Apple Workshop on Privacy-Preserving Machine Learning 2024
At Apple, we believe privacy is a fundamental human right. It’s also one of our core values, influencing both our research and the design of Apple’s products and services. Understanding how people use their devices often helps in improving the user experience. However, accessing the data that provides such insights — for example, what users type on their keyboards and the websites they visit — can compromise user privacy. We develop system architectures that enable learning at scale by leveraging advances in machine learning (ML), such as private federated learning (PFL), combined with…
At Apple, we believe privacy is a fundamental human right. Our work to protect user privacy is informed by a set of privacy principles, and one of those principles is to prioritize using on-device processing. By performing computations locally on a user’s device, we help minimize the amount of data…
*Equal Contributors While federated learning (FL) has recently emerged as a promising approach to train machine learning models, it is limited to only preliminary explorations in the domain of automatic speech recognition (ASR). Moreover, FL does not inherently guarantee user privacy and requires the use of differential privacy (DP) for…
Progress in natural language processing enables more intuitive ways of interacting with technology. For example, many of Apple’s products and services, including Siri and search, use natural language understanding and generation to enable a fluent and seamless interface experience for users. Natural language is a rapidly moving area of machine…
This is a LoRA for FLUX Klein Base 9b. **Link: https://civitai.red/models/2381927/flux2-klein-base-9b-smartphone-snapshot-photo-reality-style** All infos on how…