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ORCIDShashank Rajput
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2020 – today
- 2024
[c15]Samuel Horváth, Stefanos Laskaridis, Shashank Rajput, Hongyi Wang:
Maestro: Uncovering Low-Rank Structures via Trainable Decomposition. ICML 2024- 2023
- [c14]Angeliki Giannou, Shashank Rajput, Dimitris Papailiopoulos:
The Expressive Power of Tuning Only the Normalization Layers. COLT 2023: 4130-4131 - [c13]Angeliki Giannou, Shashank Rajput, Jy-yong Sohn, Kangwook Lee, Jason D. Lee, Dimitris Papailiopoulos:
Looped Transformers as Programmable Computers. ICML 2023: 11398-11442 - [c12]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:
Recommender Systems with Generative Retrieval. NeurIPS 2023 - [i16]Angeliki Giannou, Shashank Rajput, Jy-yong Sohn, Kangwook Lee, Jason D. Lee, Dimitris S. Papailiopoulos:
Looped Transformers as Programmable Computers. CoRR abs/2301.13196 (2023) - [i15]Angeliki Giannou, Shashank Rajput, Dimitris S. Papailiopoulos:
The Expressive Power of Tuning Only the Norm Layers. CoRR abs/2302.07937 (2023) - [i14]Shashank Rajput, Nikhil Mehta, Anima Singh, Raghunandan H. Keshavan, Trung Vu, Lukasz Heldt, Lichan Hong, Yi Tay, Vinh Q. Tran, Jonah Samost, Maciej Kula, Ed H. Chi, Maheswaran Sathiamoorthy:
Recommender Systems with Generative Retrieval. CoRR abs/2305.05065 (2023) - [i13]Samuel Horváth
, Stefanos Laskaridis, Shashank Rajput, Hongyi Wang:
Maestro: Uncovering Low-Rank Structures via Trainable Decomposition. CoRR abs/2308.14929 (2023) - 2022
- [c11]Kartik Sreenivasan, Shashank Rajput, Jy-yong Sohn, Dimitris S. Papailiopoulos:
Finding Nearly Everything within Random Binary Networks. AISTATS 2022: 3531-3541 - [c10]Tuan Dinh, Jy-yong Sohn, Shashank Rajput, Timothy Ossowski, Yifei Ming, Junjie Hu, Dimitris S. Papailiopoulos, Kangwook Lee:
Utilizing Language-Image Pretraining for Efficient and Robust Bilingual Word Alignment. EMNLP (Findings) 2022: 154-168 - [c9]Shashank Rajput, Kangwook Lee, Dimitris S. Papailiopoulos:
Permutation-Based SGD: Is Random Optimal? ICLR 2022 - [c8]Chulhee Yun, Shashank Rajput, Suvrit Sra:
Minibatch vs Local SGD with Shuffling: Tight Convergence Bounds and Beyond. ICLR 2022 - [c7]Tuan Dinh, Yuchen Zeng, Ruisu Zhang, Ziqian Lin, Michael Gira, Shashank Rajput, Jy-yong Sohn, Dimitris S. Papailiopoulos, Kangwook Lee:
LIFT: Language-Interfaced Fine-Tuning for Non-language Machine Learning Tasks. NeurIPS 2022 - [i12]Tuan Dinh, Jy-yong Sohn, Shashank Rajput, Timothy Ossowski, Yifei Ming, Junjie Hu, Dimitris S. Papailiopoulos, Kangwook Lee:
Utilizing Language-Image Pretraining for Efficient and Robust Bilingual Word Alignment. CoRR abs/2205.11616 (2022) - [i11]Tuan Dinh, Yuchen Zeng, Ruisu Zhang, Ziqian Lin, Michael Gira, Shashank Rajput, Jy-yong Sohn, Dimitris S. Papailiopoulos, Kangwook Lee:
LIFT: Language-Interfaced Fine-Tuning for Non-Language Machine Learning Tasks. CoRR abs/2206.06565 (2022) - 2021
- [c6]Shashank Rajput, Kartik Sreenivasan, Dimitris S. Papailiopoulos, Amin Karbasi:
