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Linearizability: a correctness condition for concurrent objects

by Maurice P. Herlihy, Jeannette M. Wing , 1990
"... A concurrent object is a data object shared by concurrent processes. Linearizability is a correctness condition for concurrent objects that exploits the semantics of abstract data types. It permits a high degree of concurrency, yet it permits programmers to specify and reason about concurrent object ..."
Abstract - Cited by 1178 (28 self) - Add to MetaCart
A concurrent object is a data object shared by concurrent processes. Linearizability is a correctness condition for concurrent objects that exploits the semantics of abstract data types. It permits a high degree of concurrency, yet it permits programmers to specify and reason about concurrent

Synchronous data flow

by Edward A. Lee, et al. , 1987
"... Data flow is a natural paradigm for describing DSP applications for concurrent implementation on parallel hardware. Data flow programs for signal processing are directed graphs where each node represents a function and each arc represents a signal path. Synchronous data flow (SDF) is a special case ..."
Abstract - Cited by 622 (45 self) - Add to MetaCart
with data flow evaporates. Multiple sample rates within the same system are easily and naturally handled. Conditions for correctness of SDF graph are explained and scheduling algorithms are described for homogeneous parallel processors sharing memory. A preliminary SDF software system for automatically

Combining Branch Predictors

by Scott Mcfarling , 1993
"... One of the key factors determining computer performance is the degree to which the implementation can take advantage of instruction-level paral-lelism. Perhaps the most critical limit to this parallelism is the presence of conditional branches that determine which instructions need to be executed ne ..."
Abstract - Cited by 629 (0 self) - Add to MetaCart
One of the key factors determining computer performance is the degree to which the implementation can take advantage of instruction-level paral-lelism. Perhaps the most critical limit to this parallelism is the presence of conditional branches that determine which instructions need to be executed

Loopy belief propagation for approximate inference: An empirical study. In:

by Kevin P Murphy , Yair Weiss , Michael I Jordan - Proceedings of Uncertainty in AI, , 1999
"... Abstract Recently, researchers have demonstrated that "loopy belief propagation" -the use of Pearl's polytree algorithm in a Bayesian network with loops -can perform well in the context of error-correcting codes. The most dramatic instance of this is the near Shannon-limit performanc ..."
Abstract - Cited by 676 (15 self) - Add to MetaCart
;belief revision") version, Weiss For the case of networks with multiple loops, Richard son To summarize, what is currently known about loopy propagation is that ( 1) it works very well in an error correcting code setting and (2) there are conditions for a single-loop network for which it can be guaranteed

Dynamic capabilities and strategic management

by David J. Teece, Gary Pisano, Amy Shuen - Strategic Management Journal , 1997
"... The dynamic capabilities framework analyzes the sources and methods of wealth creation and capture by private enterprise firms operating in environments of rapid technological change. The competitive advantage of firms is seen as resting on distinctive processes (ways of coordinating and combining), ..."
Abstract - Cited by 1792 (7 self) - Add to MetaCart
), shaped by the firm’s (specific) asset positions (such as the firm’s portfolio of difficult-to-trade knowledge assets and complementary assets), and the evolution path(s) it has adopted or inherited. The importance of path dependencies is amplified where conditions of increasing returns exist. Whether

Design of capacity-approaching irregular low-density parity-check codes

by Thomas J. Richardson, M. Amin Shokrollahi, Rüdiger L. Urbanke - IEEE TRANS. INFORM. THEORY , 2001
"... We design low-density parity-check (LDPC) codes that perform at rates extremely close to the Shannon capacity. The codes are built from highly irregular bipartite graphs with carefully chosen degree patterns on both sides. Our theoretical analysis of the codes is based on [1]. Assuming that the unde ..."
Abstract - Cited by 588 (6 self) - Add to MetaCart
to infinity. Furthermore, we prove a stability condition which implies an upper bound on the fraction of errors that a belief-propagation decoder can correct when applied to a code induced from a bipartite graph with a given degree distribution. Our codes are found by optimizing the degree structure

Constructing Free Energy Approximations and Generalized Belief Propagation Algorithms

by Jonathan S. Yedidia, William T. Freeman, Yair Weiss - IEEE Transactions on Information Theory , 2005
"... Important inference problems in statistical physics, computer vision, error-correcting coding theory, and artificial intelligence can all be reformulated as the computation of marginal probabilities on factor graphs. The belief propagation (BP) algorithm is an efficient way to solve these problems t ..."
Abstract - Cited by 585 (13 self) - Add to MetaCart
Important inference problems in statistical physics, computer vision, error-correcting coding theory, and artificial intelligence can all be reformulated as the computation of marginal probabilities on factor graphs. The belief propagation (BP) algorithm is an efficient way to solve these problems

Base-calling of automated sequencer traces using phred. I. Accuracy Assessment

by Brent Ewing, Ladeana Hillier, Michael C. Wendl, Phil Green - GENOME RES , 1998
"... The availability of massive amounts of DNA sequence information has begun to revolutionize the practice of biology. As a result, current large-scale sequencing output, while impressive, is not adequate to keep pace with growing demand and, in particular, is far short of what will be required to obta ..."
Abstract - Cited by 1653 (4 self) - Add to MetaCart
improved accuracy of the data processing software and reliable accuracy measures to reduce the need for human involvement in error correction and make human review more efficient. Here, we describe one step toward that goal: a base-calling program for automated sequencer traces, phred, with improved

Variable Selection via Nonconcave Penalized Likelihood and its Oracle Properties

by Jianqing Fan , Runze Li , 2001
"... Variable selection is fundamental to high-dimensional statistical modeling, including nonparametric regression. Many approaches in use are stepwise selection procedures, which can be computationally expensive and ignore stochastic errors in the variable selection process. In this article, penalized ..."
Abstract - Cited by 948 (62 self) - Add to MetaCart
functions are symmetric, nonconcave on (0, ∞), and have singularities at the origin to produce sparse solutions. Furthermore, the penalty functions should be bounded by a constant to reduce bias and satisfy certain conditions to yield continuous solutions. A new algorithm is proposed for optimizing

Decoding by Linear Programming

by Emmanuel J. Candès, Terence Tao , 2004
"... This paper considers the classical error correcting problem which is frequently discussed in coding theory. We wish to recover an input vector f ∈ Rn from corrupted measurements y = Af + e. Here, A is an m by n (coding) matrix and e is an arbitrary and unknown vector of errors. Is it possible to rec ..."
Abstract - Cited by 1399 (16 self) - Add to MetaCart
This paper considers the classical error correcting problem which is frequently discussed in coding theory. We wish to recover an input vector f ∈ Rn from corrupted measurements y = Af + e. Here, A is an m by n (coding) matrix and e is an arbitrary and unknown vector of errors. Is it possible
Results 1 - 10 of 17,248