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Results 1 - 10
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1,488
Optimal Aggregation Algorithms for Middleware
- IN PODS
, 2001
"... Assume that each object in a database has m grades, or scores, one for each of m attributes. For example, an object can have a color grade, that tells how red it is, and a shape grade, that tells how round it is. For each attribute, there is a sorted list, which lists each object and its grade under ..."
Abstract
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Cited by 717 (4 self)
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must access every object in the database, to find its grade under each attribute. Fagin has given an algorithm (“Fagin’s Algorithm”, or FA) that is much more efficient. For some monotone aggregation functions, FA is optimal with high probability in the worst case. We analyze an elegant and remarkably
Improved Approximation Algorithms for Maximum Cut and Satisfiability Problems Using Semidefinite Programming
- Journal of the ACM
, 1995
"... We present randomized approximation algorithms for the maximum cut (MAX CUT) and maximum 2-satisfiability (MAX 2SAT) problems that always deliver solutions of expected value at least .87856 times the optimal value. These algorithms use a simple and elegant technique that randomly rounds the solution ..."
Abstract
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Cited by 1211 (13 self)
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We present randomized approximation algorithms for the maximum cut (MAX CUT) and maximum 2-satisfiability (MAX 2SAT) problems that always deliver solutions of expected value at least .87856 times the optimal value. These algorithms use a simple and elegant technique that randomly rounds
Similarity estimation techniques from rounding algorithms
- In Proc. of 34th STOC
, 2002
"... A locality sensitive hashing scheme is a distribution on a family F of hash functions operating on a collection of objects, such that for two objects x, y, Prh∈F[h(x) = h(y)] = sim(x,y), where sim(x,y) ∈ [0, 1] is some similarity function defined on the collection of objects. Such a scheme leads ..."
Abstract
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Cited by 449 (6 self)
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to a compact representation of objects so that similarity of objects can be estimated from their compact sketches, and also leads to efficient algorithms for approximate nearest neighbor search and clustering. Min-wise independent permutations provide an elegant construction of such a locality
A comparative study of energy minimization methods for Markov random fields
- IN ECCV
, 2006
"... One of the most exciting advances in early vision has been the development of efficient energy minimization algorithms. Many early vision tasks require labeling each pixel with some quantity such as depth or texture. While many such problems can be elegantly expressed in the language of Markov Ran ..."
Abstract
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Cited by 415 (36 self)
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One of the most exciting advances in early vision has been the development of efficient energy minimization algorithms. Many early vision tasks require labeling each pixel with some quantity such as depth or texture. While many such problems can be elegantly expressed in the language of Markov
Segmentation using eigenvectors: A unifying view
- In ICCV
, 1999
"... Automatic grouping and segmentation of images remains a challenging problem in computer vision. Recently, a number of authors have demonstrated good performance on this task using methods that are based on eigenvectors of the a nity matrix. These approaches are extremely attractive in that they are ..."
Abstract
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Cited by 380 (1 self)
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in that they are based on simple eigendecomposition algorithms whose stability is well understood. Nevertheless, the use of eigendecompositions in the context of segmentation is far from well understood. In this paper we give a unied treatment of these algorithms, and show the close connections between them while
The even more irresistible SROIQ
- In KR
, 2006
"... We describe an extension of the description logic underlying OWL-DL, SHOIN, with a number of expressive means that we believe will make it more useful in practise. Roughly speaking, we extend SHOIN with all expressive means that were suggested to us by ontology developers as useful additions to OWL- ..."
Abstract
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Cited by 342 (50 self)
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rather elegant tableau-based reasoning algorithm: it combines the use of automata to keep track of universal value restrictions with the techniques developed for SHOIQ. We believe that SROIQ could serve as a logical basis for possible future extensions of OWL-DL.
Is there an Elegant Universal Theory of Prediction?
- IDSIA / USI-SUPSI DALLE MOLLE INSTITUTE FOR ARTIFICIAL INTELLIGENCE. GALLERIA 2, 6928
, 2006
"... Solomonoff’s inductive learning model is a powerful, universal and highly elegant theory of sequence prediction. Its critical flaw is that it is incomputable and thus cannot be used in practice. It is sometimes suggested that it may still be useful to help guide the development of very general and p ..."
Abstract
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Cited by 7 (0 self)
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Solomonoff’s inductive learning model is a powerful, universal and highly elegant theory of sequence prediction. Its critical flaw is that it is incomputable and thus cannot be used in practice. It is sometimes suggested that it may still be useful to help guide the development of very general
Automating the search for elegant proofs
- J. Automated Reasoning
"... The research reported in this article was spawned by a colleague’s request to find an elegant proof (of a theorem from Boolean algebra) to replace his proof consisting of 816 deduced steps. The request was met by finding a proof consisting of 100 deduced steps. The methodology used to obtain the far ..."
Abstract
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Cited by 8 (4 self)
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the far shorter proof is presented in detail through a sequence of experiments. Although clearly not an algorithm, the methodology is sufficiently general to enable its use for seeking elegant proofs regardless of the domain of study. In addition to (usually) being more elegant, shorter proofs often
Generating Accurate Rule Sets Without Global Optimization
- IN: PROC. OF THE 15TH INT. CONFERENCE ON MACHINE LEARNING
, 1998
"... The two dominant schemes for rule-learning, C4.5 and RIPPER, both operate in two stages. First they induce an initial rule set and then they refine it using a rather complex optimization stage that discards (C4.5) or adjusts (RIPPER) individual rules to make them work better together. In contrast, t ..."
Abstract
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Cited by 269 (7 self)
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and the separate-and-conquer rule-learning technique. The algorithm is straightforward and elegant: despite this, experiments on standard datasets show that it produces rule sets that are as accurate as and of similar size to those generated by C4.5, and more accurate than RIPPER's. Moreover, it operates
Results 1 - 10
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1,488
