We propose the Target Charging Technique (TCT), a unified privacy
analys...
Composition theorems are general and powerful tools that facilitate priv...
The problem of learning threshold functions is a fundamental one in mach...
CountSketch and Feature Hashing (the "hashing trick") are popular random...
CountSketch is a popular dimensionality reduction technique that maps ve...
Clustering is a fundamental problem in data analysis. In differentially
...
Differentially private algorithms for common metric aggregation tasks, s...
Streaming algorithms are algorithms for processing large data streams, u...
Common datasets have the form of elements with keys (e.g.,
transactions ...
Weighted sampling is a fundamental tool in data analysis and machine lea...
Classically, ML models trained with stochastic gradient descent (SGD) ar...
Recently there has been increased interest in using machine learning
tec...
Influence maximization (IM) is the problem of finding a set of s nodes i...
We consider massive distributed datasets that consist of elements modele...
Metric embeddings are immensely useful representation of interacting ent...