In this technique, the graph appears as a set of dots. Alternatively, each time period can be viewed as a detached point in time, usually at an integer value on the horizontal axis, and the measured variable is plotted as a height above that time-axis point. Extensive experiments performed on four large datasets with up to one million samples show that our discrete optimization based graph hashing method obtains superior search accuracy over state-of-the-art unsupervised hashing methods, especially for longer codes. Discrete Mathematics provides a common forum for significant research in many areas of discrete mathematics and combinatorics. In this graphical technique, the graph appears as a sequence of horizontal steps. We show that a graph admits a topology on its node set which is. A tractable alternating maximization algorithm is then proposed to explicitly deal with the discrete constraints, yielding high-quality codes to well capture the local neighborhoods. PrCa, P., Graphs and topologies on discrete sets, Discrete Mathematics. beside a continuous graph is a graph where both variables are continuous, it means that their fields are de Real number, so the. We cast the graph hashing problem into a discrete optimization framework which directly learns the binary codes. A continuous function allows the x-values to be ANY points in the interval, including fractions, decimals, and irrational values. A graph is discrete when one (or both) of the variables has discrete entries, its means that are entered number, without decimal part, so the graph has no continuity, the trace will be broken parts, not a single one. This paper presents a graph-based unsupervised hashing model to preserve the neighborhood structure of massive data in a discrete code space. We argue that the degraded performance is due to inferior optimization procedures used to achieve discrete binary codes. However, the performance of most unsupervised learning based hashing methods deteriorates rapidly as the hash code length increases. In particular, learning based hashing has received considerable attention due to its appealing storage and search efficiency. For an example, the function f (x)1/x cannot take on x values of x0 because that would make the function undefined (1/0 undefined). The domain of a function is what input values it can take on. Hashing has emerged as a popular technique for fast nearest neighbor search in gigantic databases. The definition of a function is as follows: A function takes any input within its domain, and maps this to 1 output. Wei Liu, Cun Mu, Sanjiv Kumar, Shih-Fu Chang Abstract Discrete mathematics is the study of mathematical structures that are countable or otherwise distinct and separable. Bibtex Metadata Paper Reviews Supplemental
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