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␈↓ ↓N␈↓α␈↓ W1


␈↓ ↓N␈↓␈↓ ↓bMOST RECENT CS REPORTS - JUNE 1979          ␈↓ π∞␈↓Author:  Tom Michael Mitchell␈↓ 
|(Thesis) 

␈↓ ↓N␈↓    Listed␈α∞below␈α∞are␈α
abstracts␈α∞of␈α∞the␈α
most        ␈↓ π∞␈↓    ABSTRACT:␈α⊃ A␈α⊃method␈α⊃is␈α⊃presented␈α⊂for
␈↓ ↓N␈↓recent␈α∂reports␈α∞published␈α∂by␈α∂the␈α∞Computer         ␈↓ π∞␈↓learning␈α⊃general␈α⊃descriptions␈α⊃of␈α⊃concepts
␈↓ ↓N␈↓Science Department of Stanford University.  ␈↓ π∞␈↓from␈α∞a␈α∞sequence␈α∞of␈α∞positive␈α∂and␈α∞negative
                                            ␈↓ π∞␈↓training␈α∃instances.␈α∀ This␈α∃method␈α∀involves
␈↓ ↓N␈↓    TO␈α REQUEST␈α REPORTS:␈α  Check␈α the              ␈↓ π∞␈↓examining␈α#a␈α#predetermined␈α#space␈α#or
␈↓ ↓N␈↓appropriate␈α⊂places␈α⊂on␈α⊂the␈α⊂enclosed␈α⊂order         ␈↓ π∞␈↓language␈α
of␈αpossible␈α
concept␈αdescriptions,
␈↓ ↓N␈↓form,␈αand␈αreturn␈αthe␈αentire␈αorder␈αform␈α
page        ␈↓ π∞␈↓finding␈αthose␈α
which␈αare␈α
consistent␈αwith␈α
the
␈↓ ↓N␈↓(including␈α
mailing␈α
label)␈α
by␈α
June␈α
29,␈α1979.       ␈↓ π∞␈↓observed␈α⊃training␈α⊃instances.␈α∩ Rather␈α⊃than
␈↓ ↓N␈↓In␈α∞many␈α∞cases␈α∞we␈α∞can␈α∞print␈α∞only␈α∞a␈α∞limited           ␈↓ π∞␈↓use␈α)heuristic␈α(search␈α)techniques␈α(to
␈↓ ↓N␈↓number␈α⊗of␈α∃copies,␈α⊗and␈α∃requests␈α⊗will␈α∃be            ␈↓ π∞␈↓examine␈α∀this␈α∀concept␈α∃description␈α∀space,
␈↓ ↓N␈↓filled␈α
on␈α
a␈α
first␈α
come,␈α
first␈α
serve␈α
basis.␈α If      ␈↓ π∞␈↓the␈α subspace␈α (version␈α space)␈α of␈α∨all
␈↓ ↓N␈↓the␈α∞code␈α∞(FREE)␈α∞is␈α∞printed␈α∞on␈α∞your␈α
mailing         ␈↓ π∞␈↓plausible␈α<concept␈α<descriptions␈α<is
␈↓ ↓N␈↓label,␈αyou␈α
will␈αnot␈α
be␈αcharged␈αfor␈α
hardcopy.       ␈↓ π∞␈↓represented␈α%and␈α$updated␈α%with␈α$each
␈↓ ↓N␈↓This␈α_exemption␈α↔from␈α_payment␈α_is␈α↔limited           ␈↓ π∞␈↓training␈α instance.␈α∨ This␈α version␈α∨space
␈↓ ↓N␈↓primarily␈α⊗to␈α⊗libraries.␈α⊗ (The␈α⊗costs␈α∃shown        ␈↓ π∞␈↓approach␈α=determines␈α=all␈α<concept
␈↓ ↓N␈↓include␈αall␈αapplicable␈αsales␈α
taxes.␈α PLEASE      ␈↓ π∞␈↓descriptions␈α∃consistent␈α∃with␈α⊗the␈α∃training
␈↓ ↓N␈↓SEND␈αNO␈αMONEY␈αNOW,␈αWAIT␈αUNTIL␈αYOU␈αGET              ␈↓ π∞␈↓instances,␈α4without␈α4backtracking␈α3to
␈↓ ↓N␈↓AN INVOICE.)                                ␈↓ π∞␈↓reexamine␈α"past␈α"training␈α"instances␈α"or
                                            ␈↓ π∞␈↓previously rejected concept descriptions.
␈↓ ↓N␈↓    ALTERNATIVELY:␈α2 Copies␈α2of␈α2most
␈↓ ↓N␈↓Stanford␈α⊂CS␈α⊂Reports␈α⊂may␈α⊂be␈α⊃obtained␈α⊂by            ␈↓ π∞␈↓    The␈α?␈αβcomputed␈α?␈αβversion␈α?␈ααspace
␈↓ ↓N␈↓writing␈α (about␈α 2␈α months␈α!after␈α MOST               ␈↓ π∞␈↓summarizes␈α the␈α∨information␈α within␈α∨the
