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Ker-I Ko

dblp:45/2707 · DBLP profile ↗
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64ranked-venue papers
46as first author
1since 2021 · last 2021
—ORCID · none

Domains — the database's venue-derived domains; a paper can count in several

Theory of computation · 61 · 44 first-author · 1 since 2021Applied, interdisciplinary, general and emerging computing · 2 · 1 first-authorArtificial intelligence and machine learning · 1 · 1 first-authorDatabases, data management, data science and information retrieval · 1 · 1 first-author

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Theoretical computer science
19 papers
Computational complexity · 75% Computational geometry · 17% Mathematical optimization · 4%
Artificial intelligence
1 paper
Learning theory · 100%

Topics — the 29 heaviest of 33, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Computational complexity › complexity classes
polynomial hierarchy
0.041990
Separating and Collapsing Results on the Relativized Probabilistic Polynomial-Time Hierarchy · J. ACM 1990
Relativized Polynomial Time Hierarchies Having Exactly K Levels · SIAM J. Comput. 1989
Relativized Polynominal Time Hierarchies Having Exactly K Levels · STOC 1988
Computational geometry
geometric complexity
0.021995
Computational Complexity of Two-Dimensional Regions · SIAM J. Comput. 1995
Some complexity issues on the simply connected regions of the two-dimensional plane · STOC 1993
Computational complexity › computability theory
computable analysis
0.011996
On the Measure of Two-Dimensional Regions with Polynomial-Time computables Boundaries · CCC 1996
Computational complexity › relativization
oracle separation
0.031991
Separating and Collapsing Results on the Relativized Probabilistic Polynomial-Time Hierarchy · J. ACM 1990
Relativized Polynomial Time Hierarchies Having Exactly K Levels · SIAM J. Comput. 1989
Separating the Low and High Hierarchies by Oracles · Inf. Comput. 1991
Computational complexity
relativization
0.021991
On the Complexity of Learning Minimum Time-Bounded Turing Machines · SIAM J. Comput. 1991
Separating and Collapsing Results on the Relativized Probabilistic Polynomial-Time Hierarchy · J. ACM 1990
Computational complexity › complexity classes
polynomial-time computability
0.011995
Computational Complexity of Two-Dimensional Regions · SIAM J. Comput. 1995
Computational geometry › computational topology
winding number
0.011995
Computational Complexity of Two-Dimensional Regions · SIAM J. Comput. 1995
Computational complexity › complexity measures
instance complexity
0.011994
Instance Complexity · J. ACM 1994
Computational complexity
reduction
0.021989
Distinguishing Conjunctive and Disjunctive Reducibilities by Sparse Sets · Inf. Comput. 1989
On Sets Truth-Table Reducible to Sparse Sets · SIAM J. Comput. 1988
Computational complexity
circuit complexity
0.021988
On Sets Truth-Table Reducible to Sparse Sets · SIAM J. Comput. 1988
On Circuit-Size Complexity and the Low Hierarchy in NP · SIAM J. Comput. 1985
Computational complexity › circuit complexity › circuit size
polynomial-size circuits
0.021988
On Sets Truth-Table Reducible to Sparse Sets · SIAM J. Comput. 1988
On Circuit-Size Complexity and the Low Hierarchy in NP · SIAM J. Comput. 1985
Computational complexity › structural complexity
complexity hierarchies
0.011991
Separating the Low and High Hierarchies by Oracles · Inf. Comput. 1991
Computational complexity › complexity classes › EXPTIME
EXPTIME-completeness
0.011991
Integral Equations, Systems of Quadratic Equations, and Exponential-Time Completeness (Extended Abstract) · STOC 1991
Mathematical optimization
integral equations
0.011991
Integral Equations, Systems of Quadratic Equations, and Exponential-Time Completeness (Extended Abstract) · STOC 1991
Computational complexity › structural complexity › complexity hierarchies
low hierarchy
0.011991
Separating the Low and High Hierarchies by Oracles · Inf. Comput. 1991
