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Arthur Zimek
Arthur Zimek is a professor in data mining, data science and machine learning at the University of Southern Denmark in Odense, Denmark. He graduated from the Ludwig Maximilian University of Munich in Munich, Germany, where he worked with Prof. Hans-Peter Kriegel. His dissertation on "Correlation Clustering" was awarded the "SIGKDD Doctoral Dissertation Award 2009 Runner-up" by the Association for Computing Machinery. He is well known for his work on Anomaly detection, outlier detection, density-based Cluster analysis, clustering, correlation clustering, and the curse of dimensionality. He is one of the founders and core developers of the open-source ELKI data mining framework. References External links University homepagePublicationsin the Digital Bibliography & Library Project Google Scholar profile Data miners Machine learning researchers German computer scientists Living people Ludwig Maximilian University of Munich alumni Academic staff of the University of Southe ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Anomaly Detection
In data analysis, anomaly detection (also referred to as outlier detection and sometimes as novelty detection) is generally understood to be the identification of rare items, events or observations which deviate significantly from the majority of the data and do not conform to a well defined notion of normal behaviour. Such examples may arouse suspicions of being generated by a different mechanism, or appear inconsistent with the remainder of that set of data. Anomaly detection finds application in many domains including cyber security, medicine, machine vision, statistics, neuroscience, law enforcement and financial fraud to name only a few. Anomalies were initially searched for clear rejection or omission from the data to aid statistical analysis, for example to compute the mean or standard deviation. They were also removed to better predictions from models such as linear regression, and more recently their removal aids the performance of machine learning algorithms. However, ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
SIGKDD
SIGKDD, representing the Association for Computing Machinery's (ACM) Special Interest Group (SIG) on Knowledge Discovery and Data Mining, hosts an influential annual conference. Conference history The KDD Conference grew from KDD (Knowledge Discovery and Data Mining) workshops at AAAI conferences, which were started by Gregory I. Piatetsky-Shapiro in 1989, 1991, and 1993, and Usama Fayyad in 1994. Conference papers of each Proceedings of the SIGKDD International Conference on Knowledge Discovery and Data Mining are published through ACM. KDD is widely considered the most influential forum for knowledge discovery and data mining research. The KDD conference has been held each year since 1995, and SIGKDD became an official ACM Special Interest Group in 1998. Past conference locations are listed on the KDD conference web site. The annual ACM SIGKDD conference is recognized as a flagship venue in the field. Based on statistics provided by independent researcher Lexing Xie in ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Ludwig Maximilian University Of Munich Alumni
Ludwig may refer to: People and fictional characters * Ludwig (given name), including a list of people and fictional characters * Ludwig (surname), including a list of people * Ludwig Ahgren, or simply Ludwig, American YouTube live streamer and content creator Arts and entertainment * ''Ludwig'' (cartoon), a 1977 animated children's series * ''Ludwig'' (film), a 1973 film by Luchino Visconti about Ludwig II of Bavaria * '' Ludwig: Requiem for a Virgin King'', a 1972 film by Hans-Jürgen Syberberg about Ludwig II of Bavaria * "Ludwig", a 1967 song by Al Hirt Other uses * Ludwig (crater), a small lunar impact crater just beyond the eastern limb of the Moon * Ludwig, Missouri, an unincorporated community in the United States * Ludwig Canal, an abandoned canal in southern Germany * Ludwig Drums, an American manufacturer of musical instruments * ''Ludwig'' (ship), a steamer that sank in 1861 after a collision with the '' Stadt Zürich'' See also * Ludewig * Ludvig * Ludwik ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Living People
Related categories * :Year of birth missing (living people) / :Year of birth unknown * :Date of birth missing (living people) / :Date of birth unknown * :Place of birth missing (living people) / :Place of birth unknown * :Year of death missing / :Year of death unknown * :Date of death missing / :Date of death unknown * :Place of death missing / :Place of death unknown * :Missing middle or first names See also * :Dead people * :Template:L, which generates this category or death years, and birth year and sort keys. : {{DEFAULTSORT:Living people 21st-century people People by status ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
German Computer Scientists
German(s) may refer to: * Germany (of or related to) **Germania (historical use) * Germans, citizens of Germany, people of German ancestry, or native speakers of the German language ** For citizens of Germany, see also German nationality law **Germanic peoples (Roman times) * German language **any of the Germanic languages * German cuisine, traditional foods of Germany People * German (given name) * German (surname) * Germán, a Spanish name Places * German (parish), Isle of Man * German, Albania, or Gërmej * German, Bulgaria * German, Iran * German, North Macedonia * German, New York, U.S. * Agios Germanos, Greece Other uses * German (mythology), a South Slavic mythological being * Germans (band), a Canadian rock band * "German" (song), a 2019 song by No Money Enterprise * ''The German'', a 2008 short film * "The Germans", an episode of ''Fawlty Towers'' * ''The German'', a nickname for Congolese rebel André Kisase Ngandu See also * Germanic (other) * Germa ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Machine Learning Researchers
