Yike Guo

Deep Unfolded IRLS-ADMM Network for Classification and Sparse Feature Selection

2018 · International Journal of Machine Learning and Computing

Two main branches of machine learning methods are model-based methods and deep neural networks. Model-based methods can explicitly include prior knowledge into the model at expense of difficulties in inference, while neural networks are featured …

BU-Trace: A Permissionless Mobile System for Privacy-Preserving Intelligent Contact Tracing

2021 · arXiv (Cornell University)

The coronavirus disease 2019 (COVID-19) pandemic has caused an unprecedented health crisis for the global. Digital contact tracing, as a transmission intervention measure, has shown its effectiveness on pandemic control. Despite intensive research on digital …

MKD: Mixup-Based Knowledge Distillation for Mandarin End-to-End Speech Recognition

2022 · Algorithms

Large-scale automatic speech recognition model has achieved impressive performance. However, huge computational resources and massive amount of data are required to train an ASR model. Knowledge distillation is a prevalent model compression method which transfers …

zkFL: Zero-Knowledge Proof-Based Gradient Aggregation for Federated Learning

2024 · IEEE Transactions on Big Data

Federated learning (FL) is a machine learning paradigm, which enables multiple and decentralized clients to collaboratively train a model under the orchestration of a central aggregator. FL can be a scalable machine learning solution inbig …

SafeLawBench: Towards Safe Alignment of Large Language Models

2025 · arXiv (Cornell University)

With the growing prevalence of large language models (LLMs), the safety of LLMs has raised significant concerns. However, there is still a lack of definitive standards for evaluating their safety due to the subjective nature …