| 2024 | ICML | MADA: Meta-Adaptive Optimizers Through Hyper-Gradient Descent. | Kaan Ozkara, Can Karakus, Parameswaran Raman, Mingyi Hong, Shoham Sabach, Branislav Kveton, Volkan Cevher |
| 2020 | SC | Herring: rethinking the parameter server at scale for the cloud. | Indu Thangakrishnan, Derya Cavdar, Can Karakus, Piyush Ghai, Yauheni Selivonchyk, Cory Pruce |
| 2018 | ISIT | Privacy-Utility Trade-off of Linear Regression under Random Projections and Additive Noise. | Mehrdad Showkatbakhsh, Can Karakus, Suhas N. Diggavi |
| 2017 | ISIT | Encoded distributed optimization. | Can Karakus, Yifan Sun, Suhas N. Diggavi |
| 2016 | ISIT | Approximately achieving the feedback interference channel capacity with point-to-point codes. | Joyson Sebastian, Can Karakus, Suhas N. Diggavi |
| 2015 | ISIT | Opportunistic scheduling for full-duplex uplink-downlink networks. | Can Karakus, Suhas N. Diggavi |
| 2013 | ISIT | Interference channel with intermittent feedback. | Can Karakus, I-Hsiang Wang, Suhas N. Diggavi |
| 2011 | CoNEXT | Shifting network tomography toward a practical goal. | Denisa Ghita, Can Karakus, Katerina J. Argyraki, Patrick Thiran |