␈↓ ↓N␈↓RECENT␈α⊃CS␈α⊃REPORTS␈α⊃listing)␈α⊃to␈α⊂NATIONAL           ␈↓ π∞␈↓training␈α⊃instances␈α⊃concerning␈α⊃the␈α⊂identity
␈↓ ↓N␈↓TECHNICAL␈α_INFORMATION␈α→SERVICE,␈α_5285            ␈↓ π∞␈↓of␈α↔the␈α⊗concept␈α↔to␈α⊗be␈α↔learned.␈α⊗ Version
␈↓ ↓N␈↓Port␈α$Royal␈α$Road,␈α%Springfield,␈α$Virginia          ␈↓ π∞␈↓spaces␈α⊗are␈α⊗therefore␈α⊗useful␈α↔for␈α⊗making
␈↓ ↓N␈↓22161.␈α) Stanford␈α)Ph.D.␈α)theses␈α)are               ␈↓ π∞␈↓reliable␈αclassifications␈αbased␈αupon␈αpartially
␈↓ ↓N␈↓available␈α≥from␈α≥UNIVERSITY␈α≤MICROFILMS,          ␈↓ π∞␈↓learned␈α$concepts,␈α$and␈α%for␈α$proposing
␈↓ ↓N␈↓300␈α∞North␈α∞Zeeb␈α
Road,␈α∞Ann␈α∞Arbor,␈α
Michigan          ␈↓ π∞␈↓informative␈α!new␈α!training␈α!instances␈α to
␈↓ ↓N␈↓48106.                                      ␈↓ π∞␈↓direct␈α further␈α∨learning.␈α  The␈α uses␈α∨of
␈↓ ↓N␈↓--␈↓ ε∩--                                        ␈↓ π∞␈↓version␈αspaces␈α
for␈αdetecting␈α
inconsistency
␈↓ ↓N␈↓--␈↓ ε∩--                                        ␈↓ π∞␈↓in␈α
the␈α
training␈αinstances,␈α
and␈α
for␈αlearning␈α
in
                                            ␈↓ π∞␈↓the␈α⊗presence␈α⊗of␈α⊗inconsistency␈α⊗are␈α⊗also
␈↓ ↓N␈↓STAN-CS-79-710                              ␈↓ π∞␈↓described.
␈↓ ↓N␈↓    NUMERICAL␈α,COMPUTATION␈α,OF␈α+THE
␈↓ ↓N␈↓SCHWARZ-CHRISTOFFEL TRANSFORMATION          ␈↓ π∞␈↓    Proofs␈α
are␈α
given␈α
for␈α
the␈α
correctness␈αof
                                            ␈↓ π∞␈↓the␈α$method␈α$for␈α%representing␈α$version
␈↓ ↓N␈↓Author:  Lloyd Trefethen                    ␈↓ π∞␈↓spaces,␈α⊗and␈α⊗of␈α⊗the␈α⊗associated␈α∃concept
                                            ␈↓ π∞␈↓learning␈α$algorithm,␈α$for␈α$any␈α#countably
␈↓ ↓N␈↓    ABSTRACT:                               ␈↓ π∞␈↓infinite␈α&concept␈α&description␈α%language.
                                            ␈↓ π∞␈↓Empirical␈α∃results␈α∃obtained␈α∃from␈α∀computer
␈↓ ↓N␈↓No. of pages:  60                           ␈↓ π∞␈↓implementations␈α'in␈α'two␈α(domains␈α'are
␈↓ ↓N␈↓Cost:  $ 3.40                               ␈↓ π∞␈↓presented.␈α∃ The␈α∀version␈α∃space␈α∀approach
␈↓ ↓N␈↓--␈↓ ε∩--                                        ␈↓ π∞␈↓has␈α⊃been␈α⊃implemented␈α⊃as␈α∩one␈α⊃component
                                            ␈↓ π∞␈↓of␈α∞the␈α∞Meta-DENDRAL␈α∞program␈α∞for␈α
learning
␈↓ ↓N␈↓STAN-CS-78-711                              ␈↓ π∞␈↓production␈α∞rules␈α∞in␈α∞the␈α∞domain␈α∞of␈α∞chemical
␈↓ ↓N␈↓    VERSION␈α≥SPACES:␈α≥AN␈α≥APPROACH␈α≤TO              ␈↓ π∞␈↓spectroscopy.␈α∃ Its␈α∃implementation␈α∃in␈α∃this
␈↓ ↓N␈↓CONCEPT LEARNING                            ␈↓ π∞␈↓program is described in detail.
␈↓ ↓N␈↓α␈↓ V2


