Kshitiz Malik

According to our database, Kshitiz Malik authored at least 16 papers between 2007 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2024

Effective Long-Context Scaling of Foundation Models.

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

Proceedings of the 2024 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies (Volume 1: Long Papers), 2024

2023

Towards Next-Generation Intelligent Assistants Leveraging LLM Techniques.

Xin Luna Dong, Seungwhan Moon, Yifan Ethan Xu, Kshitiz Malik, Zhou Yu

Proceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2023

Where to Begin? On the Impact of Pre-Training and Initialization in Federated Learning.

John Nguyen, Jianyu Wang, Kshitiz Malik, Maziar Sanjabi, Michael G. Rabbat

Proceedings of the Eleventh International Conference on Learning Representations, 2023

Joint Federated Learning and Personalization for on-Device ASR.

Junteng Jia, Ke Li, Mani Malek, Kshitiz Malik, Jay Mahadeokar, Ozlem Kalinli, Frank Seide

Proceedings of the IEEE Automatic Speech Recognition and Understanding Workshop, 2023

2022

Where to Begin? Exploring the Impact of Pre-Training and Initialization in Federated Learning.

John Nguyen, Kshitiz Malik, Maziar Sanjabi, Michael G. Rabbat

CoRR, 2022

FedSynth: Gradient Compression via Synthetic Data in Federated Learning.

Shengyuan Hu, Jack Goetz, Kshitiz Malik, Hongyuan Zhan, Zhe Liu, Yue Liu

CoRR, 2022

PAPAYA: Practical, Private, and Scalable Federated Learning.

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

Proceedings of the Fifth Conference on Machine Learning and Systems, 2022

Federated Learning with Partial Model Personalization.

Krishna Pillutla, Kshitiz Malik, Abdelrahman Mohamed, Michael G. Rabbat, Maziar Sanjabi, Lin Xiao

Proceedings of the International Conference on Machine Learning, 2022

Federated Learning with Buffered Asynchronous Aggregation.

John Nguyen, Kshitiz Malik, Hongyuan Zhan, Ashkan Yousefpour, Mike Rabbat, Mani Malek, Dzmitry Huba

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2022

2019

Active Federated Learning.

Jack Goetz, Kshitiz Malik, Duc Bui, Seungwhan Moon, Honglei Liu, Anuj Kumar

CoRR, 2019

Federated User Representation Learning.

Duc Bui, Kshitiz Malik, Jack Goetz, Honglei Liu, Seungwhan Moon, Anuj Kumar, Kang G. Shin

CoRR, 2019

2009

Critical Branches and Lucky Loads in Control-Independence Architectures

Kshitiz Malik

PhD thesis, 2009

2008

Fetch-Criticality Reduction through Control Independence.

Mayank Agarwal, Nitin Navale, Kshitiz Malik, Matthew I. Frank

Proceedings of the 35th International Symposium on Computer Architecture (ISCA 2008), 2008

Branch-mispredict level parallelism (BLP) for control independence.

Kshitiz Malik, Mayank Agarwal, Sam S. Stone, Kevin M. Woley, Matthew I. Frank

Proceedings of the 14th International Conference on High-Performance Computer Architecture (HPCA-14 2008), 2008

PaCo: Probability-based path confidence prediction.

Kshitiz Malik, Mayank Agarwal, Vikram Dhar, Matthew I. Frank

Proceedings of the 14th International Conference on High-Performance Computer Architecture (HPCA-14 2008), 2008

2007

Exploiting Postdominance for Speculative Parallelization.

Mayank Agarwal, Kshitiz Malik, Kevin M. Woley, Sam S. Stone, Matthew I. Frank

Proceedings of the 13st International Conference on High-Performance Computer Architecture (HPCA-13 2007), 2007