Computational complexity › structural complexity
sparse sets
0.021989
On Sets Truth-Table Reducible to Sparse Sets · SIAM J. Comput. 1988
Distinguishing Conjunctive and Disjunctive Reducibilities by Sparse Sets · Inf. Comput. 1989
Computational complexity
complexity classes
0.011989
Computational Complexity of Roots of Real Functions (Extended Abstract) · FOCS 1989
Computational complexity › reduction
truth-table reducibility
0.011988
On Sets Truth-Table Reducible to Sparse Sets · SIAM J. Comput. 1988
Computational complexity
complexity of numerical computation
0.021983
On the Computational Complexity of Ordinary Differential Equations · Inf. Control. 1983
Some Negative Results on the Computational Complexity of Total Variation and Differentiation · Inf. Control. 1982
Automata and formal languages › language learning
language identification
0.011987
Identification of Pattern Languages from Examples and Queries · Inf. Comput. 1987
Automata and formal languages › formal language classes
pattern languages
0.011987
Identification of Pattern Languages from Examples and Queries · Inf. Comput. 1987
Cryptographic primitives and cryptanalysis
one-way functions
0.011986
A Note on One-Way Functions and Polynomial-Time Isomorphisms (Extended Abstract) · STOC 1986
Computational complexity › cryptographic complexity
one-way functions
0.011986
A Note on One-Way Functions and Polynomial-Time Isomorphisms (Extended Abstract) · STOC 1986
Computational complexity › decision problems › isomorphism problems
polynomial-time isomorphism
0.011986
A Note on One-Way Functions and Polynomial-Time Isomorphisms (Extended Abstract) · STOC 1986
Computational complexity
kolmogorov complexity
0.011994
Instance Complexity · J. ACM 1994
Mathematical optimization
ordinary differential equation
0.011983
On the Computational Complexity of Ordinary Differential Equations · Inf. Control. 1983
Approximation and online algorithms › approximation algorithms
polynomial-time approximation
0.011981
Completeness, Approximation and Density · SIAM J. Comput. 1981
Computational complexity
structural complexity
0.011981
Completeness, Approximation and Density · SIAM J. Comput. 1981
Mathematical optimization
numerical computation
0.011989
Computational Complexity of Roots of Real Functions (Extended Abstract) · FOCS 1989

Methods — techniques the papers use, named apart from their topics

relativization · 0.0left r.e. real · 0.0computable real number · 0.0discrete computational model · 0.0time-bounded complexity · 0.0special-case program · 0.0completeness reduction · 0.0inductive inference · 0.0reduction · 0.0complexity classification · 0.0structural complexity theory · 0.0isomorphism theory · 0.0
YearPublicationVenuePosition
2021 On continuous one-way functions
Ker-I Ko, Lidong Wu
Theor. Comput. Sci.1
2017 Competitive profit maximization in social networks
Weian Li, Xiaoying Qu, Qizhi Fang, Ker-I Ko
Theor. Comput. Sci.6
2013 On the complexity of computing the Hausdorff distance
Ker-I Ko
J. Complex.1
2013 On logarithmic-space computable real numbers
Fuxiang Yu, Ker-I Ko
Theor. Comput. Sci.2
2013 On parallel complexity of analytic functions
Fuxiang Yu, Ker-I Ko
Theor. Comput. Sci.2
2009 CCA 2009 Front Matter - Proceedings of the Sixth International Conference on Computability and Complexity in Analysis
Andrej Bauer, Peter Hertling, Ker-I Ko
CCA3
2009 CCA 2009 Preface - Proceedings of the Sixth International Conference on Computability and Complexity in Analysis
Andrej Bauer, Peter Hertling, Ker-I Ko
CCA3
2008 On the complexity of non-unique probe selection
Yongxi Cheng, Ker-I Ko, Weili Wu 0001
Theor. Comput. Sci.2
2007 On the complexity of computing the logarithm and square root functions on a complex domain
Ker-I Ko, Fuxiang Yu
J. Complex.1
2007 Jordan curves with polynomial inverse moduli of continuity
Ker-I Ko, Fuxiang Yu
Theor. Comput. Sci.1
2006 Computability and complexity in analysis
Vasco Brattka, Peter Hertling, Ker-I Ko, Hideki Tsuiki
J. Complex.3
