Can Karakus - RankMe

34 papers A* 2A 2B 5C 1Journal 19Unranked 4

Year	Rank	Type	Title / Venue / Authors
2025	—	`conf`	Marconi: Prefix Caching for the Era of Hybrid LLMs. MLSys Rui Pan, Zhuang Wang, Zhen Jia, Can Karakus, Luca Zancato, Tri Dao, Yida Wang, Ravi Netravali
2024	A*	`conf`	MADA: Meta-Adaptive Optimizers Through Hyper-Gradient Descent. ICML Kaan Ozkara, Can Karakus, Parameswaran Raman, Mingyi Hong, Shoham Sabach, Branislav Kveton, Volkan Cevher
2024	J	`jnl`	MADA: Meta-Adaptive Optimizers through hyper-gradient Descent. CoRR Kaan Ozkara, Can Karakus, Parameswaran Raman, Mingyi Hong, Shoham Sabach, Branislav Kveton, Volkan Cevher
2024	J	`jnl`	Marconi: Prefix Caching for the Era of Hybrid LLMs. CoRR Rui Pan, Zhuang Wang, Zhen Jia, Can Karakus, Luca Zancato, Tri Dao, Ravi Netravali, Yida Wang
2021	J	`jnl`	Amazon SageMaker Model Parallelism: A General and Flexible Framework for Large Model Training. CoRR Can Karakus, Rahul Huilgol, Fei Wu, Anirudh Subramanian, Cade Daniel, Derya Çavdar, Teng Xu, Haohan Chen, Arash Rahnama, Luis Quintela
2020	A	`conf`	Herring: rethinking the parameter server at scale for the cloud. SC Indu Thangakrishnan, Derya Cavdar, Can Karakus, Piyush Ghai, Yauheni Selivonchyk, Cory Pruce
2020	J	`jnl`	Qsparse-Local-SGD: Distributed SGD With Quantization, Sparsification, and Local Computations. IEEE J. Sel. Areas Inf. Theory Debraj Basu, Deepesh Data, Can Karakus, Suhas N. Diggavi
2019	C	`conf`	Densifying Assumed-Sparse Tensors - Improving Memory Efficiency and MPI Collective Performance During Tensor Accumulation for Parallelized Training of Neural Machine Translation Models. ISC Derya Cavdar, Valeriu Codreanu, Can Karakus, John A. Lockman III, Damian Podareanu, Vikram A. Saletore, Alexander Sergeev, Don D. Smith II, Victor Suthichai, Quy Ta, Srinivas Varadharajan, Lucas A. Wilson, Rengan Xu, Pei Yang
2019	J	`jnl`	Densifying Assumed-sparse Tensors: Improving Memory Efficiency and MPI Collective Performance during Tensor Accumulation for Parallelized Training of Neural Machine Translation Models. CoRR Derya Çavdar, Valeriu Codreanu, Can Karakus, John A. Lockman III, Damian Podareanu, Vikram A. Saletore, Alexander Sergeev, Don D. Smith II, Victor Suthichai, Quy Ta, Srinivas Varadharajan, Lucas A. Wilson, Rengan Xu, Pei Yang
2019	J	`jnl`	Differentially Private Consensus-Based Distributed Optimization. CoRR Mehrdad Showkatbakhsh, Can Karakus, Suhas N. Diggavi
2019	J	`jnl`	Privacy-Utility Trade-off of Linear Regression under Random Projections and Additive Noise. CoRR Mehrdad Showkatbakhsh, Can Karakus, Suhas N. Diggavi
2019	A*	`conf`	Qsparse-local-SGD: Distributed SGD with Quantization, Sparsification and Local Computations. NeurIPS Debraj Basu, Deepesh Data, Can Karakus, Suhas N. Diggavi
2019	J	`jnl`	Qsparse-local-SGD: Distributed SGD with Quantization, Sparsification, and Local Computations. CoRR Debraj Basu, Deepesh Data, Can Karakus, Suhas N. Diggavi
2019	J	`jnl`	Redundancy Techniques for Straggler Mitigation in Distributed Optimization and Learning. J. Mach. Learn. Res. Can Karakus, Yifan Sun, Suhas N. Diggavi, Wotao Yin
2018	J	`jnl`	Approximate Capacity of Fast Fading Interference Channels With no Instantaneous CSIT. IEEE Trans. Commun. Joyson Sebastian, Can Karakus, Suhas N. Diggavi
2018	B	`conf`	Privacy-Utility Trade-off of Linear Regression under Random Projections and Additive Noise. ISIT Mehrdad Showkatbakhsh, Can Karakus, Suhas N. Diggavi
2018	J	`jnl`	Redundancy Techniques for Straggler Mitigation in Distributed Optimization and Learning. CoRR Can Karakus, Yifan Sun, Suhas N. Diggavi, Wotao Yin
2018	—	`—`	Robust Communication and Optimization over Dynamic Networks. Can Karakus
2017	J	`jnl`	Approximate capacity of Fading Gaussian Interference Channels with Point-to-Point codes. CoRR Joyson Sebastian, Can Karakus, Suhas N. Diggavi
2017	B	`conf`	Encoded distributed optimization. ISIT Can Karakus, Yifan Sun, Suhas N. Diggavi
2017	J	`jnl`	Enhancing Multiuser MIMO Through Opportunistic D2D Cooperation. IEEE Trans. Wirel. Commun. Can Karakus, Suhas N. Diggavi
2017	—	`conf`	Straggler Mitigation in Distributed Optimization Through Data Encoding. NIPS Can Karakus, Yifan Sun, Suhas N. Diggavi, Wotao Yin
2017	J	`jnl`	Straggler Mitigation in Distributed Optimization Through Data Encoding. CoRR Can Karakus, Yifan Sun, Suhas N. Diggavi, Wotao Yin
2016	B	`conf`	Approximately achieving the feedback interference channel capacity with point-to-point codes. ISIT Joyson Sebastian, Can Karakus, Suhas N. Diggavi
2016	J	`jnl`	Enhancing Multiuser MIMO Through Opportunistic D2D Cooperation. CoRR Can Karakus, Suhas N. Diggavi
2015	J	`jnl`	Gaussian Interference Channel With Intermittent Feedback. IEEE Trans. Inf. Theory Can Karakus, I-Hsiang Wang, Suhas N. Diggavi
2015	J	`jnl`	Opportunistic Scheduling for Full-Duplex Uplink-Downlink Networks. CoRR Can Karakus, Suhas N. Diggavi
2015	B	`conf`	Opportunistic scheduling for full-duplex uplink-downlink networks. ISIT Can Karakus, Suhas N. Diggavi
2015	—	`conf`	Rate splitting is approximately optimal for fading Gaussian interference channels. Allerton Joyson Sebastian, Can Karakus, Suhas N. Diggavi, I-Hsiang Wang
2014	J	`jnl`	Gaussian Interference Channel with Intermittent Feedback. CoRR Can Karakus, I-Hsiang Wang, Suhas N. Diggavi
2013	—	`conf`	An achievable rate region for Gaussian interference channel with intermittent feedback. Allerton Can Karakus, I-Hsiang Wang, Suhas N. Diggavi
2013	J	`jnl`	Interference Channel with Intermittent Feedback CoRR Can Karakus, I-Hsiang Wang, Suhas N. Diggavi
2013	B	`conf`	Interference channel with intermittent feedback. ISIT Can Karakus, I-Hsiang Wang, Suhas N. Diggavi
2011	A	`conf`	Shifting network tomography toward a practical goal. CoNEXT Denisa Ghita, Can Karakus, Katerina J. Argyraki, Patrick Thiran