papers

Publications (66)

cs.NI2019

Machine Learning based detection of multiple Wi-Fi BSSs for LTE-U CSAT

Vanlin Sathya, Adam Dziedzic, Monisha Ghosh +1

According to the LTE-U Forum specification, a LTE-U base-station (BS) reduces its duty cycle from 50% to 33% when it senses an increase in the number of co-channel Wi-Fi basic serv…

cs.CV2025

BitMark: Watermarking Bitwise Autoregressive Image Generative Models

Louis Kerner, Michel Meintz, Bihe Zhao +2

State-of-the-art text-to-image models generate photorealistic images at an unprecedented speed. This work focuses on models that operate in a bitwise autoregressive manner over a d…

cs.CV2024

Benchmarking Robust Self-Supervised Learning Across Diverse Downstream Tasks

Antoni Kowalczuk, Jan Dubiński, Atiyeh Ashari Ghomi +6

Large-scale vision models have become integral in many applications due to their unprecedented performance and versatility across downstream tasks. However, the robustness of these…

cs.LG2024

Have it your way: Individualized Privacy Assignment for DP-SGD

Franziska Boenisch, Christopher Mühl, Adam Dziedzic +2

When training a machine learning model with differential privacy, one sets a privacy budget. This budget represents a maximal privacy violation that any user is willing to face by…

cs.NI2020

Machine Learning enabled Spectrum Sharing in Dense LTE-U/Wi-Fi Coexistence Scenarios

Adam Dziedzic, Vanlin Sathya, Muhammad Iqbal Rochman +2

The application of Machine Learning (ML) techniques to complex engineering problems has proved to be an attractive and efficient solution. ML has been successfully applied to sever…

cs.LG2024

On the Privacy Risk of In-context Learning

Haonan Duan, Adam Dziedzic, Mohammad Yaghini +2

Large language models (LLMs) are excellent few-shot learners. They can perform a wide variety of tasks purely based on natural language prompts provided to them. These prompts cont…