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Minimum Leaf OutBranching Problems
 Lect. Notes Comput. Sci. 5034 (2008), 235–246 (Proc. AAIM’08
, 2008
"... Abstract. Given a digraph D, the Minimum Leaf OutBranching problem (MinLOB) is the problem of finding in D an outbranching with the minimum possible number of leaves, i.e., vertices of outdegree 0. We describe three parameterizations of MinLOB and prove that two of them are NPcomplete for every ..."
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Cited by 13 (3 self)
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Abstract. Given a digraph D, the Minimum Leaf OutBranching problem (MinLOB) is the problem of finding in D an outbranching with the minimum possible number of leaves, i.e., vertices of outdegree 0. We describe three parameterizations of MinLOB and prove that two of them are NPcomplete for every
Minimum Leaf Outbranching and Related Problems
, 2008
"... Given a digraph D, the Minimum Leaf OutBranching problem (MinLOB) is the problem of finding in D an outbranching with the minimum possible number of leaves, i.e., vertices of outdegree 0. We prove that MinLOB is polynomialtime solvable for acyclic digraphs. In general, MinLOB is NPhard and we co ..."
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Cited by 9 (0 self)
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Given a digraph D, the Minimum Leaf OutBranching problem (MinLOB) is the problem of finding in D an outbranching with the minimum possible number of leaves, i.e., vertices of outdegree 0. We prove that MinLOB is polynomialtime solvable for acyclic digraphs. In general, MinLOB is NPhard and we
Outbranchings with Extremal Number of Leaves
"... A subdigraph T of a digraph D is called an outtree if T is an oriented tree with just one vertex s of indegree zero. A spanning outtree is called an outbranching. A vertex x of an outbranching B is called a leaf if d + B (x) = 0. This is mainly a survey paper on outbranchings with minimum and ..."
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A subdigraph T of a digraph D is called an outtree if T is an oriented tree with just one vertex s of indegree zero. A spanning outtree is called an outbranching. A vertex x of an outbranching B is called a leaf if d + B (x) = 0. This is mainly a survey paper on outbranchings with minimum
Cliquewidth: When Hard Does Not Mean Impossible
, 2011
"... In recent years, the parameterized complexity approach has lead to the introduction of many new algorithms and frameworks on graphs and digraphs of bounded cliquewidth and, equivalently, rankwidth. However, despite intensive work on the subject, there still exist wellestablished hard problems whe ..."
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Cited by 1 (0 self)
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where neither a parameterized algorithm nor a theoretical obstacle to its existence are known. Our article is interested mainly in the digraph case, targeting the wellknown Minimum Leaf OutBranching (cf. also Minimum Leaf Spanning Tree) and Edge Disjoint Paths problems on digraphs of bounded clique
Where the REALLY Hard Problems Are
 IN J. MYLOPOULOS AND R. REITER (EDS.), PROCEEDINGS OF 12TH INTERNATIONAL JOINT CONFERENCE ON AI (IJCAI91),VOLUME 1
, 1991
"... It is well known that for many NPcomplete problems, such as KSat, etc., typical cases are easy to solve; so that computationally hard cases must be rare (assuming P != NP). This paper shows that NPcomplete problems can be summarized by at least one "order parameter", and that the hard p ..."
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Cited by 681 (1 self)
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It is well known that for many NPcomplete problems, such as KSat, etc., typical cases are easy to solve; so that computationally hard cases must be rare (assuming P != NP). This paper shows that NPcomplete problems can be summarized by at least one "order parameter", and that the hard
Irrelevant Features and the Subset Selection Problem
 MACHINE LEARNING: PROCEEDINGS OF THE ELEVENTH INTERNATIONAL
, 1994
"... We address the problem of finding a subset of features that allows a supervised induction algorithm to induce small highaccuracy concepts. We examine notions of relevance and irrelevance, and show that the definitions used in the machine learning literature do not adequately partition the features ..."
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Cited by 741 (26 self)
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We address the problem of finding a subset of features that allows a supervised induction algorithm to induce small highaccuracy concepts. We examine notions of relevance and irrelevance, and show that the definitions used in the machine learning literature do not adequately partition the features
Solving multiclass learning problems via errorcorrecting output codes
 JOURNAL OF ARTIFICIAL INTELLIGENCE RESEARCH
, 1995
"... Multiclass learning problems involve nding a de nition for an unknown function f(x) whose range is a discrete set containing k>2values (i.e., k \classes"). The de nition is acquired by studying collections of training examples of the form hx i;f(x i)i. Existing approaches to multiclass l ..."
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Cited by 730 (8 self)
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Multiclass learning problems involve nding a de nition for an unknown function f(x) whose range is a discrete set containing k>2values (i.e., k \classes"). The de nition is acquired by studying collections of training examples of the form hx i;f(x i)i. Existing approaches to multiclass
Fast Folding and Comparison of RNA Secondary Structures (The Vienna RNA Package)
"... Computer codes for computation and comparison of RNA secondary structures, the Vienna RNA package, are presented, that are based on dynamic programming algorithms and aim at predictions of structures with minimum free energies as well as at computations of the equilibrium partition functions and bas ..."
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Cited by 812 (119 self)
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Computer codes for computation and comparison of RNA secondary structures, the Vienna RNA package, are presented, that are based on dynamic programming algorithms and aim at predictions of structures with minimum free energies as well as at computations of the equilibrium partition functions
Fast Algorithms for Mining Association Rules
, 1994
"... We consider the problem of discovering association rules between items in a large database of sales transactions. We present two new algorithms for solving this problem that are fundamentally different from the known algorithms. Empirical evaluation shows that these algorithms outperform the known a ..."
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Cited by 3551 (15 self)
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We consider the problem of discovering association rules between items in a large database of sales transactions. We present two new algorithms for solving this problem that are fundamentally different from the known algorithms. Empirical evaluation shows that these algorithms outperform the known
Results 1  10
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433,564