Cost aware Inference for IoT Devices. - Pengkai Zhu; Durmus Alp Emre Acar; Nan Feng; Prateek Jain 002; Venkatesh Saligrama (AISTATS, 2019)

Shallow RNN: Accurate Time-series Classification on Resource Constrained Devices. - Don Kurian Dennis; Durmus Alp Emre Acar; Vikram Mandikal; Vinu Sankar Sadasivan; Venkatesh Saligrama; Harsha Vardhan Simhadri; Prateek Jain 002 (NeurIPS, 2019)

Budget Learning via Bracketing. - Durmus Alp Emre Acar; Aditya Gangrade; Venkatesh Saligrama (AISTATS, 2020)

Federated Learning Based on Dynamic Regularization. - Durmus Alp Emre Acar; Yue Zhao; Ramon Matas Navarro; Matthew Mattina; Paul N. Whatmough; Venkatesh Saligrama (ICLR, 2021)

Memory Efficient Online Meta Learning. - Durmus Alp Emre Acar; Ruizhao Zhu; Venkatesh Saligrama (ICML, 2021)

Debiasing Model Updates for Improving Personalized Federated Training. - Durmus Alp Emre Acar; Yue Zhao; Ruizhao Zhu; Ramon Matas Navarro; Matthew Mattina; Paul N. Whatmough; Venkatesh Saligrama (ICML, 2021)

Faster Convex Lipschitz Regression via 2-block ADMM. - Ali Siahkamari; Durmus Alp Emre Acar; Christopher Liao; Kelly Geyer; Venkatesh Saligrama; Brian Kulis (CoRR, 2021)

Faster Algorithms for Learning Convex Functions. - Ali Siahkamari; Durmus Alp Emre Acar; Christopher Liao; Kelly L. Geyer; Venkatesh Saligrama; Brian Kulis (ICML, 2022)

FedHeN: Federated Learning in Heterogeneous Networks. - Durmus Alp Emre Acar; Venkatesh Saligrama (CoRR, 2022)

Scaffolding a Student to Instill Knowledge. - Anil Kag; Durmus Alp Emre Acar; Aditya Gangrade; Venkatesh Saligrama (ICLR, 2023)

Towards Federated Learning with On-device Training and Communication in 8-bit Floating Point. - Bokun Wang; Axel Berg; Durmus Alp Emre Acar; Chuteng Zhou (CoRR, 2024)