Kshitiz Malik

Publication Activity (10 Years)

Years Active: 2007-2024
Publications (10 Years): 16

Top Topics

Multiple Representations

Online Training

Learning Process

Top Venues

Publications

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)
Xin Luna Dong, Seungwhan Moon, Yifan Ethan Xu, Kshitiz Malik, Zhou Yu
Towards Next-Generation Intelligent Assistants Leveraging LLM Techniques. KDD (2023)
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 (2023)
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)
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)
John Nguyen, Kshitiz Malik, Hongyuan Zhan, Ashkan Yousefpour, Mike Rabbat, Mani Malek, Dzmitry Huba
Federated Learning with Buffered Asynchronous Aggregation. AISTATS (2022)
Krishna Pillutla, Kshitiz Malik, Abdelrahman Mohamed, Michael Rabbat, Maziar Sanjabi, Lin Xiao
Federated Learning with Partial Model Personalization. CoRR (2022)
John Nguyen, Jianyu Wang, Kshitiz Malik, Maziar Sanjabi, Michael Rabbat
Where to Begin? On the Impact of Pre-Training and Initialization in Federated Learning. CoRR (2022)
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)
Shengyuan Hu, Jack Goetz, Kshitiz Malik, Hongyuan Zhan, Zhe Liu, Yue Liu
FedSynth: Gradient Compression via Synthetic Data in Federated Learning. CoRR (2022)
John Nguyen, Kshitiz Malik, Maziar Sanjabi, Michael Rabbat
Where to Begin? Exploring the Impact of Pre-Training and Initialization in Federated Learning. CoRR (2022)
Krishna Pillutla, Kshitiz Malik, Abdelrahman Mohamed, Michael Rabbat, Maziar Sanjabi, Lin Xiao
Federated Learning with Partial Model Personalization. ICML (2022)
John Nguyen, Kshitiz Malik, Hongyuan Zhan, Ashkan Yousefpour, Michael Rabbat, Mani Malek Esmaeili, Dzmitry Huba
Federated Learning with Buffered Asynchronous Aggregation. CoRR (2021)
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 (2021)
Jack Goetz, Kshitiz Malik, Duc Bui, Seungwhan Moon, Honglei Liu, Anuj Kumar
Active Federated Learning. CoRR (2019)
Duc Bui, Kshitiz Malik, Jack Goetz, Honglei Liu, Seungwhan Moon, Anuj Kumar, Kang G. Shin
Federated User Representation Learning. CoRR (2019)
Mayank Agarwal, Nitin Navale, Kshitiz Malik, Matthew I. Frank
Fetch-Criticality Reduction through Control Independence. ISCA (2008)
Kshitiz Malik, Mayank Agarwal, Vikram Dhar, Matthew I. Frank
PaCo: Probability-based path confidence prediction. HPCA (2008)
Kshitiz Malik, Mayank Agarwal, Sam S. Stone, Kevin M. Woley, Matthew I. Frank
Branch-mispredict level parallelism (BLP) for control independence. HPCA (2008)
Mayank Agarwal, Kshitiz Malik, Kevin M. Woley, Sam S. Stone, Matthew I. Frank
Exploiting Postdominance for Speculative Parallelization. HPCA (2007)