Results 1 - 10 of 99,474

Optimal Sampling Rates in Infinite-Dimensional Compressed Sensing

by Mitra Fatemi, Loic Baboulaz, Martin Vetterli
"... Abstract—The theory of compressed sensing studies the prob-lem of recovering a high dimensional sparse vector from its projections onto lower dimensional subspaces. The recently introduced framework of infinite-dimensional compressed sensing [1], to some extent generalizes these results to infinite- ..."
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. In this paper, by considering Fourier and Haar wavelet bases, we experimentally show that M can be optimally tuned to minimize the number of samples m that guarantee perfect recovery. This study does not have any parallel in the finite-dimensional CS. I.

Empirical exchange rate models of the Seventies: do they fit out of sample?

by Richard A. Meese, Kenneth Rogoff - JOURNAL OF INTERNATIONAL ECONOMICS , 1983
"... This study compares the out-of-sample forecasting accuracy of various structural and time series exchange rate models. We find that a random walk model performs as well as any estimated model at one to twelve month horizons for the dollar/pound, dollar/mark, dollar/yen and trade-weighted dollar exch ..."
Abstract - Cited by 854 (12 self) - Add to MetaCart
This study compares the out-of-sample forecasting accuracy of various structural and time series exchange rate models. We find that a random walk model performs as well as any estimated model at one to twelve month horizons for the dollar/pound, dollar/mark, dollar/yen and trade-weighted dollar

Optimal sampling rate assignment with dynamic route selection for real-time wireless sensor networks

by Weihuan Shu, Xue Liu, Zonghua Gu, Sathish Gopalakrishnan - in RTSS ’08 , 2007
"... Abstract—The allocation of computation and communication resources in a manner that optimizes aggregate system performance is a crucial aspect of system management. Wireless sensor network poses new challenges due to the resource constraints and real-time requirements. Existing work has dealt with t ..."
Abstract - Cited by 11 (1 self) - Add to MetaCart
, we address the problem of optimizing sampling rates with dynamic route selection for wireless sensor networks. We model the problem as a constrained optimization problem and solve it under the Network Utility Maximization framework. Based on the primal-dual method and dual decomposition technique, we

Minimum Error Rate Training in Statistical Machine Translation

by Franz Josef Och , 2003
"... Often, the training procedure for statistical machine translation models is based on maximum likelihood or related criteria. A general problem of this approach is that there is only a loose relation to the final translation quality on unseen text. In this paper, we analyze various training cri ..."
Abstract - Cited by 757 (7 self) - Add to MetaCart
criteria which directly optimize translation quality.

CoSaMP: Iterative signal recovery from incomplete and inaccurate samples

by D. Needell, J. A. Tropp - California Institute of Technology, Pasadena , 2008
"... Abstract. Compressive sampling offers a new paradigm for acquiring signals that are compressible with respect to an orthonormal basis. The major algorithmic challenge in compressive sampling is to approximate a compressible signal from noisy samples. This paper describes a new iterative recovery alg ..."
Abstract - Cited by 770 (13 self) - Add to MetaCart
Abstract. Compressive sampling offers a new paradigm for acquiring signals that are compressible with respect to an orthonormal basis. The major algorithmic challenge in compressive sampling is to approximate a compressible signal from noisy samples. This paper describes a new iterative recovery

Optimization Flow Control, I: Basic Algorithm and Convergence

by Steven H. Low, David E. Lapsley - IEEE/ACM TRANSACTIONS ON NETWORKING , 1999
"... We propose an optimization approach to flow control where the objective is to maximize the aggregate source utility over their transmission rates. We view network links and sources as processors of a distributed computation system to solve the dual problem using gradient projection algorithm. In thi ..."
Abstract - Cited by 694 (64 self) - Add to MetaCart
We propose an optimization approach to flow control where the objective is to maximize the aggregate source utility over their transmission rates. We view network links and sources as processors of a distributed computation system to solve the dual problem using gradient projection algorithm

Genetic Algorithms for Multiobjective Optimization: Formulation, Discussion and Generalization

by Carlos M. Fonseca, Peter J. Fleming , 1993
"... The paper describes a rank-based fitness assignment method for Multiple Objective Genetic Algorithms (MOGAs). Conventional niche formation methods are extended to this class of multimodal problems and theory for setting the niche size is presented. The fitness assignment method is then modified to a ..."
Abstract - Cited by 633 (15 self) - Add to MetaCart
to allow direct intervention of an external decision maker (DM). Finally, the MOGA is generalised further: the genetic algorithm is seen as the optimizing element of a multiobjective optimization loop, which also comprises the DM. It is the interaction between the two that leads to the determination of a

Exact Matrix Completion via Convex Optimization

by Emmanuel J. Candès, Benjamin Recht , 2008
"... We consider a problem of considerable practical interest: the recovery of a data matrix from a sampling of its entries. Suppose that we observe m entries selected uniformly at random from a matrix M. Can we complete the matrix and recover the entries that we have not seen? We show that one can perfe ..."
Abstract - Cited by 873 (26 self) - Add to MetaCart
We consider a problem of considerable practical interest: the recovery of a data matrix from a sampling of its entries. Suppose that we observe m entries selected uniformly at random from a matrix M. Can we complete the matrix and recover the entries that we have not seen? We show that one can

Dynamic programming algorithm optimization for spoken word recognition

by Hiroaki Sakoe, Seibi Chiba - IEEE TRANSACTIONS ON ACOUSTICS, SPEECH, AND SIGNAL PROCESSING , 1978
"... This paper reports on an optimum dynamic programming (DP) based time-normalization algorithm for spoken word recognition. First, a general principle of time-normalization is given using timewarping function. Then, two time-normalized distance definitions, ded symmetric and asymmetric forms, are der ..."
Abstract - Cited by 788 (3 self) - Add to MetaCart
is restricted so as to improve discrimination between words in different categories. AND SEIBI CHIBA vestigations were made, based on the assumption that speech patterns are time-sampled with a common and uniform sampling period, as in most general cases. One of the problems discussed in this paper involves

Constrained model predictive control: Stability and optimality

by D. Q. Mayne, J. B. Rawlings, C. V. Rao, P. O. M. Scokaert - AUTOMATICA , 2000
"... Model predictive control is a form of control in which the current control action is obtained by solving, at each sampling instant, a finite horizon open-loop optimal control problem, using the current state of the plant as the initial state; the optimization yields an optimal control sequence and t ..."
Abstract - Cited by 738 (16 self) - Add to MetaCart
Model predictive control is a form of control in which the current control action is obtained by solving, at each sampling instant, a finite horizon open-loop optimal control problem, using the current state of the plant as the initial state; the optimization yields an optimal control sequence
Results 1 - 10 of 99,474