A machine is a physical system using power to apply forces and control movement to perform an action. The term is commonly applied to artificial devices, such as those employing engines or motors, but also to natural biological macromolecules, such as molecular machines. Machines can be driven by animals and people, by natural forces such as wind and water, and by chemical, thermal, or electrical power, and include a system of mechanisms that shape the actuator input to achieve a specific application of output forces and movement. They can also include computers and sensors that monitor performance and plan movement, often called mechanical systems. Renaissance natural philosophers identified six simple machines which were the elementary devices that put a load into motion, and calculated the ratio of output force to input force, known today as mechanical advantage. Modern machines are complex systems that consist of structural elements, mechanisms and control components ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Digital Bibliography & Library Project
DBLP is a computer science bibliography website. Starting in 1993 at Universität Trier in Germany, it grew from a small collection of HTML files and became an organization hosting a database and logic programming bibliography site. Since November 2018, DBLP is a branch of Schloss Dagstuhl – Leibniz-Zentrum für Informatik (LZI). DBLP listed more than 5.4 million journal articles, conference papers, and other publications on computer science in December 2020, up from about 14,000 in 1995 and 3.66 million in July 2016. All important journals on computer science are tracked. Proceedings papers of many conferences are also tracked. It is mirrored at three sites across the Internet. For his work on maintaining DBLP, Michael Ley received an award from the Association for Computing Machinery (ACM) and the VLDB Endowment Special Recognition Award in 1997. Furthermore, he was awarded the ACM Distinguished Service Award for "creating, developing, and curating DBLP" in 2019. ''DBLP'' ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
ELKI
ELKI (for ''Environment for DeveLoping KDD-Applications Supported by Index-Structures'') is a data mining (KDD, knowledge discovery in databases) software framework developed for use in research and teaching. It was originally at the database systems research unit of Professor Hans-Peter Kriegel at the Ludwig Maximilian University of Munich, Germany, and now continued at the Technical University of Dortmund, Germany. It aims at allowing the development and evaluation of advanced data mining algorithms and their interaction with database index structures. Description The ELKI framework is written in Java and built around a modular architecture. Most currently included algorithms belong to clustering, outlier detection and database indexes. The object-oriented architecture allows the combination of arbitrary algorithms, data types, distance functions, indexes, and evaluation measures. The Java just-in-time compiler optimizes all combinations to a similar extent, making benc ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Curse Of Dimensionality
The curse of dimensionality refers to various phenomena that arise when analyzing and organizing data in high-dimensional spaces that do not occur in low-dimensional settings such as the three-dimensional physical space of everyday experience. The expression was coined by Richard E. Bellman when considering problems in dynamic programming. Dimensionally cursed phenomena occur in domains such as numerical analysis, sampling, combinatorics, machine learning, data mining and databases. The common theme of these problems is that when the dimensionality increases, the volume of the space increases so fast that the available data become sparse. In order to obtain a reliable result, the amount of data needed often grows exponentially with the dimensionality. Also, organizing and searching data often relies on detecting areas where objects form groups with similar properties; in high dimensional data, however, all objects appear to be sparse and dissimilar in many ways, which prevents co ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Cluster Analysis
Cluster analysis or clustering is the task of grouping a set of objects in such a way that objects in the same group (called a cluster) are more similar (in some sense) to each other than to those in other groups (clusters). It is a main task of exploratory data analysis, and a common technique for statistics, statistical data analysis, used in many fields, including pattern recognition, image analysis, information retrieval, bioinformatics, data compression, computer graphics and machine learning. Cluster analysis itself is not one specific algorithm, but the general task to be solved. It can be achieved by various algorithms that differ significantly in their understanding of what constitutes a cluster and how to efficiently find them. Popular notions of clusters include groups with small Distance function, distances between cluster members, dense areas of the data space, intervals or particular statistical distributions. Clustering can therefore be formulated as a multi-object ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Anomaly Detection
In data analysis, anomaly detection (also referred to as outlier detection and sometimes as novelty detection) is generally understood to be the identification of rare items, events or observations which deviate significantly from the majority of the data and do not conform to a well defined notion of normal behaviour. Such examples may arouse suspicions of being generated by a different mechanism, or appear inconsistent with the remainder of that set of data. Anomaly detection finds application in many domains including cyber security, medicine, machine vision, statistics, neuroscience, law enforcement and financial fraud to name only a few. Anomalies were initially searched for clear rejection or omission from the data to aid statistical analysis, for example to compute the mean or standard deviation. They were also removed to better predictions from models such as linear regression, and more recently their removal aids the performance of machine learning algorithms. However, ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
