PPT-An unbiased adaptive sampling algorithm for the exploration

Jérôme Waldispühl PhD School of Computer Science McGill Centre for Bioinformatics McGill University Canada Yann Ponty PhD Laboratoire dinformatique LIX École Polytechnique. Ideally if the channel is ideal without and channel distortion and additive noise we can demodulate the signal perfectly at the output without causin g any error However in practice all the channels are non ideal and noisy in nature So to recover t Anup. Bhattacharya. IIT Delhi. . Joint work with Davis . Issac. (MPI), . Ragesh. . Jaiswal. (IITD) and Amit Kumar (IITD). Introduction: Sampling. Select a subset of data. Computations on “representative” subset would approximate computations on whole data. Ch. 20 Efficiency and Mean Squared Error. CIS 2033: Computational Probability and Statistics. Prof. Longin Jan Latecki.  . Prepared in part by: Nouf Albarakati. An Estimate. An estimate is a value that only depends on the dataset x. Michael Cohen, Yin Tat Lee, Cameron Musco, Christopher Musco, . Richard . Peng. , Aaron Sidford . M.I.T.. Outline. Reducing Row Count. Row . S. ampling and Leverage Scores. Adaptive Uniform Sampling. Moritz Hardt. IBM Research Almaden. Joint work with Cynthia Dwork, Vitaly Feldman, . Toni Pitassi, Omer Reingold, Aaron Roth. Statistical Estimation. Data domain . X. , class labels . Y. Unknown distribution . t-shirts of each size to order?. In this lesson you will learn how to identify representative samples. . by differentiating between biased and unbiased methods of sampling.. The population is the entire group. How do you predict the winner of an election before the election takes place?. In this lesson you will learn how to collect data about a . population. by identifying a sample of the population.. How many texts do middle school students send in one day?. in Adaptive Data Analysis. Vitaly. Feldman. Overview. Adaptive data analysis. Motivation. Definitions. Basic techniques. With . Dwork. , . Hardt. , . Pitassi. , . Reingold. , Roth . [DFHPRR 14,15]. New results . To get valid results, survey samples must be chosen very carefully. An unbiased sample is selected so that it accurately represents the entire population. Two ways to pick an unbiased sample are on the . A new sampling method. Motivating example. Want to study the average amount of water used per person per month. How would you design a survey?. 2. A new sampling method. Consider the two strategies. Sample person by person. Applied Statistics and Probability for Engineers. Sixth Edition. Douglas C. Montgomery George C. . Runger. Chapter 7 Title and Outline. 2. 7. Point Estimation of Parameters and Sampling Distributions. Filters. . Chapter-7 : Wiener Filters and the LMS Algorithm. Marc Moonen . Dept. E.E./ESAT-STADIUS, KU Leuven. marc.moonen@esat.kuleuven.be. www.esat.kuleuven.be. /. stadius. /. Part-III : Optimal & Adaptive Filters. Marc Moonen . Dept. E.E./ESAT-STADIUS, KU Leuven. marc.moonen@esat.kuleuven.be. www.esat.kuleuven.be. /. stadius. /. Part-III : Optimal & Adaptive Filters. . Wieners Filters & the LMS Algorithm. . Brett Shapiro. 25 . February . 2011. 1. G1100161. Control Loops Keep LIGO Running. Evolving seismic noise from:. weather. people. … adaptive control also makes a very good thesis topic…. 2. How are Adaptive Loops Useful?.