An Exponential Improvement on the Memorization Capacity of Deep Threshold Networks. NeurIPS 2021: 12674-12685 - [i10]Shashank Rajput, Kangwook Lee, Dimitris S. Papailiopoulos:
Permutation-Based SGD: Is Random Optimal? CoRR abs/2102.09718 (2021) - [i9]Shashank Rajput, Kartik Sreenivasan, Dimitris S. Papailiopoulos, Amin Karbasi:
An Exponential Improvement on the Memorization Capacity of Deep Threshold Networks. CoRR abs/2106.07724 (2021) - [i8]Kartik Sreenivasan, Shashank Rajput, Jy-yong Sohn, Dimitris S. Papailiopoulos:
Finding Everything within Random Binary Networks. CoRR abs/2110.08996 (2021) - [i7]Chulhee Yun, Shashank Rajput, Suvrit Sra:
Minibatch vs Local SGD with Shuffling: Tight Convergence Bounds and Beyond. CoRR abs/2110.10342 (2021) - 2020
- [c5]Shashank Rajput, Anant Gupta, Dimitris S. Papailiopoulos:
Closing the convergence gap of SGD without replacement. ICML 2020: 7964-7973 - [c4]Ankit Pensia, Shashank Rajput, Alliot Nagle, Harit Vishwakarma, Dimitris S. Papailiopoulos:
Optimal Lottery Tickets via Subset Sum: Logarithmic Over-Parameterization is Sufficient. NeurIPS 2020 - [c3]Hongyi Wang, Kartik Sreenivasan, Shashank Rajput, Harit Vishwakarma, Saurabh Agarwal, Jy-yong Sohn, Kangwook Lee, Dimitris S. Papailiopoulos:
Attack of the Tails: Yes, You Really Can Backdoor Federated Learning. NeurIPS 2020 - [i6]Shashank Rajput, Anant Gupta, Dimitris S. Papailiopoulos:
Closing the convergence gap of SGD without replacement. CoRR abs/2002.10400 (2020) - [i5]Ankit Pensia, Shashank Rajput, Alliot Nagle, Harit Vishwakarma, Dimitris S. Papailiopoulos:
Optimal Lottery Tickets via SubsetSum: Logarithmic Over-Parameterization is Sufficient. CoRR abs/2006.07990 (2020) - [i4]Hongyi Wang, Kartik Sreenivasan, Shashank Rajput, Harit Vishwakarma, Saurabh Agarwal, Jy-yong Sohn, Kangwook Lee, Dimitris S. Papailiopoulos:
Attack of the Tails: Yes, You Really Can Backdoor Federated Learning. CoRR abs/2007.05084 (2020)
2010 – 2019
- 2019
- [c2]Shashank Rajput, Zhili Feng, Zachary Charles, Po-Ling Loh, Dimitris S. Papailiopoulos:
Does Data Augmentation Lead to Positive Margin? ICML 2019: 5321-5330 - [c1]Shashank Rajput, Hongyi Wang, Zachary Charles, Dimitris S. Papailiopoulos:
DETOX: A Redundancy-based Framework for Faster and More Robust Gradient Aggregation. NeurIPS 2019: 10320-10330 - [i3]Shashank Rajput, Zhili Feng, Zachary Charles, Po-Ling Loh, Dimitris S. Papailiopoulos:
Does Data Augmentation Lead to Positive Margin? CoRR abs/1905.03177 (2019) - [i2]Zachary Charles, Shashank Rajput, Stephen J. Wright, Dimitris S. Papailiopoulos:
Convergence and Margin of Adversarial Training on Separable Data. CoRR abs/1905.09209 (2019) - [i1]Shashank Rajput, Hongyi Wang, Zachary Charles, Dimitris S. Papailiopoulos:
DETOX: A Redundancy-based Framework for Faster and More Robust Gradient Aggregation. CoRR abs/1907.12205 (2019)
Coauthor Index
aka: Dimitris Papailiopoulos
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last updated on 2024-09-04 00:28 CEST by the dblp team
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