Research map / Architectures and efficiency / RNNs and normalization
Learning with Auxiliary Activation for Memory-Efficient Training
Read the paperCheck your idea against 108,967 papers
AI-extracted summary. Written by AI from the paper's title only (no summary yet). Numbers and claims can be wrong or missing context, so check the paper before you cite or build on it.
Closest papers by meaning
- Reducing Fine-Tuning Memory Overhead by Approximate and Memory-Sharing Backpropagation (ICML 2024 · similarity 0.88)
- Backprop with Approximate Activations for Memory-efficient Network Training (NeurIPS 2019 · similarity 0.88)
- INSTANT: Compressing Gradients and Activations for Resource-Efficient Training (ICLR 2026 · similarity 0.86)
- Accelerated training through iterative gradient propagation along the residual path (ICLR 2025 · similarity 0.85)
- Aux-NAS: Exploiting Auxiliary Labels with Negligibly Extra Inference Cost (ICLR 2024 · similarity 0.84)
- Better NTK Conditioning: A Free Lunch from (ReLU) Nonlinear Activation in Wide Neural Networks (NeurIPS 2025 · similarity 0.84)
Writing a paper in this area? scime draft is a free LaTeX editor with AI included, real-time co-authors and a check of your references and venue rules before you submit. It also imports OpenAI Prism projects.