2006 On the complexity of finding circumscribed rectangles and squares for a two-dimensional domain
Fuxiang Yu, Arthur W. Chou, Ker-I Ko
J. Complex.3
2005 On the Complexity of Finding Circumscribed Rectangles for a Two-Dimensional Domain
Fuxiang Yu, Arthur W. Chou, Ker-I Ko
CCA3
2005 On the Complexity of Computing the Logarithm and Square Root Functions on a Complex Domain
Ker-I Ko, Fuxiang Yu
COCOON1
2005 The computational complexity of distance functions of two-dimensional domains
Arthur W. Chou, Ker-I Ko
Theor. Comput. Sci.2
2004 A greedy approximation for minimum connected dominating sets
Lu Ruan 0001, Hongwei Du 0001, Xiaohua Jia, Weili Wu 0001, Yingshu Li 0001, Ker-I Ko
Theor. Comput. Sci.6
2002 Foreword
Ker-I Ko, Anil Nerode, Klaus Weihrauch
Theor. Comput. Sci.1
1998 On the Computability of Fractal Dimensions and Hausdorff Measure
Ker-I Ko
Ann. Pure Appl. Log.1
1998 In Memoriam Ronald V. Book
Ding-Zhu Du, Ker-I Ko
Theor. Comput. Sci.2
1996 On the Measure of Two-Dimensional Regions with Polynomial-Time computables Boundaries
abstract
We study the computability of the Lebesgue measure of a two-dimensional region that has a polynomial-time computable boundary. It is shown that the two-dimensional measure of the boundary itself completely characterizes the computability of the measure of the interior region. Namely, if a polynomial-time computable, simple, closed curve has measure zero, then its interior region must have a computable measure. Conversely, if such a curve has a positive measure, then the measure of its interior region could be any positive, left r.e. real number.
Ker-I Ko, Klaus Weihrauch
CCC1
1995 Computational Complexity of Fixed Points and Intersection Points
Ker-I Ko
J. Complex.1
1995 On the longest circuit in an alterable digraph
Ker-I Ko, Chih-Long Lin
J. Glob. Optim.1
1995 Computational Complexity of Two-Dimensional Regions
abstract
The computational complexity of bounded sets of the two-dimensional plane is studied in the discrete computational model. We introduce four notions of polynomial-time computable sets in ${\bf R}^{2}$ and study their relationship. The computational complexity of the winding number problem, membership problem, distance problem, and area problem is characterized by the relations between discrete complexity classes of the NP theory.
Arthur W. Chou, Ker-I Ko
SIAM J. Comput.2
1995 A Polynomial-Time Computable Curve whose Interior has a Nonrecursive Measure
Ker-I Ko
Theor. Comput. Sci.1
1994 Instance Complexity
abstract
We introduce a measure for the computational complexity of mdiwdual instances of a decision problem and study some of Its properties.The instance complexity of a string ~with respect to a set A and time bound t, ict(x : A). is defined as the size of the smallest special-case program for A that run> m time t,decides x correctly, and makes no mistakes on other strings ("don't know" answers are permitted).We prove that a set A is m P if and only if there exist a polynomial t and a constant c such that ic'(x : A) < c for all X; on the other hand, If A ]s NP-hard and P # NP, then for all polynomials t and constants c. lc'(~: A) > c log I ~I for ]nfimtely many x.Obserwng that Kf(x), the t-bounded Kolmogorov complexity of x, N roughly an upper bound on ]Ct(.t: A), we proceed to investigate the existence of mdiwdually hard problem Instances.].e , strings whose instance complexity E close to their Kolmogorov complexity.We prove that if t(n) z n is a time-constructible function and A 1s a recurswe set not in DTIME(t), there then exist a constant c and mfimtely many I such that ic'(x : ,4) z K' (x) -c. for some Prehmmary versions of parts of this work have appeared under the titles "What 1s a hard instance of a computational problem?" m Proceedings of tize Conference on Structare m Cornplexm Theory (Berkeley, Calif., June i 986), and "On the instance complexity of NP-hard problems" in Procecduzgs of the 5tk .4nrrualConference on StntctLwe m Cowrpkwty Theory (Barcelona, Spain, July 1990).
