The Experts below are selected from a list of 9 Experts worldwide ranked by ideXlab platform
J Kwisthout - One of the best experts on this subject based on the ideXlab platform.
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most frugal explanations Occams Razor applied to bayesian abduction
BNAIC 2013: Proceedings of the 25th Benelux Conference on Artificial Intelligence Delft The Netherlands November 7-8 2013, 2013Co-Authors: J KwisthoutAbstract:What constitutes Best in Inference to the Best Explanation has been hotly debated. In Bayesian models the traditional interpretation is Best = Most Probable. We propose an alternative notion, denoted as Most Frugal Explanation (MFE), that utilizes the fact that only few variables actually are relevant for deciding upon the best explanation. We show that MFE is intractable in general, but can be tractably approximated under plausible situational constraints.
Flaten James - One of the best experts on this subject based on the ideXlab platform.
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Rotation Mitigation and Occams + Tungsten Flight Termination for Eclipse Balloon Missions
DePaul University, 2017Co-Authors: Peterson Simon, Ailts Garrett, Nelson Joshua, Toth Daniel, Flaten JamesAbstract:Stack rotation is a nemesis for many ballooning experiments, especially photography when trying to keep a specific target in view such as the Moon’s shadow (or the Sun itself) on eclipse flights. Ascending weather balloons tend to slow or even stop rotating once in the stratosphere and out of most cross winds. However payload stacks can continue to rotate with respect to the balloon right up to burst, especially if attached to the balloon neck by just a single main line. Our passive “rotation mitigation” device attaches directly to the neck of the balloon and runs four parallel lines separated by 6 inches from the balloon neck down to the payload stack, significantly diminishing stack rotation with respect to the balloon, especially at high altitudes. This arrangement complicates the placement of the parachute, but we have successfully deployed parachutes from a hook on the side of the upper-most payload box. This also complicates the placement of a flight-termination line-cutter, be that Montana’s “Occams” Razor cutter or something like a Tungsten hot-wire cutter. We have developed a compact payload box to enclose both an Occams Razor cutter and a Tungsten hot-wire cutter, both of which can independently release the multiple lines of our rotation mitigation device. We can fire the Occams by XBee commands relayed through our RFD 900 payload, as an alternative to the Iridium text-message system. The Tungsten cutter can be fired by XBee command, by timer, or by autonomous GPS-sensor-based decision making
Sehring Hans-werner - One of the best experts on this subject based on the ideXlab platform.
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Occams Razor for Big Data? On Detecting Quality in Large Unstructured Datasets
'MDPI AG', 2020Co-Authors: Dresp-langley Birgitta, Ekseth, Ole Kristian, Fesl Jan, Gohshi Seiichi, Kurz Marc, Sehring Hans-wernerAbstract:Detecting quality in large unstructured datasets requires capacities far beyond the limits of human perception and communicability and, as a result, there is an emerging trend towards increasingly complex analytic solutions in data science to cope with this problem. This new trend towards analytic complexity represents a severe challenge for the principle of parsimony or Occams Razor in science. This review article combines insight from various domains such as physics, computational science, data engineering, and cognitive science to review the specific properties of big data. Problems for detecting data quality without losing the principle of parsimony are then highlighted on the basis of specific examples. Computational building block approaches for data clustering can help to deal with large unstructured datasets in minimized computation time, and meaning can be extracted rapidly from large sets of unstructured image or video data parsimoniously through relatively simple unsupervised machine learning algorithms. Why we still massively lack in expertise for exploiting big data wisely to extract relevant information for specific tasks, recognize patterns, generate new information, or store and further process large amounts of sensor data is then reviewed; examples illustrating why we need subjective views and pragmatic methods to analyze big data contents are brought forward. The review concludes on how cultural differences between East and West are likely to affect the course of big data analytics, and the development of increasingly autonomous artificial intelligence aimed at coping with the big data deluge in the near future
Peterson Simon - One of the best experts on this subject based on the ideXlab platform.
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Rotation Mitigation and Occams + Tungsten Flight Termination for Eclipse Balloon Missions
DePaul University, 2017Co-Authors: Peterson Simon, Ailts Garrett, Nelson Joshua, Toth Daniel, Flaten JamesAbstract:Stack rotation is a nemesis for many ballooning experiments, especially photography when trying to keep a specific target in view such as the Moon’s shadow (or the Sun itself) on eclipse flights. Ascending weather balloons tend to slow or even stop rotating once in the stratosphere and out of most cross winds. However payload stacks can continue to rotate with respect to the balloon right up to burst, especially if attached to the balloon neck by just a single main line. Our passive “rotation mitigation” device attaches directly to the neck of the balloon and runs four parallel lines separated by 6 inches from the balloon neck down to the payload stack, significantly diminishing stack rotation with respect to the balloon, especially at high altitudes. This arrangement complicates the placement of the parachute, but we have successfully deployed parachutes from a hook on the side of the upper-most payload box. This also complicates the placement of a flight-termination line-cutter, be that Montana’s “Occams” Razor cutter or something like a Tungsten hot-wire cutter. We have developed a compact payload box to enclose both an Occams Razor cutter and a Tungsten hot-wire cutter, both of which can independently release the multiple lines of our rotation mitigation device. We can fire the Occams by XBee commands relayed through our RFD 900 payload, as an alternative to the Iridium text-message system. The Tungsten cutter can be fired by XBee command, by timer, or by autonomous GPS-sensor-based decision making
Dresp-langley Birgitta - One of the best experts on this subject based on the ideXlab platform.
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Occams Razor for Big Data? On Detecting Quality in Large Unstructured Datasets
'MDPI AG', 2020Co-Authors: Dresp-langley Birgitta, Ekseth, Ole Kristian, Fesl Jan, Gohshi Seiichi, Kurz Marc, Sehring Hans-wernerAbstract:Detecting quality in large unstructured datasets requires capacities far beyond the limits of human perception and communicability and, as a result, there is an emerging trend towards increasingly complex analytic solutions in data science to cope with this problem. This new trend towards analytic complexity represents a severe challenge for the principle of parsimony or Occams Razor in science. This review article combines insight from various domains such as physics, computational science, data engineering, and cognitive science to review the specific properties of big data. Problems for detecting data quality without losing the principle of parsimony are then highlighted on the basis of specific examples. Computational building block approaches for data clustering can help to deal with large unstructured datasets in minimized computation time, and meaning can be extracted rapidly from large sets of unstructured image or video data parsimoniously through relatively simple unsupervised machine learning algorithms. Why we still massively lack in expertise for exploiting big data wisely to extract relevant information for specific tasks, recognize patterns, generate new information, or store and further process large amounts of sensor data is then reviewed; examples illustrating why we need subjective views and pragmatic methods to analyze big data contents are brought forward. The review concludes on how cultural differences between East and West are likely to affect the course of big data analytics, and the development of increasingly autonomous artificial intelligence aimed at coping with the big data deluge in the near future
