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2020 – today
- 2024
[c8]Shreyas Subramanian, Vignesh Ganapathiraman, Corey Barrett:
Hop, skip, jump to Convergence: Dynamics of Learning Rate Transitions for Improved Training of Large Language Models. EMNLP (Findings) 2024: 16349-16362- [i2]Amrutha Varshini Ramesh, Vignesh Ganapathiraman, Issam H. Laradji, Mark Schmidt:
BlockLLM: Memory-Efficient Adaptation of LLMs by Selecting and Optimizing the Right Coordinate Blocks. CoRR abs/2406.17296 (2024) - 2023
- [c7]Vignesh Ganapathiraman, Francisco Javier Calderon, Anila Joshi:
BANDIT SAMPLING FOR FASTER NEURAL NETWORK TRAINING WITH SGD. Tiny Papers @ ICLR 2023 - [c6]Shreyas Subramanian, Vignesh Ganapathiraman, Aly El Gamal:
Learned Learning Rate Schedules for Deep Neural Network Training Using Reinforcement Learning. Tiny Papers @ ICLR 2023 - [c5]Shreyas Subramanian, Vignesh Ganapathiraman, Aly El Gamal:
Efficient Learning rate schedules for Stochastic Non-negative Matrix Factorization via Reinforcement Learning. Tiny Papers @ ICLR 2023 - 2020
- [c4]Yingyi Ma, Vignesh Ganapathiraman, Yaoliang Yu, Xinhua Zhang:
Convex Representation Learning for Generalized Invariance in Semi-Inner-Product Space. ICML 2020: 6532-6542 - [i1]Yingyi Ma, Vignesh Ganapathiraman, Yaoliang Yu, Xinhua Zhang:
Convex Representation Learning for Generalized Invariance in Semi-Inner-Product Space. CoRR abs/2004.12209 (2020)
2010 – 2019
- 2019
- [c3]Yingyi Ma, Vignesh Ganapathiraman, Xinhua Zhang:
Learning Invariant Representations with Kernel Warping. AISTATS 2019: 1003-1012 - 2018
- [c2]Vignesh Ganapathiraman, Zhan Shi, Xinhua Zhang, Yaoliang Yu:
Inductive Two-layer Modeling with Parametric Bregman Transfer. ICML 2018: 1622-1631 - 2016
- [c1]Vignesh Ganapathiraman, Xinhua Zhang, Yaoliang Yu, Junfeng Wen:
Convex Two-Layer Modeling with Latent Structure. NIPS 2016: 1280-1288
Coauthor Index
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