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2,571
Optimal Design of Hierarchical Wavelet Networks for Timeseries Forecasting
"... Abstract. The purpose of this study is to identify the Hierarchical Wavelet Neural Networks (HWNN) and select important input features for each subwavelet neural network automatically. Based on the predefined instruction/operator sets, a HWNN is created and evolved using treestructure based Extend ..."
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Cited by 1 (0 self)
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Extended Compact Genetic Programming (ECGP), and the parameters are optimized by Differential Evolution (DE) algorithm. This framework also allows input variables selection. Empirical results on benchmark timeseries approximation problems indicate that theproposedmethodiseffectiveandefficient. 1
Benchmarking Least Squares Support Vector Machine Classifiers
 NEURAL PROCESSING LETTERS
, 2001
"... In Support Vector Machines (SVMs), the solution of the classification problem is characterized by a (convex) quadratic programming (QP) problem. In a modified version of SVMs, called Least Squares SVM classifiers (LSSVMs), a least squares cost function is proposed so as to obtain a linear set of eq ..."
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Cited by 476 (46 self)
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stage by gradually pruning the support value spectrum and optimizing the hyperparameters during the sparse approximation procedure. In this paper, twenty public domain benchmark datasets are used to evaluate the test set performance of LSSVM classifiers with linear, polynomial and radial basis function
The DaCapo Benchmarks: Java Benchmarking Development and Analysis
"... Since benchmarks drive computer science research and industry product development, which ones we use and how we evaluate them are key questions for the community. Despite complex runtime tradeoffs due to dynamic compilation and garbage collection required for Java programs, many evaluations still us ..."
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Cited by 397 (65 self)
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not require (3). We use and introduce new value, timeseries, and statistical metrics for static and dynamic properties such as code complexity, code size, heap composition, and pointer mutations. No benchmark suite is definitive, but these metrics show that DaCapo improves over SPEC Java in a variety of ways
How much should we trust differencesindifferences estimates?
, 2003
"... Most papers that employ DifferencesinDifferences estimation (DD) use many years of data and focus on serially correlated outcomes but ignore that the resulting standard errors are inconsistent. To illustrate the severity of this issue, we randomly generate placebo laws in statelevel data on femal ..."
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Cited by 828 (1 self)
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at the 5 percent level for up to 45 percent of the placebo interventions. We use Monte Carlo simulations to investigate how well existing methods help solve this problem. Econometric corrections that place a specific parametric form on the timeseries process do not perform well. Bootstrap (taking
Similarity search in high dimensions via hashing
, 1999
"... The nearest or nearneighbor query problems arise in a large variety of database applications, usually in the context of similarity searching. Of late, there has been increasing interest in building search/index structures for performing similarity search over highdimensional data, e.g., image dat ..."
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Cited by 641 (10 self)
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databases, document collections, timeseries databases, and genome databases. Unfortunately, all known techniques for solving this problem fall prey to the \curse of dimensionality. " That is, the data structures scale poorly with data dimensionality; in fact, if the number of dimensions exceeds 10
Localityconstrained linear coding for image classification
 IN: IEEE CONFERENCE ON COMPUTER VISION AND PATTERN CLASSIFICATOIN
, 2010
"... The traditional SPM approach based on bagoffeatures (BoF) requires nonlinear classifiers to achieve good image classification performance. This paper presents a simple but effective coding scheme called Localityconstrained Linear Coding (LLC) in place of the VQ coding in traditional SPM. LLC util ..."
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Cited by 443 (20 self)
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, achieving stateoftheart performance on several benchmarks. Compared with the sparse coding strategy [22], the objective function used by LLC has an analytical solution. In addition, the paper proposes a fast approximated LLC method by first performing a Knearestneighbor search and then solving a
The Determinants of Credit Spread Changes.
 Journal of Finance
, 2001
"... ABSTRACT Using dealer's quotes and transactions prices on straight industrial bonds, we investigate the determinants of credit spread changes. Variables that should in theory determine credit spread changes have rather limited explanatory power. Further, the residuals from this regression are ..."
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Cited by 422 (2 self)
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linear interpolation scheme to estimate the entire yield curve. Credit spreads are then defined as the difference between the yield of bondi and the associated yield of the Treasury curve at the same maturity. Treasury Rate Level We use Datastream's monthly series of 10year Benchmark Treasury
Locally Adaptive Dimensionality Reduction for Indexing Large Time Series Databases
 In proceedings of ACM SIGMOD Conference on Management of Data
, 2002
"... Similarity search in large time series databases has attracted much research interest recently. It is a difficult problem because of the typically high dimensionality of the data.. The most promising solutions' involve performing dimensionality reduction on the data, then indexing the reduced d ..."
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Cited by 316 (33 self)
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Similarity search in large time series databases has attracted much research interest recently. It is a difficult problem because of the typically high dimensionality of the data.. The most promising solutions' involve performing dimensionality reduction on the data, then indexing the reduced
Prices and unit labor costs: A new test of price stickiness
, 1999
"... This paper investigates the predictions of a simple optimizing model of nominal price rigidity for the aggregate price level and the dynamics of inflation. I compare the model’s predictions with those of a perfectly competitive, flexible price ‘benchmark’ model (corresponding to the model of pricing ..."
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Cited by 356 (11 self)
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with the data. I find that, while the evolution of prices relative to unit labor costs is quite different from what would be predicted by the flexibleprice ‘benchmark ’ model, a simple model of nominal price rigidity delivers an extremely close approximation both of the price/unit labor cost ratio
PROBEN1  a set of neural network benchmark problems and benchmarking rules
, 1994
"... Proben1 is a collection of problems for neural network learning in the realm of pattern classification and function approximation plus a set of rules and conventions for carrying out benchmark tests with these or similar problems. Proben1 contains 15 data sets from 12 different domains. All datasets ..."
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Cited by 234 (0 self)
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Proben1 is a collection of problems for neural network learning in the realm of pattern classification and function approximation plus a set of rules and conventions for carrying out benchmark tests with these or similar problems. Proben1 contains 15 data sets from 12 different domains. All
Results 1  10
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