LDAdam: Adaptive optimization from low-dimensional gradient statistics
Robert T, Safaryan M, Modoranu I-V, Alistarh D-A. 2025. LDAdam: Adaptive optimization from low-dimensional gradient statistics. 13th International Conference on Learning Representations. ICLR: International Conference on Learning Representations, 101877–101913.
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Abstract
We introduce LDAdam, a memory-efficient optimizer for training large models, that performs adaptive optimization steps within lower dimensional subspaces, while consistently exploring the full parameter space during training. This strategy keeps the optimizer's memory footprint to a fraction of the model size. LDAdam relies on a new projection-aware update rule for the optimizer states that allows for transitioning between subspaces, i.e., estimation of the statistics of the projected gradients. To mitigate the errors due to low-rank projection, LDAdam integrates a new generalized error feedback mechanism, which explicitly accounts for both gradient and optimizer state compression. We prove the convergence of LDAdam under standard assumptions, and provide empirical evidence that LDAdam allows for efficient fine-tuning and pre-training of language models.
Publishing Year
Date Published
2025-04-01
Proceedings Title
13th International Conference on Learning Representations
Publisher
ICLR
Page
101877-101913
Conference
ICLR: International Conference on Learning Representations
Conference Location
Singapore, Singapore
Conference Date
2025-04-24 – 2025-04-28
ISBN
IST-REx-ID
Cite this
Robert T, Safaryan M, Modoranu I-V, Alistarh D-A. LDAdam: Adaptive optimization from low-dimensional gradient statistics. In: 13th International Conference on Learning Representations. ICLR; 2025:101877-101913.
Robert, T., Safaryan, M., Modoranu, I.-V., & Alistarh, D.-A. (2025). LDAdam: Adaptive optimization from low-dimensional gradient statistics. In 13th International Conference on Learning Representations (pp. 101877–101913). Singapore, Singapore: ICLR.
Robert, Thomas, Mher Safaryan, Ionut-Vlad Modoranu, and Dan-Adrian Alistarh. “LDAdam: Adaptive Optimization from Low-Dimensional Gradient Statistics.” In 13th International Conference on Learning Representations, 101877–913. ICLR, 2025.
T. Robert, M. Safaryan, I.-V. Modoranu, and D.-A. Alistarh, “LDAdam: Adaptive optimization from low-dimensional gradient statistics,” in 13th International Conference on Learning Representations, Singapore, Singapore, 2025, pp. 101877–101913.
Robert T, Safaryan M, Modoranu I-V, Alistarh D-A. 2025. LDAdam: Adaptive optimization from low-dimensional gradient statistics. 13th International Conference on Learning Representations. ICLR: International Conference on Learning Representations, 101877–101913.
Robert, Thomas, et al. “LDAdam: Adaptive Optimization from Low-Dimensional Gradient Statistics.” 13th International Conference on Learning Representations, ICLR, 2025, pp. 101877–913.
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