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2020 – today
- 2024
[c11]Wenhan Xiong, Jingyu Liu, Igor Molybog, Hejia Zhang, Prajjwal Bhargava, Rui Hou, Louis Martin, Rashi Rungta, Karthik Abinav Sankararaman, Barlas Oguz, Madian Khabsa, Han Fang, Yashar Mehdad, Sharan Narang, Kshitiz Malik, Angela Fan, Shruti Bhosale, Sergey Edunov, Mike Lewis, Sinong Wang, Hao Ma:
Effective Long-Context Scaling of Foundation Models. NAACL-HLT 2024: 4643-4663- 2023
- [c10]Junteng Jia, Ke Li, Mani Malek, Kshitiz Malik, Jay Mahadeokar, Ozlem Kalinli, Frank Seide:
Joint Federated Learning and Personalization for on-Device ASR. ASRU 2023: 1-8 - [c9]John Nguyen, Jianyu Wang, Kshitiz Malik, Maziar Sanjabi, Michael G. Rabbat:
Where to Begin? On the Impact of Pre-Training and Initialization in Federated Learning. ICLR 2023 - [c8]Xin Luna Dong
, Seungwhan Moon, Yifan Ethan Xu, Kshitiz Malik, Zhou Yu:
Towards Next-Generation Intelligent Assistants Leveraging LLM Techniques. KDD 2023: 5792-5793 - [i9]Wenhan Xiong, Jingyu Liu, Igor Molybog, Hejia Zhang, Prajjwal Bhargava, Rui Hou, Louis Martin, Rashi Rungta, Karthik Abinav Sankararaman, Barlas Oguz, Madian Khabsa, Han Fang, Yashar Mehdad, Sharan Narang, Kshitiz Malik, Angela Fan, Shruti Bhosale, Sergey Edunov, Mike Lewis, Sinong Wang, Hao Ma:
Effective Long-Context Scaling of Foundation Models. CoRR abs/2309.16039 (2023) - 2022
- [c7]John Nguyen, Kshitiz Malik, Hongyuan Zhan, Ashkan Yousefpour, Mike Rabbat, Mani Malek, Dzmitry Huba:
Federated Learning with Buffered Asynchronous Aggregation. AISTATS 2022: 3581-3607 - [c6]Krishna Pillutla, Kshitiz Malik, Abdelrahman Mohamed, Michael G. Rabbat, Maziar Sanjabi, Lin Xiao:
Federated Learning with Partial Model Personalization. ICML 2022: 17716-17758 - [c5]Dzmitry Huba, John Nguyen, Kshitiz Malik, Ruiyu Zhu, Mike Rabbat, Ashkan Yousefpour, Carole-Jean Wu, Hongyuan Zhan, Pavel Ustinov, Harish Srinivas, Kaikai Wang, Anthony Shoumikhin, Jesik Min, Mani Malek:
PAPAYA: Practical, Private, and Scalable Federated Learning. MLSys 2022 - [i8]Shengyuan Hu, Jack Goetz, Kshitiz Malik, Hongyuan Zhan, Zhe Liu, Yue Liu:
FedSynth: Gradient Compression via Synthetic Data in Federated Learning. CoRR abs/2204.01273 (2022) - [i7]Krishna Pillutla, Kshitiz Malik, Abdelrahman Mohamed, Michael G. Rabbat, Maziar Sanjabi, Lin Xiao:
Federated Learning with Partial Model Personalization. CoRR abs/2204.03809 (2022) - [i6]John Nguyen, Kshitiz Malik, Maziar Sanjabi, Michael G. Rabbat:
Where to Begin? Exploring the Impact of Pre-Training and Initialization in Federated Learning. CoRR abs/2206.15387 (2022) - [i5]John Nguyen, Jianyu Wang, Kshitiz Malik, Maziar Sanjabi, Michael G. Rabbat:
Where to Begin? On the Impact of Pre-Training and Initialization in Federated Learning. CoRR abs/2210.08090 (2022) - 2021
- [i4]John Nguyen, Kshitiz Malik, Hongyuan Zhan, Ashkan Yousefpour, Michael G. Rabbat, Mani Malek, Dzmitry Huba:
Federated Learning with Buffered Asynchronous Aggregation. CoRR abs/2106.06639 (2021) - [i3]Dzmitry Huba, John Nguyen, Kshitiz Malik, Ruiyu Zhu, Mike Rabbat, Ashkan Yousefpour, Carole-Jean Wu, Hongyuan Zhan, Pavel Ustinov, Harish Srinivas, Kaikai Wang, Anthony Shoumikhin, Jesik Min, Mani Malek:
Papaya: Practical, Private, and Scalable Federated Learning. CoRR abs/2111.04877 (2021)
2010 – 2019
- 2019
- [i2]Duc Bui, Kshitiz Malik, Jack Goetz, Honglei Liu, Seungwhan Moon, Anuj Kumar, Kang G. Shin:
Federated User Representation Learning. CoRR abs/1909.12535 (2019) - [i1]Jack Goetz, Kshitiz Malik, Duc Bui, Seungwhan Moon, Honglei Liu, Anuj Kumar:
Active Federated Learning. CoRR abs/1909.12641 (2019)
2000 – 2009
- 2009
- [b1]Kshitiz Malik:
Critical Branches and Lucky Loads in Control-Independence Architectures. University of Illinois Urbana-Champaign, USA, 2009 - 2008
- [c4]Kshitiz Malik, Mayank Agarwal, Vikram Dhar, Matthew I. Frank:
PaCo: Probability-based path confidence prediction. HPCA 2008: 50-61 - [c3]Kshitiz Malik, Mayank Agarwal, Sam S. Stone, Kevin M. Woley, Matthew I. Frank:
Branch-mispredict level parallelism (BLP) for control independence. HPCA 2008: 62-73 - [c2]Mayank Agarwal, Nitin Navale, Kshitiz Malik, Matthew I. Frank:
Fetch-Criticality Reduction through Control Independence. ISCA 2008: 13-24 - 2007
- [c1]Mayank Agarwal, Kshitiz Malik, Kevin M. Woley, Sam S. Stone, Matthew I. Frank:
Exploiting Postdominance for Speculative Parallelization. HPCA 2007: 295-305
Coauthor Index
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