Eichner, Hubert

Advances and Open Problems in Federated Learning

Kairouz, P., McMahan, H. B., Avent, B., Bellet, A., Bennis, M., Bhagoji, A. N., Bonawitz, K., Charles, Z., Cormode, G., Cummings, R., et al. (2019) · arXiv

Privacy-Preserving Technologies in DataStochastic Gradient Optimization Techniques

Cited by 7,857

Towards Federated Learning at Scale: System Design

Bonawitz, K., Eichner, H., Grieskamp, W., Huba, D., Ingerman, A., Ivanov, V., Kiddon, C., Konečný, J., Mazzocchi, S., McMahan, H. B., et al. (2019) · arXiv

Privacy-Preserving Technologies in DataStochastic Gradient Optimization Techniques

Cited by 2,334

Federated Learning for Mobile Keyboard Prediction

Hard, A., Rao, K., Mathews, R., Ramaswamy, S., Beaufays, F., Augenstein, S., Eichner, H., Kiddon, C., & Ramage, D. (2018) · arXiv

Privacy-Preserving Technologies in DataPrivacy, Security, and Data Protection

Cited by 1,148

Applied Federated Learning: Improving Google Keyboard Query Suggestions

Yang, T., Andrew, G., Eichner, H., Sun, H., Li, W., Kong, N., Ramage, D., & Beaufays, F. (2018) · arXiv

Privacy-Preserving Technologies in DataPrivacy, Security, and Data Protection

Cited by 684

Federated Evaluation of On-device Personalization

Wang, K., Mathews, R., Kiddon, C., Eichner, H., Beaufays, F., & Ramage, D. (2019) · arXiv

Privacy-Preserving Technologies in DataDomain Adaptation and Few-Shot Learning

Cited by 184

Semi-Cyclic Stochastic Gradient Descent

Eichner, H., Koren, T., McMahan, H. B., Srebro, N., & Talwar, K. (2019) · arXiv

Stochastic Gradient Optimization TechniquesPrivacy-Preserving Technologies in Data

Cited by 66

Neural mechanisms underlying sensitivity to reverse-phi motion in the fly

Leonhardt, A., Meier, M., Serbe, E., Eichner, H., & Borst, A. (2017) · PLOS ONE

Visual perception and processing mechanismsNeurobiology and Insect Physiology Research

Cited by 16