Dynamic code generation is the creation of executable code at runtime. Such “on-the-fly ” code generation is a powerful technique, enabling applications to use runtime information to improve performance by up to an order of magnitude [4, 8, 20, 22, 23]. Unfortunately, previous general

stepsize schedule for good performance. For the case of linear value function approximations and λ = 0, the Least-Squares TD (LSTD) algorithm of Bradtke and Barto (1996, Machine learning, 22:1–3, 33–57) eliminates all stepsize parameters and improves data efficiency. This paper updates Bradtke and Barto’s

an overview of network analysis techniques and discusses their implementation in the VC context. A simple example illustrating network analysis is presented in the Appendix. Section II describes our data. In Section III, we analyze the effect of VC networking on fund performance. Section IV examines

In this study, alinear decomposition technique, independent component analysis (ICA), is applied to single-trial multichannel EEG data from event-related potential (ERP) experiments. Spatial filters derived by ICA blindly separate the input data into asum of temporally independent and spatially

changes in soil temperature. At the oak-hickory site in 1997, rates rose from a constant 1 g C m -2 d -1 to a steady 4 g C m -2 d -1 in the June-August period (slightly higher than the tropical rain forest), as the average daily soil temperature rose to approximately 22°C, before falling away again

accurately and more importantly prevent malicious use of transformed data by untrusted entities. Traditional encryption based techniques incur expensive O(n) computation cost (where n is the total number of points in space) and possibly logarithmic communication cost for resolving a KNN query

Discovery of functional dependencies from relations has been identified as an important database analysis technique. In this paper, we present a new approach for finding functional dependencies from large databases, based on partitioning the set of rows with respect to their attribute values

square estimation. Finally there are some results of a spatial analysis of R & D spillovers data (for 22 countries and 20 years) shown.

Abstract—We study compressive sensing in the spatial domain to achieve target localization, specifically direction of arrival (DOA), using multiple-input multiple-output (MIMO) radar. A sparse localization framework is proposed for a MIMO array in which transmit and receive elements are placed

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