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ORCIDSyed Zawad
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2020 – today
- 2025
[j5]Seyed Mahmoud Sajjadi Mohammadabadi
, Syed Zawad, Feng Yan, Lei Yang:
Speed Up Federated Learning in Heterogeneous Environments: A Dynamic Tiering Approach. IEEE Internet Things J. 12(5): 5026-5035 (2025)- [j4]Syed Zawad, Xiaolong Ma, Jun Yi, Cheng Li, Minjia Zhang, Lei Yang, Feng Yan, Yuxiong He:
FedCust: Offloading hyperparameter customization for federated learning. Perform. Evaluation 167: 102450 (2025) - [j3]Ahsan Ali, Xiaolong Ma, Syed Zawad, Paarijaat Aditya, Istemi Ekin Akkus, Ruichuan Chen, Lei Yang, Feng Yan:
Enabling scalable and adaptive machine learning training via serverless computing on public cloud. Perform. Evaluation 167: 102451 (2025) - [i10]Leonid Karlinsky, Assaf Arbelle, Abraham Daniels, Ahmed Nassar, Amit Alfassi, Bo Wu, Eli Schwartz, Dhiraj Joshi, Jovana Kondic, Nimrod Shabtay, Pengyuan Li, Roei Herzig, Shafiq Abedin, Shaked Perek, Sivan Harary, Udi Barzelay, Adi Raz Goldfarb, Aude Oliva, Ben Wieles, Bishwaranjan Bhattacharjee, Brandon Huang, Christoph Auer, Dan Gutfreund, David Beymer, David Wood, Hilde Kuehne, Jacob A. Hansen, Joseph Shtok, Ken Wong, Luis Angel D. Bathen, Mayank Mishra, Maksym Lysak, Michele Dolfi, Mikhail Yurochkin, Nikolaos Livathinos, Nimrod Harel, Ophir Azulai, Oshri Naparstek, Rafael Teixeira de Lima, Rameswar Panda, Sivan Doveh, Shubham Gupta, Subhro Das, Syed Zawad, Yusik Kim, Zexue He, Alexander Brooks, Gabe Goodhart, Anita Govindjee, Derek Leist, Ibrahim Ibrahim, Aya Soffer, David D. Cox, Kate Soule, Luis A. Lastras, Nirmit Desai, Shila Ofek-Koifman, Sriram Raghavan, Tanveer F. Syeda-Mahmood, Peter W. J. Staar, Tal Drory, Rogério Feris:
Granite Vision: a lightweight, open-source multimodal model for enterprise Intelligence. CoRR abs/2502.09927 (2025) - [i9]Hajar Emami-Gohari, Swanand Ravindra Kadhe, Syed Yousaf Shah, Constantin Adam, Abdulhamid Adebayo, Praneet Adusumilli, Farhan Ahmed, Nathalie Baracaldo Angel, Santosh Borse, Yuan Chi Chang, Xuan-Hong Dang, Nirmit Desai, Revital Eres, Ran Iwamoto, Alexei Karve, Yan Koyfman, Wei-Han Lee, Changchang Liu, Boris Lublinsky, Takuya Ohko, Pablo Pesce, Maroun Touma, Shiqiang Wang, Shalisha Witherspoon, Herbert Woisetschlaeger, David Wood, Kun-Lung Wu, Issei Yoshida, Syed Zawad, Petros Zerfos, Yi Zhou, Bishwaranjan Bhattacharjee:
GneissWeb: Preparing High Quality Data for LLMs at Scale. CoRR abs/2502.14907 (2025) - [i8]Aladin Djuhera, Swanand Ravindra Kadhe, Farhan Ahmed, Syed Zawad, Holger Boche:
SafeMERGE: Preserving Safety Alignment in Fine-Tuned Large Language Models via Selective Layer-Wise Model Merging. CoRR abs/2503.17239 (2025) - 2024
- [c9]Heiko Ludwig, Yi Zhou, Syed Zawad, Yuya Jeremy Ong, Pengyuan Li, Eric Butler, Eelaaf Zahid:
Towards Collecting Royalties for Copyrighted Data for Generative Models. ICWS 2024: 20-26 - [i7]Mayank Mishra, Matt Stallone, Gaoyuan Zhang, Yikang Shen, Aditya Prasad, Adriana Meza Soria, Michele Merler, Parameswaran Selvam, Saptha Surendran, Shivdeep Singh, Manish Sethi, Xuan-Hong Dang, Pengyuan Li, Kun-Lung Wu, Syed Zawad, Andrew Coleman, Matthew White, Mark Lewis, Raju Pavuluri, Yan Koyfman, Boris Lublinsky, Maximilien de Bayser, Ibrahim Abdelaziz, Kinjal Basu, Mayank Agarwal, Yi Zhou, Chris Johnson, Aanchal Goyal, Hima Patel, S. Yousaf Shah, Petros Zerfos, Heiko Ludwig, Asim Munawar, Maxwell Crouse, Pavan Kapanipathi, Shweta Salaria, Bob Calio, Sophia Wen, Seetharami Seelam, Brian Belgodere, Carlos A. Fonseca, Amith Singhee, Nirmit Desai, David D. Cox, Ruchir Puri, Rameswar Panda:
Granite Code Models: A Family of Open Foundation Models for Code Intelligence. CoRR abs/2405.04324 (2024) - 2023
- [b1]Syed Zawad:
