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Stanford Webinar, Mar 9: When big data seems too small


 
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On March 9, Stanford’s Dr. Gregory Valiant discusses the difficulties of and solutions for making accurate inferences in this challenging regime, in which the empirical distribution of the available data is misleading.



 
 
 
 
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Free Stanford Webinar
When Your Big Data Seems Too Small: Accurate Inferences Beyond the Empirical Distribution
 
Many of the techniques and algorithms that are used in machine learning and data sciences assume that the empirical distribution of the available data is an accurate approximation of the primary phenomena being investigated. However, when dealing with complex or high dimensional distributions, even large datasets can fail to accurately represent its core. As examples, in large genomic datasets many rare genetic variants are unobserved, and in a large natural language corpus, many reasonable sequences of five words might not be observed.

In this webinar, Stanford’s Dr. Gregory Valiant discusses the difficulties of and solutions for making accurate inferences in this challenging regime, in which the empirical distribution of the available data is misleading. Learn how to extract accurate information about the underlying distribution, including information about the portion that has not been observed in the given dataset.

You will learn:
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An intuitive approach for reasoning about the distribution that underlies a given dataset

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Techniques that leverage this intuition, and reveal the structure of the underlying distribution---including the structure of the unseen portion of it from which no datapoints have been observed

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Practical implications of these techniques for the analysis of genomic datasets, including how to estimate the value of sequencing additional human genomes


Presented by the Databases and the Foundations in Computer Science graduate certificate programs.
Questions? Contact 650-204-3984 or scpd-customerservice@stanford.edu.
 
Date:  March 09, 2017
Day: Thursday
Time:  10am PT, 1pm ET
 
 
Venue:
Online via Webex
 
 
events  Upcoming Events
February 12- March 24, 2017
 
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