␈↓ ↓N␈↓No. of pages:  216                          ␈↓ π∞␈↓described␈α∂can␈α∂be␈α∂applied␈α∂and␈α∞generalized
␈↓ ↓N␈↓Cost:  $ 7.75                               ␈↓ π∞␈↓to other matrix equation problems.
␈↓ ↓N␈↓--␈↓ ε∩--
                                            ␈↓ π∞␈↓No. of pages:  50
␈↓ ↓N␈↓STAN-CS-79-712                              ␈↓ π∞␈↓Available in microfiche only.
␈↓ ↓N␈↓    THE ERATA OF COMPUTER PROGRAMMING       ␈↓ π∞␈↓--␈↓ R--

␈↓ ↓N␈↓Author:  Donald E. Knuth

␈↓ ↓N␈↓    ABSTRACT:␈α, This␈α,report␈α,lists␈α,all
␈↓ ↓N␈↓corrections␈α
and␈α
changes␈αof␈α
Volumes␈α
1␈αand
␈↓ ↓N␈↓3␈α
of␈α
␈↓↓The␈α
Art␈α
of␈α
Computer␈α
Programming␈↓,␈α
as␈α
of
␈↓ ↓N␈↓January␈α!5,␈α 1979.␈α! This␈α!updates␈α the
␈↓ ↓N␈↓previous␈α∞list␈α
in␈α∞report␈α
CS-551,␈α∞May␈α
1976.
␈↓ ↓N␈↓The␈α∂second␈α∂edition␈α∂of␈α∂Volume␈α∂2␈α∂has␈α∞been
␈↓ ↓N␈↓delayed␈α∞two␈α
years␈α∞due␈α
to␈α∞the␈α
fact␈α∞that␈α
it
␈↓ ↓N␈↓was␈α∩completely␈α∩revised␈α⊃and␈α∩put␈α∩into␈α⊃the
␈↓ ↓N␈↓TEX␈α=typesetting␈α>language;␈α=since
␈↓ ↓N␈↓publication␈α∩of␈α⊃this␈α∩new␈α⊃edition␈α∩is␈α∩not␈α⊃far
␈↓ ↓N␈↓off,␈α∃no␈α∃changes␈α∃to␈α∃Volume␈α∃2␈α∃are␈α∀listed
␈↓ ↓N␈↓here.

␈↓ ↓N␈↓No. of pages:  58
␈↓ ↓N␈↓Cost:  $ 3.35
␈↓ ↓N␈↓--␈↓ ε∩--

␈↓ ↓N␈↓STAN-CS-79-713
␈↓ ↓N␈↓    A␈αHESSENBERG-SCHUR␈αMETHOD␈αFOR␈αTHE
␈↓ ↓N␈↓PROBLEM AX + XB = C

␈↓ ↓N␈↓Authors:␈α→ Gene␈α_Golub,␈α→Stephen␈α→Nash␈α_&
␈↓ ↓N␈↓Charles Van Loan

␈↓ ↓N␈↓    ABSTRACT:␈α⊃ One␈α⊂of␈α⊃the␈α⊃most␈α⊂effective
␈↓ ↓N␈↓methods␈αfor␈αsolving␈αthe␈αmatrix␈αequation␈αAX
␈↓ ↓N␈↓+␈α
XB␈α∞=␈α
C␈α∞is␈α
the␈α∞Bartels-Stewart␈α
algorithm.
␈↓ ↓N␈↓Key␈α∃to␈α∃this␈α∃technique␈α∃is␈α∃the␈α∃orthogonal
␈↓ ↓N␈↓reduction␈α∃of␈α∃A␈α∃and␈α∃B␈α∃to␈α∃triangular␈α∃form
␈↓ ↓N␈↓using␈α∂the␈α∂QR␈α∞algorithm␈α∂for␈α∂eigenvalues.␈α∞ A
␈↓ ↓N␈↓new␈α⊗method␈α⊗is␈α⊗proposed␈α⊗which␈α⊗differes
␈↓ ↓N␈↓from␈α∂the␈α∂Bartels-Stewart␈α∂algorithm␈α∂in␈α∞that
␈↓ ↓N␈↓A␈αis␈αonly␈αreduced␈αto␈αHessenberg␈αform.␈α
 The
␈↓ ↓N␈↓resulting␈α⊂algorithm␈α∂is␈α⊂between␈α∂30␈α⊂and␈α∂70
␈↓ ↓N␈↓percent␈α(faster␈α(depending␈α(upon␈α'the
␈↓ ↓N␈↓dimensions␈α⊂of␈α⊂the␈α⊂matrices␈α⊂A␈α⊂and␈α⊂B.␈α⊂ The
␈↓ ↓N␈↓stability␈α0of␈α1the␈α0new␈α1method␈α0is
␈↓ ↓N␈↓demonstrated␈α≤through␈α≤a␈α≥roundoff␈α≤error
␈↓ ↓N␈↓analysis␈αand␈αsupported␈αby␈αnumerical␈αtests.
␈↓ ↓N␈↓Finally,␈α⊗it␈α⊗is␈α∃shown␈α⊗how␈α⊗the␈α∃techniques