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Arun Ganesh Phones & Addresses

  • 2127 Piedmont Rd, San Jose, CA 95132
  • Pleasanton, CA
  • Santa Clara, CA
  • Southfield, MI
  • Edison, NJ
  • Kalamazoo, MI
  • Livermore, CA

Professional Records

Medicine Doctors

Arun Ganesh Photo 1

Arun Ganesh

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Resumes

Resumes

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Manager - Data Governance And Data Management

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Location:
San Francisco, CA
Industry:
Information Technology And Services
Work:
Western Digital
Manager - Data Governance and Data Management

Atmel Corporation Jan 2012 - Mar 2015
Master Data and Supply Chain Analyst

Altera Jan 2012 - Mar 2015
Senior Business System Analyst

Deloitte Oct 2009 - Jan 2012
Functional Sap Mm and Mdm Analyst

Impressive Systems May 2008 - Oct 2009
Sap Materials Mangement and Warehouse Mgmt Consultant
Education:
University of California, Berkeley 2013 - 2015
Western Michigan University 2004 - Dec 2006
Master of Science, Masters, Industrial Engineering
Visvesvaraya Technological University Jun 2004
Bachelor of Engineering, Bachelors
Visvesvaraya Technological University 2000 - 2004
Bachelors, Mechanical Engineering
Skills:
Sap Erp
Sap
Sap Implementation
Sap R/3
Materials Management
Erp
Sd
Testing
Master Data
Integration
Vendor Management
Crm
Business Analysis
Data Migration
Procurement
Change Management
Master Data Management
Sap Fi
Certifications:
Sap Certified Scm Solutions Consulatnt
Project Management Professional
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Arun Ganesh

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Arun Ganesh

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Publications

Us Patents

Leveraging Public Data In Training Neural Networks With Private Mirror Descent

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US Patent:
20230103911, Apr 6, 2023
Filed:
Oct 4, 2022
Appl. No.:
17/937825
Inventors:
- Mountain View CA, US
Ehsan Amid - Mountain View CA, US
Arun Ganesh - Seattle WA, US
Rajiv Mathews - Sunnyvale CA, US
Swaroop Ramaswamy - Mountain View CA, US
Shuang Song - Mountain View CA, US
Thomas Steinke - Mountain View CA, US
Vinith Suriyakumar - Mountain View CA, US
Abhradeep Guha Thakurta - Los Gatos CA, US
Assignee:
Google LLC - Mountain View CA
International Classification:
G06N 3/08
Abstract:
A method include obtaining a set of differentially private (DP) gradients each generated based on processing corresponding private data, and obtaining a set of public gradients each generated based on processing corresponding public data. The method also includes applying mirror descent to the set of public gradients to learn a geometry for the set of DP gradients, and reshaping the set of DP gradients based on the learned geometry. The method further includes training a machine learning model based on the reshaped set of DP gradients.
Arun Ganesh from San Jose, CA, age ~42 Get Report