Pekka Orponen, Ker-I Ko, Uwe Schöning, Osamu Watanabe 0001
J. ACM2
1993 Some complexity issues on the simply connected regions of the two-dimensional plane
abstract
Article Some complexity issues on the simply connected regions of the two-dimensional plane Share on Authors: Arthur W. Chou View Profile , Ker-I Ko View Profile Authors Info & Claims STOC '93: Proceedings of the twenty-fifth annual ACM symposium on Theory of ComputingJune 1993 Pages 1–10https://doi.org/10.1145/167088.167093Online:01 June 1993Publication History 2citation145DownloadsMetricsTotal Citations2Total Downloads145Last 12 Months7Last 6 weeks1 Get Citation AlertsNew Citation Alert added!This alert has been successfully added and will be sent to:You will be notified whenever a record that you have chosen has been cited.To manage your alert preferences, click on the button below.Manage my AlertsNew Citation Alert!Please log in to your account Save to BinderSave to BinderCreate a New BinderNameCancelCreateExport CitationPublisher SiteGet Access
Arthur W. Chou, Ker-I Ko
STOC2
1992 On the Computational Complexity of Integral Equations
Ker-I Ko
Ann. Pure Appl. Log.1
1992 A note on best fractions of a computable real number
Ding-Zhu Du, Ker-I Ko
J. Complex.2
1991 Integral Equations, Systems of Quadratic Equations, and Exponential-Time Completeness (Extended Abstract)
abstract
Article Free Access Share on Integral equations, systems of quadratic equations, and exponential time completeness Author: Ker-I. Ko Department of Computer Science, State University of New York at Stony Brook, Stony Brook, NY Department of Computer Science, State University of New York at Stony Brook, Stony Brook, NYView Profile Authors Info & Claims STOC '91: Proceedings of the twenty-third annual ACM symposium on Theory of ComputingJanuary 1991 Pages 10–20https://doi.org/10.1145/103418.103427Online:03 January 1991Publication History 1citation374DownloadsMetricsTotal Citations1Total Downloads374Last 12 Months3Last 6 weeks0 Get Citation AlertsNew Citation Alert added!This alert has been successfully added and will be sent to:You will be notified whenever a record that you have chosen has been cited.To manage your alert preferences, click on the button below.Manage my AlertsNew Citation Alert!Please log in to your account Save to BinderSave to BinderCreate a New BinderNameCancelCreateExport CitationPublisher SiteeReaderPDF
Ker-I Ko
STOC1
1991 Three Sigma^p_2-Complete Problems in Computational Learning Theory
Ker-I Ko, Wen-Guey Tzeng
Comput. Complex.1
1991 Separating the Low and High Hierarchies by Oracles
Ker-I Ko
Inf. Comput.1
1991 On the Complexity of Learning Minimum Time-Bounded Turing Machines
abstract
The following problems about time-bounded program-size complexity are studied: (1) for a given string x, a size bound s, and a time bound t, whether there exists a Turing machine of size less than or equal to s that prints x in t moves; (2) for two given finite sets Y and Z of strings, a size bound s, and a time bound t, whether there exists a Turing machine of size less than or equal to s that operates in time t and accepts all $y \in Y$ and rejects all $z \in Z$. These problems are fundamental in complexity theory and feasible learning theory. The complexity of these problems is apparently between P and $NP$, but appears very difficult to classify precisely. These problems are attacked by the approach of relativization. It is shown that for certain variations of the problems, they could be either polynomial-time computable or not polynomial-time computable, depending on different oracles. Furthermore, there are oracles relative to which they are not complete for $NP$ under the polynomial-time Turing reductions, but are complete for $NP$ under the strong $NP$ reductions.
Ker-I Ko
SIAM J. Comput.1
1991 On Adaptive Versus Nonadaptive Bounded Query Machines
Ker-I Ko
Theor. Comput. Sci.1
1990 Learning String Patterns and Tree Patterns from Examples
Ker-I Ko, Assaf Marron, Wen-Guey Tzeng
ML1
1990 Separating and Collapsing Results on the Relativized Probabilistic Polynomial-Time Hierarchy
abstract
The probabilistic polynomial-time hierarchy (BPH) is the hierarchy generated by applying the BP-operator to the Meyer-Stockmeyer polynomial-time hierarchy (PH), where the BP-operator is the natural generalization of the probabilistic complexity class BPP. The similarity and difference between the two hierarchies BPH and PH is investigated. Oracles A and B are constructed such that both PH( A ) and PH( B ) are infinite while BPH( A ) is not equal to PH( A ) at any level and BPH( B ) is identical to PH( B ) at every level. Similar separating and collapsing results in the case that PH( A ) is finite having exactly k levels are also considered.
