Search Results for author:
Found 5 papers, 2 papers with code
Private Release of Text Embedding Vectors
Ensuring strong theoretical privacy guarantees on text data is a challenging problem which is usually attained at the expense of utility.
The PetShop Dataset -- Finding Causes of Performance Issues across Microservices
Although the machine learning and systems research communities have proposed various techniques to tackle this problem, there is currently a lack of standardized datasets for quantitative benchmarking.
Contextual Online False Discovery Rate Control
In this paper, we consider the problem of controlling FDR in an online manner.
Subsampled Rényi Differential Privacy and Analytical Moments Accountant
We study the problem of subsampling in differential privacy (DP), a question that is the centerpiece behind many successful differentially private machine learning algorithms.
Semi-Supervised Learning on Data Streams via Temporal Label Propagation
We consider the problem of labeling points on a fast-moving data stream when only a small number of labeled examples are available.