Towards Scalable, Private and Practical Deep Learning. University of Nevada, Reno, USA, 2023 - [j2]Shreshth Tuli, Fatemeh Mirhakimi, Samodha Pallewatta, Syed Zawad, Giuliano Casale, Bahman Javadi, Feng Yan, Rajkumar Buyya, Nicholas R. Jennings:
AI augmented Edge and Fog computing: Trends and challenges. J. Netw. Comput. Appl. 216: 103648 (2023) - [c8]Syed Zawad, Ali Anwar, Yi Zhou, Nathalie Baracaldo, Feng Yan:
HDFL: A Heterogeneity and Client Dropout-Aware Federated Learning Framework. CCGrid 2023: 311-321 - [c7]Syed Zawad, Cheng Li, Zhewei Yao, Elton Zheng, Yuxiong He, Feng Yan:
DySR: Adaptive Super-Resolution via Algorithm and System Co-design. ICLR 2023 - [i6]Seyed Mahmoud Sajjadi Mohammadabadi, Syed Zawad, Feng Yan, Lei Yang:
Speed Up Federated Learning in Heterogeneous Environment: A Dynamic Tiering Approach. CoRR abs/2312.05642 (2023) - 2022
- [c6]Jingoo Han, Ahmad Faraz Khan, Syed Zawad, Ali Anwar, Nathalie Baracaldo, Yi Zhou, Feng Yan, Ali Raza Butt:
TIFF: Tokenized Incentive for Federated Learning. CLOUD 2022: 407-416 - [c5]Jingoo Han, Ahmad Faraz Khan, Syed Zawad, Ali Anwar, Nathalie Baracaldo, Yi Zhou, Feng Yan, Ali Raza Butt:
Heterogeneity-Aware Adaptive Federated Learning Scheduling. IEEE Big Data 2022: 911-920 - [p4]Syed Zawad, Feng Yan, Ali Anwar:
Introduction to Federated Learning Systems. Federated Learning 2022: 195-212 - [p3]Syed Zawad, Feng Yan, Ali Anwar:
Local Training and Scalability of Federated Learning Systems. Federated Learning 2022: 213-233 - [p2]Syed Zawad, Feng Yan, Ali Anwar:
Straggler Management. Federated Learning 2022: 235-258 - [p1]Syed Zawad, Feng Yan, Ali Anwar:
Systems Bias in Federated Learning. Federated Learning 2022: 259-278 - [i5]Ahsan Ali, Syed Zawad, Paarijaat Aditya, Istemi Ekin Akkus, Ruichuan Chen, Feng Yan:
SMLT: A Serverless Framework for Scalable and Adaptive Machine Learning Design and Training. CoRR abs/2205.01853 (2022) - [i4]Shreshth Tuli, Fatemeh Mirhakimi, Samodha Pallewatta, Syed Zawad, Giuliano Casale, Bahman Javadi, Feng Yan, Rajkumar Buyya, Nicholas R. Jennings:
AI Augmented Edge and Fog Computing: Trends and Challenges. CoRR abs/2208.00761 (2022) - 2021
- [c4]Syed Zawad, Ahsan Ali, Pin-Yu Chen, Ali Anwar, Yi Zhou, Nathalie Baracaldo, Yuan Tian, Feng Yan:
Curse or Redemption? How Data Heterogeneity Affects the Robustness of Federated Learning. AAAI 2021: 10807-10814 - [i3]Syed Zawad, Ahsan Ali, Pin-Yu Chen, Ali Anwar, Yi Zhou, Nathalie Baracaldo, Yuan Tian, Feng Yan:
Curse or Redemption? How Data Heterogeneity Affects the Robustness of Federated Learning. CoRR abs/2102.00655 (2021) - 2020
- [j1]Heyang Qin, Syed Zawad, Yanqi Zhou, Sanjay Padhi, Lei Yang, Feng Yan:
Reinforcement-Learning-Empowered MLaaS Scheduling for Serving Intelligent Internet of Things. IEEE Internet Things J. 7(7): 6325-6337 (2020) - [c3]Zheng Chai, Ahsan Ali, Syed Zawad, Stacey Truex, Ali Anwar, Nathalie Baracaldo, Yi Zhou, Heiko Ludwig, Feng Yan, Yue Cheng:
TiFL: A Tier-based Federated Learning System. HPDC 2020: 125-136 - [i2]Zheng Chai, Ahsan Ali, Syed Zawad, Stacey Truex, Ali Anwar, Nathalie Baracaldo, Yi Zhou, Heiko Ludwig, Feng Yan, Yue Cheng:
TiFL: A Tier-based Federated Learning System. CoRR abs/2001.09249 (2020)
2010 – 2019
- 2019
- [c2]Hsin-Pai Cheng, Patrick Yu, Haojing Hu, Syed Zawad, Feng Yan, Shiyu Li, Hai Helen Li, Yiran Chen:
Towards Decentralized Deep Learning with Differential Privacy. CLOUD 2019: 130-145 - [c1]Heyang Qin, Syed Zawad, Yanqi Zhou, Lei Yang, Dongfang Zhao, Feng Yan:
Swift machine learning model serving scheduling: a region based reinforcement learning approach. SC 2019: 13:1-13:23 - [i1]Yanqi Zhou, Peng Wang, Sercan Ömer Arik, Haonan Yu, Syed Zawad, Feng Yan, Greg Diamos:
EPNAS: Efficient Progressive Neural Architecture Search. CoRR abs/1907.04648 (2019)
Coauthor Index
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last updated on 2025-04-16 21:19 CEST by the dblp team
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