High Dimensional Differentially Private Stochastic Optimization with Heavy-Tailed Data

Mathematics

• Data Distribution 100%
• Stochastics 100%
• Loss Function 66%
• Dimensional Space 66%
• Linear Models 33%
• Error Bound 33%
• Polytope 33%
• Fourth-Order 33%
• Underlying Space 33%

Keyphrases

• Learning Statistics 33%
• Polytope Constraints 33%
• L0-norm Constraint 33%
• Sparse Linear Models 33%
• Learning Privacy 33%