Kshitiz Malik - RankMe

22 papers A* 7A 1C 1Journal 10Unranked 2

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	An Empirical Study on Noisy Data and LLM Pretraining Loss Divergence. CoRR Qizhen Zhang, Ankush Garg, Jakob N. Foerster, Niladri S. Chatterji, Kshitiz Malik, Mike Lewis
2024	—	`conf`	Effective Long-Context Scaling of Foundation Models. NAACL-HLT 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
2023	J	`jnl`	Effective Long-Context Scaling of Foundation Models. CoRR 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
2023	C	`conf`	Joint Federated Learning and Personalization for on-Device ASR. ASRU Junteng Jia, Ke Li, Mani Malek, Kshitiz Malik, Jay Mahadeokar, Ozlem Kalinli, Frank Seide
2023	A*	`conf`	Towards Next-Generation Intelligent Assistants Leveraging LLM Techniques. KDD Xin Luna Dong, Seungwhan Moon, Yifan Ethan Xu, Kshitiz Malik, Zhou Yu
2023	A*	`conf`	Where to Begin? On the Impact of Pre-Training and Initialization in Federated Learning. ICLR John Nguyen, Jianyu Wang, Kshitiz Malik, Maziar Sanjabi, Michael G. Rabbat
2022	J	`jnl`	FedSynth: Gradient Compression via Synthetic Data in Federated Learning. CoRR Shengyuan Hu, Jack Goetz, Kshitiz Malik, Hongyuan Zhan, Zhe Liu, Yue Liu
2022	A	`conf`	Federated Learning with Buffered Asynchronous Aggregation. AISTATS John Nguyen, Kshitiz Malik, Hongyuan Zhan, Ashkan Yousefpour, Mike Rabbat, Mani Malek, Dzmitry Huba
2022	A*	`conf`	Federated Learning with Partial Model Personalization. ICML Krishna Pillutla, Kshitiz Malik, Abdelrahman Mohamed, Michael G. Rabbat, Maziar Sanjabi, Lin Xiao
2022	J	`jnl`	Federated Learning with Partial Model Personalization. CoRR Krishna Pillutla, Kshitiz Malik, Abdelrahman Mohamed, Michael G. Rabbat, Maziar Sanjabi, Lin Xiao
2022	—	`conf`	PAPAYA: Practical, Private, and Scalable Federated Learning. MLSys 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
2022	J	`jnl`	Where to Begin? Exploring the Impact of Pre-Training and Initialization in Federated Learning. CoRR John Nguyen, Kshitiz Malik, Maziar Sanjabi, Michael G. Rabbat
2022	J	`jnl`	Where to Begin? On the Impact of Pre-Training and Initialization in Federated Learning. CoRR John Nguyen, Jianyu Wang, Kshitiz Malik, Maziar Sanjabi, Michael G. Rabbat
2021	J	`jnl`	Federated Learning with Buffered Asynchronous Aggregation. CoRR John Nguyen, Kshitiz Malik, Hongyuan Zhan, Ashkan Yousefpour, Michael G. Rabbat, Mani Malek, Dzmitry Huba
2021	J	`jnl`	Papaya: Practical, Private, and Scalable Federated Learning. CoRR 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
2019	J	`jnl`	Active Federated Learning. CoRR Jack Goetz, Kshitiz Malik, Duc Bui, Seungwhan Moon, Honglei Liu, Anuj Kumar
2019	J	`jnl`	Federated User Representation Learning. CoRR Duc Bui, Kshitiz Malik, Jack Goetz, Honglei Liu, Seungwhan Moon, Anuj Kumar, Kang G. Shin
2009	—	`—`	Critical Branches and Lucky Loads in Control-Independence Architectures Kshitiz Malik
2008	A*	`conf`	Branch-mispredict level parallelism (BLP) for control independence. HPCA Kshitiz Malik, Mayank Agarwal, Sam S. Stone, Kevin M. Woley, Matthew I. Frank
2008	A*	`conf`	Fetch-Criticality Reduction through Control Independence. ISCA Mayank Agarwal, Nitin Navale, Kshitiz Malik, Matthew I. Frank
2008	A*	`conf`	PaCo: Probability-based path confidence prediction. HPCA Kshitiz Malik, Mayank Agarwal, Vikram Dhar, Matthew I. Frank
2007	A*	`conf`	Exploiting Postdominance for Speculative Parallelization. HPCA Mayank Agarwal, Kshitiz Malik, Kevin M. Woley, Sam S. Stone, Matthew I. Frank