Publications

  1. B. Li, G. Verma, and S. Segarra. Graph-based Algorithm Unfolding for Energy-aware Power Allocation in Wireless Networks. IEEE Transactions on Wireless Communications, 2022 (Submitted).
  2. B. Li, A. Swami, and S. Segarra. Power Allocation for Wireless Federated Learning using Graph Neural Networks. IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2022 (Accepted).
  3. Y. Zhu, B. Li, and S. Segarra. Hypergraphs with Edge-Dependent Vertex Weights: Spectral Clustering based on the 1-Laplacian. IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2022 (Accepted).
  4. B. Li, G. Verma, C. Rao, and S. Segarra. Energy-Efficient Power Allocation in Wireless Networks using Graph Neural Networks. Asilomar Conference on Signals, Systems, and Computers, 2021. [video]
  5. Y. Zhu, B. Li, and S. Segarra. Co-clustering Vertices and Hyperedges via Spectral Hypergraph Partitioning. European Signal Processing Conference (EUSIPCO), 2021.
  6. G. Cutura, B. Li, A. Swami and S. Segarra. Deep demixing: Reconstructing the Evolution of Epidemics using Graph Neural Networks. European Signal Processing Conference (EUSIPCO), 2021. [video]
  7. B. Li and A. Sano. Extraction and Interpretation of Deep Autoencoder-based Temporal Features from Wearables for Forecasting Personalized Mood, Health, and Stress. Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies (IMWUT), 2020. [video]
  8. B. Li and A. Sano. Early versus Late Modality Fusion of Deep Wearable Sensor Features for Personalized Prediction of Tomorrow’s Mood, Health, and Stress. International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC), 2020. [video]
  9. B. Li, T. B. Smith, K. R. Choudhury, B. Harrawood, L. Ebner, J. E. Roos and G. D. Rubin. Influence of Background Lung Characteristics on Nodule Detection with Computed Tomography. Journal of Medical Imaging, 2020.
  10. B. Li, H. Yu and A. Sano. Toward End-to-end Prediction of Future Wellbeing using Deep Sensor Representation Learning. International Conference on Affective Computing and Intelligent Interaction Workshops and Demos (ACIIW), 2019.
  11. J. M. Malof, B. Li, B. Huang, K. Bradbury and A. Stretslov. Mapping Solar Array Location, Size, and Capacity using Deep Learning and Overhead Imagery. arXiv preprint arXiv:1902.10895, 2019.