Shashank Rajput

According to our database, Shashank Rajput authored at least 19 papers between 2019 and 2023.

Collaborative distances:

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

2023

Maestro: Uncovering Low-Rank Structures via Trainable Decomposition.

Samuel Horváth, Stefanos Laskaridis, Shashank Rajput, Hongyi Wang

CoRR, 2023

The Expressive Power of Tuning Only the Norm Layers.

Angeliki Giannou, Shashank Rajput, Dimitris S. Papailiopoulos

CoRR, 2023

Recommender Systems with Generative Retrieval.

Shashank Rajput, Nikhil Mehta, Anima Singh, Raghunandan Hulikal Keshavan, Trung Vu, Lukasz Heldt, Lichan Hong, Yi Tay, Vinh Q. Tran, Jonah Samost, Maciej Kula, Ed H. Chi, Mahesh Sathiamoorthy

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Looped Transformers as Programmable Computers.

Angeliki Giannou, Shashank Rajput, Jy-yong Sohn, Kangwook Lee, Jason D. Lee, Dimitris Papailiopoulos

Proceedings of the International Conference on Machine Learning, 2023

The Expressive Power of Tuning Only the Normalization Layers.

Angeliki Giannou, Shashank Rajput, Dimitris Papailiopoulos

Proceedings of the Thirty Sixth Annual Conference on Learning Theory, 2023

2022

LIFT: Language-Interfaced Fine-Tuning for Non-language Machine Learning Tasks.

Tuan Dinh, Yuchen Zeng, Ruisu Zhang, Ziqian Lin, Michael Gira, Shashank Rajput, Jy-yong Sohn, Dimitris S. Papailiopoulos, Kangwook Lee

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Minibatch vs Local SGD with Shuffling: Tight Convergence Bounds and Beyond.

Chulhee Yun, Shashank Rajput, Suvrit Sra

Proceedings of the Tenth International Conference on Learning Representations, 2022

Permutation-Based SGD: Is Random Optimal?

Shashank Rajput, Kangwook Lee, Dimitris S. Papailiopoulos

Proceedings of the Tenth International Conference on Learning Representations, 2022

Utilizing Language-Image Pretraining for Efficient and Robust Bilingual Word Alignment.

Tuan Dinh, Jy-yong Sohn, Shashank Rajput, Timothy Ossowski, Yifei Ming, Junjie Hu, Dimitris S. Papailiopoulos, Kangwook Lee

Proceedings of the Findings of the Association for Computational Linguistics: EMNLP 2022, 2022

Finding Nearly Everything within Random Binary Networks.

Kartik Sreenivasan, Shashank Rajput, Jy-yong Sohn, Dimitris S. Papailiopoulos

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

2021

Finding Everything within Random Binary Networks.

Kartik Sreenivasan, Shashank Rajput, Jy-yong Sohn, Dimitris S. Papailiopoulos

CoRR, 2021

An Exponential Improvement on the Memorization Capacity of Deep Threshold Networks.

Shashank Rajput, Kartik Sreenivasan, Dimitris S. Papailiopoulos, Amin Karbasi

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

2020

Optimal Lottery Tickets via SubsetSum: Logarithmic Over-Parameterization is Sufficient.

Ankit Pensia, Shashank Rajput, Alliot Nagle, Harit Vishwakarma, Dimitris S. Papailiopoulos

CoRR, 2020

Attack of the Tails: Yes, You Really Can Backdoor Federated Learning.

Hongyi Wang, Kartik Sreenivasan, Shashank Rajput, Harit Vishwakarma, Saurabh Agarwal, Jy-yong Sohn, Kangwook Lee, Dimitris S. Papailiopoulos

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Optimal Lottery Tickets via Subset Sum: Logarithmic Over-Parameterization is Sufficient.

Ankit Pensia, Shashank Rajput, Alliot Nagle, Harit Vishwakarma, Dimitris S. Papailiopoulos

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Closing the convergence gap of SGD without replacement.

Shashank Rajput, Anant Gupta, Dimitris S. Papailiopoulos

Proceedings of the 37th International Conference on Machine Learning, 2020

2019

Convergence and Margin of Adversarial Training on Separable Data.

Zachary Charles, Shashank Rajput, Stephen J. Wright, Dimitris S. Papailiopoulos

CoRR, 2019

DETOX: A Redundancy-based Framework for Faster and More Robust Gradient Aggregation.

Shashank Rajput, Hongyi Wang, Zachary Charles, Dimitris S. Papailiopoulos

Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

Does Data Augmentation Lead to Positive Margin?

Shashank Rajput, Zhili Feng, Zachary Charles, Po-Ling Loh, Dimitris S. Papailiopoulos

Proceedings of the 36th International Conference on Machine Learning, 2019