Ker-I Ko
J. ACM1
1989 Computational Complexity of Roots of Real Functions (Extended Abstract)
abstract
An attempt is made to give a more accurate classification of the computational complexity of roots of real functions. Attention is focused on the simplest types of functions, namely, one-to-one and k-to-one functions, and the complexity of their roots is characterized in terms of relations between discrete complexity classes, such as LOGSPACE, P, UP, and NP.>
Ker-I Ko
FOCS1
1989 Distinguishing Conjunctive and Disjunctive Reducibilities by Sparse Sets
Ker-I Ko
Inf. Comput.1
1989 Relativized Polynomial Time Hierarchies Having Exactly K Levels
abstract
It is proved that for every integer $k \geqq 0$, there is an oracle $A_k $ relative to which the polynomial time hierarchy collapses so that it has exactly k levels. Furthermore, sets $B_k $ and $C_k $ may be constructed so that, relative to $B_k $, the polynomial time hierarchy has exactly k levels and the class PSPACE coincides with the polynomial time hierarchy, and, relative to $C_k $, the polynomial time hierarchy has exactly k levels and the class PSPACE is different from the polynomial time hierarchy.
Ker-I Ko
SIAM J. Comput.1
1988 Relativized Polynominal Time Hierarchies Having Exactly K Levels
abstract
Article Free Access Share on Relativized polynomial time hierarchies having exactly K levels Author: Ker-I Ko Department of Computer Science, State University of New York at Stony Brook, Stony Brook, NY Department of Computer Science, State University of New York at Stony Brook, Stony Brook, NYView Profile Authors Info & Claims STOC '88: Proceedings of the twentieth annual ACM symposium on Theory of computingJanuary 1988 Pages 245–253https://doi.org/10.1145/62212.62235Online:01 January 1988Publication History 4citation270DownloadsMetricsTotal Citations4Total Downloads270Last 12 Months11Last 6 weeks4 Get Citation AlertsNew Citation Alert added!This alert has been successfully added and will be sent to:You will be notified whenever a record that you have chosen has been cited.To manage your alert preferences, click on the button below.Manage my AlertsNew Citation Alert!Please log in to your account Save to BinderSave to BinderCreate a New BinderNameCancelCreateExport CitationPublisher SiteeReaderPDF
Ker-I Ko
STOC1
1988 On Sets Truth-Table Reducible to Sparse Sets
abstract
We study sets that are truth-table reducible to sparse sets in polynomial time. The principal results are as follows: (1) For every integer $k > 0$, there is a set L and a sparse set S such that $L \leqq _{(k + 1) - tt}^P S$, but there is no sparse set $S'$ such that $L \leqq _{k - tt}^P S'$. (2) There exist a sparse set S and a set L such that $L \leqq _{tt}^P S$ but there is no integer k such that for some sparse $S'$, $L \leqq _{k - tt}^P S'$. (3) The class of sets that are bounded truth-table reducible to tally sets is equal to the class of sets that are many–one reducible to tally sets. (4) The class of sets having polynomial-size circuits is equal to the class of sets that are truth-table reducible to tally sets. Similar results are developed for truth-table reducibilities that are computed nondeterministically in polynomial time or in polynomial space.
Ronald V. Book, Ker-I Ko
SIAM J. Comput.2
1988 Searching for Two Objects by Underweight Feedback
abstract
A group testing problem with two irregular coins and with a test device that detects only an underweight coin is considered. The maximum number of tests required to identify two irregulars, one overweight and one underweight, is known to have a lower bound of $2\log n$. We present a procedure that gives an upper bound of $2\log n + O ( \log \log n\sqrt {\log n} )$.
