Muriel Médard

Repeat-Free Codes.

2019 · arXiv (Cornell University)

In this paper we consider the problem of encoding data into \textit{repeat-free} sequences in which sequences are imposed to contain any $k$-tuple at most once (for predefined $k$). First, the capacity of the repeat-free constraint …

Low Influence, Utility, and Independence in Differential Privacy: A\n Curious Case of $3 \\choose 2$

2020 · arXiv (Cornell University)

We study the relationship between randomized low influence functions and\ndifferentially private mechanisms. Our main aim is to formally determine\nwhether differentially private mechanisms are low influence and whether low\ninfluence randomized functions can be differentially private. We …

InfoShape: Task-Based Neural Data Shaping via Mutual Information

2022 · arXiv (Cornell University)

The use of mutual information as a tool in private data sharing has remained an open challenge due to the difficulty of its estimation in practice. In this paper, we propose InfoShape, a task-based encoder …

MultiTok: Variable-Length Tokenization for Efficient LLMs Adapted from LZW Compression

2024 · arXiv (Cornell University)

Large language models have drastically changed the prospects of AI by introducing technologies for more complex natural language processing. However, current methodologies to train such LLMs require extensive resources including but not limited to large …