Sliding Window Quantile

Approximate Counts And Quantiles Over Sliding Windows
Approximate Counts and Quantiles over Sliding Windows Arvind Arasu Stanford University xed-size sliding window over this stream with size N = maintaining quantile summaries of the most recent N ... Read Full Source

Continuously Maintaining quantile Summaries Of The Most ...
• For the sliding window model where quantile sum-maries are maintained for the N most recently seen el-ements in a data stream, we developed a one-pass de-terministic -approximate algorithm to maintain quan-tiles summaries. The algorithm requires a space of ... Fetch Full Source

Resource Sharing In Continuous Sliding-Window Aggregates
Resource Sharing in Continuous Sliding-Window Aggregates Arvind Arasu Jennifer Widom Stanford University farvinda,widomg@cs.stanford.edu The quantile aggregation function is specified using a pa-rameter ˚ 2 (0;1] and is denoted QUANTILE(˚). ... Get Doc

No Pane, No Gain: Efficient Evaluation Of Sliding-Window ...
No Pane, No Gain: Efficient Evaluation of Sliding-Window Aggregates over Data Streams Jin ~i', David ~aier', Kristin Tuftel, Vassilis papadimosl, Peter A. Tucke? ... Access Doc

Continuously Maintaining Quantile Summaries Of The Most ...
2.4 Challenges Note that in the sliding window model, the actual con-tents of the most recent N tuples changeuponnew elements arrive, though N is fixed. ... Read Full Source

Optimal Window Change Detection - IEEE Computer Society
Optimal Window Change Detection Jan Peter Patist Vrije Universiteit Amsterdam A sliding window of size nis a buffer of the maximum quantile differences. Then these difference can be rewritten as cumulative sums. ... Fetch Content

IEEE TRANSACTIONS ON KNOWLEDGE AND DATA ENGINEERING, VOL. 18 ...
Abstract—Quantile computation has many applications including data mining and financial data analysis. obtained within the rank error precision N over all N data items in a data stream or in a sliding window. However, scalable online ... Visit Document

Fast And Accurate Computation Of Equi-Depth Histograms Over ...
Sliding window. To report the final quantile at each time, AM com-bines the sketch of the unexpired largest blocks covering the entire equi-depth histogram for sliding windows over a data stream. We have performed extensive experimental evaluations to compare the ... Access Document

Algorithmica - Springer
Approximate quantile computation is another well-studied problem in data streams. For this problem, a classical result of Munro and Paterson Under the sliding window model, it is not obvious how to increment an exponential histogram by w i. We can, ... Retrieve Document

Space Efficient Quantile Summary For Constrained Sliding ...
Space Efficient Quantile Summary for Constrained Sliding Windows on a Data Stream Jian Xu Xuemin Lin Xiaofang Zhou Computer Science & Engineering School of ITEE ... Read Here

Outline
Sliding window technique Sliding window: the most recent N elements in data streams. COMP9314 Xuemin Lin @DBG.unsw 15 Problem: Input:data stream D & a sliding window (N) Easy to extend to time window and landmark windows Quantile summary for n-of-N model ... Retrieve Document

Fast Computation Of Approximate Biased Histograms On Sliding ...
Approximate biased quantile were thus defined in [3] and [19] as follows: DEFINITION 2. An approximate Low-Biased Quantile with bias factor φ < 1of a given sequence of data items, say S, is the set of W is the sliding window size and ... Fetch Document

Standard Deviation - Wikipedia, The Free Encyclopedia
In statistics, the standard deviation (SD, also represented by the Greek letter sigma, σ for the population standard deviation or s for the sample standard deviation) is a measure that is used to quantify the amount of variation or dispersion of a set of data values. A standard deviation close ... Read Article

Adaptive Spatial Partitioning For Multidimensional Data Streams1
Adaptive Spatial Partitioning for Multidimensional Data Streams1 John Hershberger2 dimensional generalization of the ε-approximate quantile [0,R]d, where d is assumed to be a constant. The scheme extends to the sliding window model with a log(εn) factor increase in space, where n ... Read Document

Online Computation And Continuous Maintaining Of Quantile ...
Example of n-of-N model Assume the sliding window is 16 in an n-of-N model. A quantile query can be answered for any 1 n talk Quantile Estimation Overview GK-quantile Summary Algorithm Data Structure Operations Space Complexity Analysis Sliding Window Model Contributions of GK ... Document Retrieval

Quantiles On Streams - UCSB Computer Science
The Greenwald-Khanna (GK) algorithm is based on the idea that if a sorted subset fv1;v2; g of the input Lin et al. presented such a sliding window scheme for quantile summaries, however, the space requirement for their algorithm is O(1 2 + 1 log 2N). ... Retrieve Document

No Pane, No Gain: Efficient Evaluation Of Sliding-Window ...
No Pane, No Gain: Efficient Evaluation of Sliding-Window Aggregates over Data Streams Jin Li1, David Maier1, For example, median, quantile, and mode are holistic. We call aggregates that are not holistic bounded aggre-gates. The term bounded encompasses the distributive and ... Visit Document

QUANTILE BASED HISTOGRAM EQUALIZATION FOR ONLINE APPLICATIONS ...
QUANTILE BASED HISTOGRAM EQUALIZATION FOR ONLINE APPLICATIONS Florian Hilger, Sirko Molau, implemented using a sliding window instead of the whole utterance. When simply applying the two techniques suc-cessively their individual delays would add up. ... Fetch Doc

LNCS 7074 - Edit Distance To Monotonicity In Sliding Windows
A sliding window covering the w most recent items in the stream for any w basic counting and quantile estimation over sliding windows. Our algorithm also incorporates an idea in [8] to remove randomization. We also consider two extensions of the problem. ... Document Retrieval

Approximate Counts And Quantiles Over Sliding Windows
Approximate Counts and Quantiles over Sliding Windows Arvind Arasu Stanford University arvinda@cs.stanford.edu Gurmeet Singh Manku Stanford University ... Access Doc

Resource Sharing In Continuous Sliding-Window Aggregates
Resource Sharing in Continuous Sliding-Window Aggregates Arvind Arasu Stanford University arvinda@cs.stanford.edu Jennifer Widom Stanford University ... Fetch Document