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2020 – today
- 2024
[c13]Kaan Ozkara, Can Karakus, Parameswaran Raman, Mingyi Hong, Shoham Sabach, Branislav Kveton, Volkan Cevher:
MADA: Meta-Adaptive Optimizers Through Hyper-Gradient Descent. ICML 2024- [i13]Kaan Ozkara, Can Karakus, Parameswaran Raman, Mingyi Hong, Shoham Sabach, Branislav Kveton, Volkan Cevher:
MADA: Meta-Adaptive Optimizers through hyper-gradient Descent. CoRR abs/2401.08893 (2024) - 2021
- [i12]Can Karakus, Rahul Huilgol, Fei Wu, Anirudh Subramanian, Cade Daniel, Derya Çavdar, Teng Xu, Haohan Chen, Arash Rahnama, Luis Quintela:
Amazon SageMaker Model Parallelism: A General and Flexible Framework for Large Model Training. CoRR abs/2111.05972 (2021) - 2020
- [j5]Debraj Basu
, Deepesh Data, Can Karakus, Suhas N. Diggavi:
Qsparse-Local-SGD: Distributed SGD With Quantization, Sparsification, and Local Computations. IEEE J. Sel. Areas Inf. Theory 1(1): 217-226 (2020) - [c12]Indu Thangakrishnan, Derya Cavdar, Can Karakus, Piyush Ghai, Yauheni Selivonchyk, Cory Pruce:
Herring: rethinking the parameter server at scale for the cloud. SC 2020: 44
2010 – 2019
- 2019
- [j4]Can Karakus, Yifan Sun, Suhas N. Diggavi, Wotao Yin:
Redundancy Techniques for Straggler Mitigation in Distributed Optimization and Learning. J. Mach. Learn. Res. 20: 72:1-72:47 (2019) - [c11]Debraj Basu, Deepesh Data, Can Karakus, Suhas N. Diggavi:
Qsparse-local-SGD: Distributed SGD with Quantization, Sparsification and Local Computations. NeurIPS 2019: 14668-14679 - [c10]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:
Densifying Assumed-Sparse Tensors - Improving Memory Efficiency and MPI Collective Performance During Tensor Accumulation for Parallelized Training of Neural Machine Translation Models. ISC 2019: 23-39 - [i11]Mehrdad Showkatbakhsh, Can Karakus, Suhas N. Diggavi:
Privacy-Utility Trade-off of Linear Regression under Random Projections and Additive Noise. CoRR abs/1902.04688 (2019) - [i10]Mehrdad Showkatbakhsh, Can Karakus, Suhas N. Diggavi:
Differentially Private Consensus-Based Distributed Optimization. CoRR abs/1903.07792 (2019) - [i9]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:
Densifying Assumed-sparse Tensors: Improving Memory Efficiency and MPI Collective Performance during Tensor Accumulation for Parallelized Training of Neural Machine Translation Models. CoRR abs/1905.04035 (2019) - [i8]Debraj Basu, Deepesh Data, Can Karakus, Suhas N. Diggavi:
Qsparse-local-SGD: Distributed SGD with Quantization, Sparsification, and Local Computations. CoRR abs/1906.02367 (2019) - 2018
- [b1]Can Karakus:
Robust Communication and Optimization over Dynamic Networks. University of California, Los Angeles, USA, 2018 - [j3]Joyson Sebastian, Can Karakus, Suhas N. Diggavi:
Approximate Capacity of Fast Fading Interference Channels With no Instantaneous CSIT. IEEE Trans. Commun. 66(12): 6015-6027 (2018) - [c9]Mehrdad Showkatbakhsh, Can Karakus, Suhas N. Diggavi:
Privacy-Utility Trade-off of Linear Regression under Random Projections and Additive Noise. ISIT 2018: 186-190 - [i7]Can Karakus, Yifan Sun, Suhas N. Diggavi, Wotao Yin:
Redundancy Techniques for Straggler Mitigation in Distributed Optimization and Learning. CoRR abs/1803.05397 (2018) - 2017
- [j2]Can Karakus, Suhas N. Diggavi:
Enhancing Multiuser MIMO Through Opportunistic D2D Cooperation. IEEE Trans. Wirel. Commun. 16(9): 5616-5629 (2017) - [c8]Can Karakus, Yifan Sun, Suhas N. Diggavi:
Encoded distributed optimization. ISIT 2017: 2890-2894 - [c7]Can Karakus, Yifan Sun, Suhas N. Diggavi, Wotao Yin:
Straggler Mitigation in Distributed Optimization Through Data Encoding. NIPS 2017: 5434-5442 - [i6]Joyson Sebastian, Can Karakus, Suhas N. Diggavi:
Approximate capacity of Fading Gaussian Interference Channels with Point-to-Point codes. CoRR abs/1706.03659 (2017) - [i5]Can Karakus, Yifan Sun, Suhas N. Diggavi, Wotao Yin:
Straggler Mitigation in Distributed Optimization Through Data Encoding. CoRR abs/1711.04969 (2017) - 2016
- [c6]Joyson Sebastian, Can Karakus, Suhas N. Diggavi:
Approximately achieving the feedback interference channel capacity with point-to-point codes. ISIT 2016: 715-719 - [i4]Can Karakus, Suhas N. Diggavi:
Enhancing Multiuser MIMO Through Opportunistic D2D Cooperation. CoRR abs/1604.06151 (2016) - 2015
- [j1]Can Karakus, I-Hsiang Wang, Suhas N. Diggavi:
Gaussian Interference Channel With Intermittent Feedback. IEEE Trans. Inf. Theory 61(9): 4663-4699 (2015) - [c5]Joyson Sebastian, Can Karakus, Suhas N. Diggavi, I-Hsiang Wang:
Rate splitting is approximately optimal for fading Gaussian interference channels. Allerton 2015: 315-321 - [c4]Can Karakus, Suhas N. Diggavi:
Opportunistic scheduling for full-duplex uplink-downlink networks. ISIT 2015: 1019-1023 - [i3]Can Karakus, Suhas N. Diggavi:
Opportunistic Scheduling for Full-Duplex Uplink-Downlink Networks. CoRR abs/1504.05898 (2015) - 2014
- [i2]Can Karakus, I-Hsiang Wang, Suhas N. Diggavi:
Gaussian Interference Channel with Intermittent Feedback. CoRR abs/1408.4590 (2014) - 2013
- [c3]Can Karakus, I-Hsiang Wang, Suhas N. Diggavi:
An achievable rate region for Gaussian interference channel with intermittent feedback. Allerton 2013: 203-210 - [c2]Can Karakus, I-Hsiang Wang, Suhas N. Diggavi:
Interference channel with intermittent feedback. ISIT 2013: 26-30 - [i1]Can Karakus, I-Hsiang Wang, Suhas N. Diggavi:
Interference Channel with Intermittent Feedback. CoRR abs/1305.3265 (2013) - 2011
- [c1]Denisa Ghita, Can Karakus, Katerina J. Argyraki, Patrick Thiran:
Shifting network tomography toward a practical goal. CoNEXT 2011: 24
Coauthor Index
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last updated on 2024-09-13 00:41 CEST by the dblp team
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