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Key Ideas of Multigrid
"... CG only works for SPD matrices. It minimizes ‖x − x ∗ ‖A and φ(x) = 1 2 x T Ax − x T b There have been many proposed extensions to nonsymmetric matrices, GMRES, BiCG, etc. GMRES (Generalized Minimal RESiduals) is one of most well known The basic idea of GMRES is to find xn ∈ Kn that minimizes ‖rn ‖ ..."
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CG only works for SPD matrices. It minimizes ‖x − x ∗ ‖A and φ(x) = 1 2 x T Ax − x T b There have been many proposed extensions to nonsymmetric matrices, GMRES, BiCG, etc. GMRES (Generalized Minimal RESiduals) is one of most well known The basic idea of GMRES is to find xn ∈ Kn that minimizes ‖rn
• The key idea of Random Linear
"... Network Coding (RLNC) is to linearly combine (“mix”) packets at the intermediate nodes Benefit: A higher throughput compared to routing can be achieved Problem: High error propagation due to linear combination of packets Error Control in Random Linear Network Coding [1] • The rowspace of the transmi ..."
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Network Coding (RLNC) is to linearly combine (“mix”) packets at the intermediate nodes Benefit: A higher throughput compared to routing can be achieved Problem: High error propagation due to linear combination of packets Error Control in Random Linear Network Coding [1] • The rowspace of the transmitted packets is preserved by the linear operations of the network • Data can be transmitted by choosing a subspace and transmitting a basis of the subspace • Topology and combinations don’t have to be known by the transmitter and the receiver ⇒ noncoherent coding • Choosing subspaces that are separated with respect to a distance metric allows to correct errors and erasures The Channel Model As channel model we use the operator channel from [1]. Denote by Fq the finite field of order q and by Fqm its extension field of degree m. Any element in Fqm can be represented by a length m vector over Fq. Hnt−δ(V) ⊕ E V U • Input: ntdimensional subspace V over Fq • Hnt−δ(V) returns a random (nt − δ)dimensional subspace of V • γdimensional error space E (not contained in V) • Output: (nr = nt − δ + γ)dimensional subspace U over Fq ⇒ δ deletions and γ insertions
Collaborative Discovering Of Key Ideas In Knowledge Building
 In Stahl, G (Eds.) Proceedings of the CSCL 2002 Conference
, 2002
"... In this paper, we describe our workinprogress for developing Collaborative Discovering Tool (CoDi tool) that is meant for enhancing knowledge building environment in the Fle2 system. Knowledgebuilding discourse in Fle2 type of systems usually leads to gradual accumulation of notes so that the use ..."
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Cited by 11 (1 self)
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that the users find it very difficult to get an overall picture of knowledge produced and synthesize knowledge advancement. By providing means for the participants to mark key ideas that they find particularly useful, the CoDi tool is designed to facilitate collective management of knowledge and inquiry
Image retrieval: ideas, influences, and trends of the new age
 ACM COMPUTING SURVEYS
, 2008
"... We have witnessed great interest and a wealth of promise in contentbased image retrieval as an emerging technology. While the last decade laid foundation to such promise, it also paved the way for a large number of new techniques and systems, got many new people involved, and triggered stronger ass ..."
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Cited by 486 (13 self)
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association of weakly related fields. In this article, we survey almost 300 key theoretical and empirical contributions in the current decade related to image retrieval and automatic image annotation, and in the process discuss the spawning of related subfields. We also discuss significant challenges involved
Comments on Broadcast Channels
, 1998
"... The key ideas in the theory of broadcast channels are illustrated by discussing some of the progress toward finding the capacity region. The capacity region is still unknown. Index TermsBinning, broadcast channel, capacity, degraded broadcast channel, feedback capacity, SlepianWolf, superposit ..."
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Cited by 571 (0 self)
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The key ideas in the theory of broadcast channels are illustrated by discussing some of the progress toward finding the capacity region. The capacity region is still unknown. Index TermsBinning, broadcast channel, capacity, degraded broadcast channel, feedback capacity, Slepian
A summary of key ideas and recent developments
, 2008
"... We summarize the theory and phenomenology of the Color Glass Condensate reviewed previously by E. Iancu and the author in hepph/0303204. In addition, we discuss some of the subsequent developments in the past year both in theory and in phenomenological applications. 1 ..."
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We summarize the theory and phenomenology of the Color Glass Condensate reviewed previously by E. Iancu and the author in hepph/0303204. In addition, we discuss some of the subsequent developments in the past year both in theory and in phenomenological applications. 1
An affine invariant interest point detector
 In Proceedings of the 7th European Conference on Computer Vision
, 2002
"... Abstract. This paper presents a novel approach for detecting affine invariant interest points. Our method can deal with significant affine transformations including large scale changes. Such transformations introduce significant changes in the point location as well as in the scale and the shape of ..."
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Cited by 1473 (55 self)
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of the neighbourhood of an interest point. Our approach allows to solve for these problems simultaneously. It is based on three key ideas: 1) The second moment matrix computed in a point can be used to normalize a region in an affine invariant way (skew and stretch). 2) The scale of the local structure is indicated
GPFS: A SharedDisk File System for Large Computing Clusters
 In Proceedings of the 2002 Conference on File and Storage Technologies (FAST
, 2002
"... GPFS is IBM's parallel, shareddisk file system for cluster computers, available on the RS/6000 SP parallel supercomputer and on Linux clusters. GPFS is used on many of the largest supercomputers in the world. GPFS was built on many of the ideas that were developed in the academic community ove ..."
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Cited by 521 (3 self)
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existing ideas scaled well, new approaches were necessary in many key areas. This paper describes GPFS, and discusses how distributed locking and recovery techniques were extended to scale to large clusters.
Bayesian Data Analysis
, 1995
"... I actually own a copy of Harold Jeffreys’s Theory of Probability but have only read small bits of it, most recently over a decade ago to confirm that, indeed, Jeffreys was not too proud to use a classical chisquared pvalue when he wanted to check the misfit of a model to data (Gelman, Meng and Ste ..."
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Cited by 2186 (63 self)
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the following: (1) in thinking about prior distributions, we should go beyond Jeffreys’s principles and move toward weakly informative priors; (2) it is natural for those of us who work in social and computational sciences to favor complex models, contra Jeffreys’s preference for simplicity; and (3) a key
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