Small Probability

14,000,000 Leading Edge Experts on the ideXlab platform

Scan Science and Technology

Contact Leading Edge Experts & Companies

Scan Science and Technology

Contact Leading Edge Experts & Companies

The Experts below are selected from a list of 327 Experts worldwide ranked by ideXlab platform

Ke Xiong - One of the best experts on this subject based on the ideXlab platform.

  • importance of Small Probability events in big data information measures applications and challenges
    arXiv: Information Theory, 2019
    Co-Authors: Ke Xiong
    Abstract:

    In many applications (e.g., anomaly detection and security systems) of smart cities, rare events dominate the importance of the total information of big data collected by Internet of Things (IoTs). That is, it is pretty crucial to explore the valuable information associated with the rare events involved in minority subsets of the voluminous amounts of data. To do so, how to effectively measure the information with importance of the Small Probability events from the perspective of information theory is a fundamental question. This paper first makes a survey of some theories and models with respect to importance measures and investigates the relationship between subjective or semantic importance and rare events in big data. Moreover, some applications for message processing and data analysis are discussed in the viewpoint of information measures. In addition, based on rare events detection, some open challenges related to information measures, such as smart cities, autonomous driving, and anomaly detection in IoTs, are introduced which can be considered as future research directions.

  • Importance of Small Probability Events in Big Data: Information Measures, Applications, and Challenges
    IEEE Access, 2019
    Co-Authors: Ke Xiong
    Abstract:

    In many applications (e.g., anomaly detection and security systems) of smart cities, rare events dominate the importance of the total information on big data collected by the Internet of Things (IoT). That is, it is pretty crucial to explore the valuable information associated with the rare events involved in minority subsets of the voluminous amounts of data. To do so, how to effectively measure the information with the importance of the Small Probability events from the perspective of information theory is a fundamental question. This paper first makes a survey of some theories and models with respect to importance measures and investigates the relationship between subjective or semantic importance and rare events in big data. Moreover, some applications for message processing and data analysis are discussed in the viewpoint of information measures. In addition, based on rare events detection, some open challenges related to information measures, such as smart cities, autonomous driving, and anomaly detection in the IoT, are introduced which can be considered as future research directions.

A.j.e.m. Janssen - One of the best experts on this subject based on the ideXlab platform.

  • Capacity of weakly (d,k)-constrained sequences
    2000 IEEE International Symposium on Information Theory (Cat. No.00CH37060), 2000
    Co-Authors: K.a.s. Immink, A.j.e.m. Janssen
    Abstract:

    We find an analytic expression for the maximum of the normalized entropy -/spl Sigma//sub i/spl isin/T/p/sub i/ ln p/sub i///spl Sigma//sub i/spl isin/T/ip/sub i/ where the set T is the disjoint union of sets S/sub n/ of positive integers that are assigned probabilities P/sub n/, /spl Sigma//sub n/P/sub n/=1. This result is applied to the computation of the capacity of weakly (d,k)-constrained sequences that are allowed to violate the (d,k)-constraint with Small Probability.

  • An entropy theorem for computing the capacity of weakly (d,k)-constrained sequences
    IEEE Transactions on Information Theory, 2000
    Co-Authors: A.j.e.m. Janssen, K.a. Schouhamer Immink
    Abstract:

    We find an analytic expression for the maximum of the normalized entropy -/spl Sigma//sub i/spl epsiv/T/p/sub i/ln p/sub i///spl Sigma//sub i/spl epsiv/T/ip/sub i/ where the set T is the disjoint union of sets S/sub n/ of positive integers that are assigned probabilities P/sub n/, /spl Sigma//sub n/P/sub n/=1. This result is applied to the computation of the capacity of weakly (d,k)-constrained sequences that are allowed to violate the (d,k)-constraint with Small Probability.

Jerome R Busemeyer - One of the best experts on this subject based on the ideXlab platform.

  • the effect of foregone payoffs on underweighting Small Probability events
    Journal of Behavioral Decision Making, 2006
    Co-Authors: Eldad Yechiam, Jerome R Busemeyer
    Abstract:

    Foregone payoffs add information about the outcomes for alternatives that are not chosen. The present paper examines the effect of foregone payoffs on underweighting rare but possible events in repeated choice tasks. Previous studies have not demonstrated any long-lasting effects of foregone payoffs (following repeated presentation of a task) when foregone payoffs do not add much information. The present paper highlights the conditions and the contributing factors for the occurrence of such long-lasting effects. An experimental study compares the effect of foregone payoffs under different degrees of rarity of the negative payoff. It is demonstrated that foregone payoffs increase the selection from risky alternatives with extremely rare and highly negative outcomes, and that this effect does not diminish with repeated presentation of the task. These findings can be summarized using a surprisingly simple reinforcement-learning model. The findings are discussed in the context of the potential long-term effect of social learning. Copyright © 2006 John Wiley & Sons, Ltd.

K.a. Schouhamer Immink - One of the best experts on this subject based on the ideXlab platform.

  • An entropy theorem for computing the capacity of weakly (d,k)-constrained sequences
    IEEE Transactions on Information Theory, 2000
    Co-Authors: A.j.e.m. Janssen, K.a. Schouhamer Immink
    Abstract:

    We find an analytic expression for the maximum of the normalized entropy -/spl Sigma//sub i/spl epsiv/T/p/sub i/ln p/sub i///spl Sigma//sub i/spl epsiv/T/ip/sub i/ where the set T is the disjoint union of sets S/sub n/ of positive integers that are assigned probabilities P/sub n/, /spl Sigma//sub n/P/sub n/=1. This result is applied to the computation of the capacity of weakly (d,k)-constrained sequences that are allowed to violate the (d,k)-constraint with Small Probability.

Liron Schiff - One of the best experts on this subject based on the ideXlab platform.

Small Probability - 15 days free trial to Access Experts & Abstracts