E n, and that Conditions III and IV hold at x 0. THEOREM. // 0 < δ g 1/41SΓ, then for any xes(x 0 ), the set (1) S*(a, δ) = {x λ : x λ = x- Wf{x), λ > 0, f(x λ ) - f(x) ^ - δ \Ff(x)\ 2 } Received January 30, 1964. The research for this paper was supported in part by General Dynamics/Astronautics, San Diego, California, Rice University, Houston, Texas, and the Martin Company, Denver, Colorado. The author is currently employed by the National Engineering Science Company, Houston, Texas.

2 LARRY ARMIJO is a nonempty subset of S(x 0 ) and any sequence {x k }ΐ= 0 such that x k+1, d), k = 0, 1, 2,, converges to the point x* which minimizes f. Proof. If xe S(x 0 ), x λ = x - Wf(x) and 0 ^ λ ^ 1/Z", Condition III and the mean value theorem imply the inequality f(x λ ) f(x) ^ - (λ - X 2 K) I Pf(x) 2 which in turn implies that x λ e S*(x, δ) for λ x ^ λ ^ λ 2, λ< so that S*(x, d) is a nonempty subset of S(x Q ). If {^fc )Γ=o is any sequence for which x k+1, δ), k =0,1, 2,, then (1) implies that sequence {f(x k )}~= 0, which is bounded below, is monotone nonincreasing and hence that Vf(x k ) \ * 0 as k > oo. The remainder of the theorem follows from Condition IV. COROLLARY 1. (The Steepest Descent Algorithm) If x k+1 = x k - -Lj7/(a? 4 ), k = 0, 1, 2, Δίί. then the sequence {x k }^=Q converges to the point x* which minimizes f. Proof. It follows from the proof of the convergence theorem that the sequence {x k }^= 0 defined in the statement of Corollary 1 is such that x k+1, 1/4Z), k = 0,1, 2,.. COROLLARY 2. (The Modified Steepest Descent Algorithm) If a is an arbitrarily assigned positive number, a m = a/2 m ~\ m = 1, 2,, and x k+1 = x k cc mj Pf(x k ) where m k is the smallest positive integer for which ( 2) f(x k - a m /f(x k )) - f(x k ) ^ - \a mh \ Ff(x k ) 2, k = 0, 1, 2,, then the sequence {x k }ΐ= 0 converges to the point x* which minimizes f. Proof. It follows from the proof of the convergence theorem that if x e S(x Q ) and x λ =x - \Pf(x), then f(x λ ) - f(x) ^ - (1/2) λ Vf(x) 2 for 0 ^ λ ^ 1J2K. If a ^ l/2iγ, then for the sequence {x k }ΐ= 0 in the statement of Corollary 2, m k = 1 and x k+1, (l/2)a), k = 0,1, 2,. If a > 1/2Z", then the integers m^ exist and a mfc > l/4iγ so that

MINIMIZATION OF FUNCTIONS 3 3* Discussion* The convergence theorem proves convergence under hypotheses which are more restrictive than those imposed by Curry [1] but less restrictive than those imposed by Goldstein [2]. However, both the algorithms which we have considered would be considerably easier to apply than the algorithm proposed by Curry since his algorithm requires the minimization of a function of one variable at each step. The method of Goldstein requires the assumption that fec 2 on S(x 0 ) and that S(x 0 ) be bounded. It also requires knowledge of a bound for the norm of the Hessian matrix of / on S(x 0 ), but yields an estimate for the ultimate rate of convergence of the gradient method. It should be pointed out that the modified steepest descent algorithm of Corollary 2 allows for the possibility of variable stepsize and does not require knowledge of the value of the Lipschitz constant K. The author is indebted to the referee for his comments and suggestions. REFERENCES 1. H. B. Curry, The method of steepest descent for nonlinear minimization problems, Quart. Appl. Math. 2 (1944), 258-263. '2. A. A. Goldstein, Cauchy's method of minimization, Numer. Math. 4 (2), (1962), 146-150.

PACIFIC JOURNAL OF MATHEMATICS H. SAMELSON Stanford University Stanford, California R. M. BLUMENTHAL University of Washington Seattle, Washington 98105 EDITORS *J. DUGUNDJI University of Southern California Los Angeles, California 90007 RICHARD ARENS University of California Los Angeles, California 90024 ASSOCIATE EDITORS E. F. BECKENBACH B. H. NEUMANN F. WOLF K. YOSIDA UNIVERSITY OF BRITISH COLUMBIA CALIFORNIA INSTITUTE OF TECHNOLOGY UNIVERSITY OF CALIFORNIA MONTANA STATE UNIVERSITY UNIVERSITY OF NEVADA NEW MEXICO STATE UNIVERSITY OREGON STATE UNIVERSITY UNIVERSITY OF OREGON OSAKA UNIVERSITY UNIVERSITY OF SOUTHERN CALIFORNIA SUPPORTING INSTITUTIONS STANFORD UNIVERSITY UNIVERSITY OF TOKYO UNIVERSITY OF UTAH WASHINGTON STATE UNIVERSITY UNIVERSITY OF WASHINGTON * * * AMERICAN MATHEMATICAL SOCIETY CHEVRON RESEARCH CORPORATION TRW SYSTEMS NAVAL ORDNANCE TEST STATION Printed in Japan by International Academic Printing Co., Ltd., Tokyo Japan

Pacific Journal of Mathematics Vol. 16, No. 1 November, 1966 Larry Armijo, Minimization of functions having Lipschitz continuous first partial derivatives................................................ 1 Edward Martin Bolger and William Leonard Harkness, Some characterizations of exponential-type distributions................... 5 James Russell Brown, Approximation theorems for Markov operators...... 13 Doyle Otis Cutler, Quasi-isomorphism for infinite Abelian p-groups....... 25 Charles M. Glennie, Some identities valid in special Jordan algebras but not valid in all Jordan algebras....................................... 47 Thomas William Hungerford, A description of Mult i (A 1,, A n ) by generators and relations.......................................... 61 James Henry Jordan, The distribution of cubic and quintic non-residues.... 77 Junius Colby Kegley, Convexity with respect to Euler-Lagrange differential operators........................................................ 87 Tilla Weinstein, On the determination of conformal imbedding............ 113 Paul Jacob Koosis, On the spectral analysis of bounded functions.......... 121 Jean-Pierre Kahane, On the construction of certain bounded continuous functions........................................................ 129 V. V. Menon, A theorem on partitions of mass-distribution................ 133 Ronald C. Mullin, The enumeration of Hamiltonian polygons in triangular maps............................................................ 139 Eugene Elliot Robkin and F. A. Valentine, Families of parallels associated with sets......................................................... 147 Melvin Rosenfeld, Commutative F-algebras............................ 159 A. Seidenberg, Derivations and integral closure......................... 167 S. Verblunsky, On the stability of the set of exponents of a Cauchy exponential series................................................ 175 Herbert Walum, Some averages of character sums....................... 189