On Computational Limits of Modern Hopfield Models: A Fine-Grained Complexity Analysis
Authors: Jerry Yao-Chieh Hu, Thomas Lin, Zhao Song, Han Liu
ICML 2024 | Conference PDF | Archive PDF | Plain Text | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Theoretical | We investigate the computational limits of the memory retrieval dynamics of modern Hopfield models from the fine-grained complexity analysis. Our key contribution is the characterization of a phase transition behavior... By the formal nature of this work, our results do not lead to practical implementations. |
| Researcher Affiliation | Collaboration | 1Department of Computer Science, Northwestern University, Evanston, IL, USA 2Department of Physics, National Taiwan University, Taipei, Taiwan 3Adobe Research, Seattle, WA, USA 4Department of Statistics and Data Science, Northwestern University, Evanston, IL, USA. |
| Pseudocode | Yes | Algorithm 1 The algorithm to solve AHop |
| Open Source Code | No | The paper is theoretical and explicitly states in its 'Limitation' section: 'By the formal nature of this work, our results do not lead to practical implementations.' Thus, no source code is provided. |
| Open Datasets | No | The paper is a theoretical work focusing on complexity analysis and does not involve experiments with publicly available datasets for training, validation, or testing. |
| Dataset Splits | No | The paper is a theoretical work and does not involve empirical validation with dataset splits for training, validation, or testing. |
| Hardware Specification | No | The paper is purely theoretical and does not describe any experiments that would require hardware specifications. |
| Software Dependencies | No | The paper is theoretical and does not detail any software dependencies or versions required for replicating experiments. |
| Experiment Setup | No | The paper is a theoretical work focusing on complexity analysis and does not describe any experimental setup details such as hyperparameters or training configurations. |