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39,483
Smooth minimization of nonsmooth functions
 Math. Programming
, 2005
"... In this paper we propose a new approach for constructing efficient schemes for nonsmooth convex optimization. It is based on a special smoothing technique, which can be applied to the functions with explicit maxstructure. Our approach can be considered as an alternative to blackbox minimization. F ..."
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Cited by 523 (1 self)
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In this paper we propose a new approach for constructing efficient schemes for nonsmooth convex optimization. It is based on a special smoothing technique, which can be applied to the functions with explicit maxstructure. Our approach can be considered as an alternative to blackbox minimization
The Nature and Growth of Vertical Specialization in World Trade
 Journal of International Economics
"... Abstract: Dramatic changes are occurring in the nature of international trade. Production processes increasingly involve a sequential, vertical trading chain stretching across many countries, with each country specializing in particular stages of a good’s production sequence. We document a key aspe ..."
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Cited by 481 (20 self)
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grown as much as 40 % in the last twentyfive years. The key insight about why vertical specialization has grown so much lies with the fact that trade barriers (tariffs and transportation costs) are incurred repeatedly as goodsinprocess cross multiple borders. Hence, even small reductions in tariffs
Greedy Function Approximation: A Gradient Boosting Machine
 Annals of Statistics
, 2000
"... Function approximation is viewed from the perspective of numerical optimization in function space, rather than parameter space. A connection is made between stagewise additive expansions and steepest{descent minimization. A general gradient{descent \boosting" paradigm is developed for additi ..."
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Cited by 1000 (13 self)
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for additive expansions based on any tting criterion. Specic algorithms are presented for least{squares, least{absolute{deviation, and Huber{M loss functions for regression, and multi{class logistic likelihood for classication. Special enhancements are derived for the particular case where the individual
The ratedistortion function for source coding with side information at the decoder
 IEEE Trans. Inform. Theory
, 1976
"... AbstractLet {(X,, Y,J}r = 1 be a sequence of independent drawings of a pair of dependent random variables X, Y. Let us say that X takes values in the finite set 6. It is desired to encode the sequence {X,} in blocks of length n into a binary stream*of rate R, which can in turn be decoded as a seque ..."
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Cited by 1060 (1 self)
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sequence { 2k}, where zk E %, the reproduction alphabet. The average distorjion level is (l/n) cl = 1 E[D(X,,z&, where D(x, $ 2 0, x E I, 2 E J, is a preassigned distortion measure. The special assumption made here is that the decoder has access to the side information {Yk}. In this paper we determine
Interiorpoint Methods
, 2000
"... The modern era of interiorpoint methods dates to 1984, when Karmarkar proposed his algorithm for linear programming. In the years since then, algorithms and software for linear programming have become quite sophisticated, while extensions to more general classes of problems, such as convex quadrati ..."
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Cited by 612 (15 self)
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, monotone linear complementarity, and convex programming over sets that can be characterized by selfconcordant barrier functions.
Separation of ownership and control
 JOURNAL OF LAW AND ECONOMICS
, 1983
"... This paper analyzes the survival of organizations in which decision agents do not bear a major share of the wealth effects of their decisions. This is what the literature on large corporations calls separation of âownershipâ and âcontrol.â Such separation of decision and risk bearing functio ..."
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Cited by 1661 (8 self)
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functions is also common to organizations like large professional partnerships, financial mutuals and nonprofits. We contend that separation of decision and risk bearing functions survives in these organizations in part because of the benefits of specialization of management and risk bearing but also
Discriminative Training and Maximum Entropy Models for Statistical Machine Translation
, 2002
"... We present a framework for statistical machine translation of natural languages based on direct maximum entropy models, which contains the widely used source channel approach as a special case. All knowledge sources are treated as feature functions, which depend on the source language senten ..."
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Cited by 508 (30 self)
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We present a framework for statistical machine translation of natural languages based on direct maximum entropy models, which contains the widely used source channel approach as a special case. All knowledge sources are treated as feature functions, which depend on the source language
ATOMIC DECOMPOSITION BY BASIS PURSUIT
, 1995
"... The TimeFrequency and TimeScale communities have recently developed a large number of overcomplete waveform dictionaries  stationary wavelets, wavelet packets, cosine packets, chirplets, and warplets, to name a few. Decomposition into overcomplete systems is not unique, and several methods for d ..."
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Cited by 2728 (61 self)
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for decomposition have been proposed, including the Method of Frames (MOF), Matching Pursuit (MP), and, for special dictionaries, the Best Orthogonal Basis (BOB). Basis Pursuit (BP) is a principle for decomposing a signal into an "optimal" superposition of dictionary elements, where optimal means having
A View Of The Em Algorithm That Justifies Incremental, Sparse, And Other Variants
 Learning in Graphical Models
, 1998
"... . The EM algorithm performs maximum likelihood estimation for data in which some variables are unobserved. We present a function that resembles negative free energy and show that the M step maximizes this function with respect to the model parameters and the E step maximizes it with respect to the d ..."
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Cited by 993 (18 self)
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. The EM algorithm performs maximum likelihood estimation for data in which some variables are unobserved. We present a function that resembles negative free energy and show that the M step maximizes this function with respect to the model parameters and the E step maximizes it with respect
Consistent hashing and random trees: Distributed caching protocols for relieving hot spots on the World Wide Web
 IN PROC. 29TH ACM SYMPOSIUM ON THEORY OF COMPUTING (STOC
, 1997
"... We describe a family of caching protocols for distributed networks that can be used to decrease or eliminate the occurrence of hot spots in the network. Our protocols are particularly designed for use with very large networks such as the Internet, where delays caused by hot spots can be severe, and ..."
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Cited by 699 (10 self)
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of existing resources, and scale gracefully as the network grows. Our caching protocols are based on a special kind of hashing that we call consistent hashing. Roughly speaking, a consistent hash function is one which changes minimally as the range of the function changes. Through the development of good
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