Ker-I Ko
SIAM J. Discret. Math.1
1987 Identification of Pattern Languages from Examples and Queries
Assaf Marron, Ker-I Ko
Inf. Comput.2
1987 A Note on the Two-Variable Pattern-Finding Problem
Ker-I Ko, Chin-Ming Hua
J. Comput. Syst. Sci.1
1987 On Helping by Robust Oracle Machines
Ker-I Ko
Theor. Comput. Sci.1
1987 Corrigenda: On the Continued Fraction Representation of Computable Real Numbers
Ker-I Ko
Theor. Comput. Sci.1
1986 A Note on One-Way Functions and Polynomial-Time Isomorphisms (Extended Abstract)
abstract
Article Free Access Share on A note on one-way functions and polynomial-time isomorphisms Authors: K I Ko Department of Computer Science, University of Houston, Houston, Tx and Mathematical Sciences Research Institute, Berkeley, Ca. Department of Computer Science, University of Houston, Houston, Tx and Mathematical Sciences Research Institute, Berkeley, Ca.View Profile , T J Long Department of Computer and Information Science, The Ohio State University, Columbus, Oh. Department of Computer and Information Science, The Ohio State University, Columbus, Oh.View Profile , D Z Du Mathematical Sciences Research Institute, Berkeley, Ca. Mathematical Sciences Research Institute, Berkeley, Ca.View Profile Authors Info & Claims STOC '86: Proceedings of the eighteenth annual ACM symposium on Theory of computingNovember 1986 Pages 295–303https://doi.org/10.1145/12130.12160Published:01 November 1986Publication History 4citation223DownloadsMetricsTotal Citations4Total Downloads223Last 12 Months12Last 6 weeks1 Get Citation AlertsNew Citation Alert added!This alert has been successfully added and will be sent to:You will be notified whenever a record that you have chosen has been cited.To manage your alert preferences, click on the button below.Manage my AlertsNew Citation Alert!Please log in to your account Save to BinderSave to BinderCreate a New BinderNameCancelCreateExport CitationPublisher SiteeReaderPDF
Ker-I Ko, Timothy J. Long, Ding-Zhu Du
STOC1
1986 Approximation to measurable functions and its relation to probabilistic computation
Ker-I Ko
Ann. Pure Appl. Log.1
1986 On the computational complexity of best Chebyshev approximations
Ker-I Ko
J. Complex.1
1986 On the Continued Fraction Representation of Computable Real Numbers
Ker-I Ko
Theor. Comput. Sci.1
1986 On the Notion of Infinite Pseudorandom Sequences
Ker-I Ko
Theor. Comput. Sci.1
1986 On One-Way Functions and Polynomial-Time Isomorphisms
Ker-I Ko, Timothy J. Long, Ding-Zhu Du
Theor. Comput. Sci.1
1985 Continuous optimization problems and a polynomial hierarchy of real functions
Ker-I Ko
J. Complex.1
1985 Nonlevelable Sets and Immune Sets in the Accepting Density Hierarchy in NP
Ker-I Ko
Math. Syst. Theory1
1985 On Circuit-Size Complexity and the Low Hierarchy in NP
abstract
Let A be a set having polynomial size circuits. If A is also known to be in NP, then we may conclude that the graph of the polynomial size circuits for A is actually in $\Pi _2^p $. Using this observation, we show that sets in NP which have polynomial size ciruits are in $L_3^p $, the third level of the low hierarchy in NP. By a similar technique, we are able to show that some other intuitively low sets in NP are in $L_2^p $, and even in a certain refinement of $L_2^p $. As a consequence, sparse sets are not strong nondeterministic polynomial time Turing complete in NP unless the polynomial time hierarchy collapses to $\Delta _2^p $.
Ker-I Ko, Uwe Schöning
SIAM J. Comput.1
1985 On Some Natural Complete Operators
Ker-I Ko
Theor. Comput. Sci.1
1984 Reducibilities on Real Numbers
Ker-I Ko
Theor. Comput. Sci.1
1983 On the Computational Complexity of Ordinary Differential Equations
Ker-I Ko
Inf. Control.1
1983 On Self-Reducibility and Weak P-Selectivity
Ker-I Ko
J. Comput. Syst. Sci.1
1983 On the Definitions of some Complexity Classes of Real Numbers
Ker-I Ko
Math. Syst. Theory1
1982 Some Negative Results on the Computational Complexity of Total Variation and Differentiation
Ker-I Ko
Inf. Control.1
1982 Some Observations on the Probabilistic Algorithms and NP-hard Problems
Ker-I Ko
Inf. Process. Lett.1
1982 The Maximum Value Problem and NP Real Numbers
Ker-I Ko
J. Comput. Syst. Sci.1
1982 Computational Complexity of Real Functions
Ker-I Ko, Harvey M. Friedman
Theor. Comput. Sci.1
1981 Completeness, Approximation and Density
abstract
Polynomial time approximations to exponential time computable problems (EXP) are considered from the point of view of structure. Infinitely often speedable and almost everywhere complex problems are studied using the notions of polynomial time productivity and immunity. In particular, the existence of a polynomial time immune set which is not polynomial time approximable at all but which is polynomial time $tt$-complete in EXP is proven. The relationship between completeness and approximability is also studied. It is shown that being polynomial time m-complete in EXP does not provide any control of the probability of erroneous approximations.
Ker-I Ko, Daniel J. Moore
SIAM J. Comput.1