Remove Data Modeling Remove Data Silos Remove Natural Language Processing
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Meet the Final Winners of the U.S. PETs Prize Challenge

DrivenData Labs

Our framework involves three key components: (1) model personalization for capturing data heterogeneity across data silos, (2) local noisy gradient descent for silo-specific, node-level differential privacy in contact graphs, and (3) model mean-regularization to balance privacy-heterogeneity trade-offs and minimize the loss of accuracy.

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Data Intelligence empowers informed decisions

Pickl AI

Marketing Targeted Campaigns Increases campaign effectiveness and ROI Data silos leading to inconsistent information. Implementing integrated data management systems. Implementing transparent data privacy policies. Social Media Analytics Analyses sentiment and improves brand perception Handling unstructured data.