On the second-order optimization for spiking neural networks
cs.LG, cs.CV
Submitted: 2026-09-24
Updated: 2026-09-24
Terminology
Sources
- A2SG:Adaptive and Asymmetric Surrogate Gradients for Training Deep Spiking Neural Networks
- Temporal Efficient Training of Spiking Neural Network via Gradient Re-weighting
- Linearized Bregman Iterations for Sparse Spiking Neural Networks
- The Geometry of Updates: Fisher Alignment at Vocabulary Scale
- Adam: A Method for Stochastic Optimization
- Decoupled Weight Decay Regularization
- Fashion-MNIST: a Novel Image Dataset for Benchmarking Machine Learning Algorithms
- Very Deep Convolutional Networks for Large-Scale Image Recognition
Related papers
- Polynomial-Augmented Neural Networks (PANNs) with Weak Orthogonality Constraints for Enhanced Function and PDE Approximation
- AIRL-S: Unifying Reinforcement Learning and Search-Based Test-Time Scaling via Adversarial Inverse Reinforcement Learning
- Transformers as Bayesian In-Context Experimenters: Smoothness-Adaptive Efficient ATE Estimation
- Convergence issues in Relational Concept Analysis based on AOC-posets
- Beliefs Beyond Posteriors: Local-Consistency Optimisation for Bayesian Neural Networks
- Understanding Diffusion Models via Ratio-Based Function Approximation with SignReLU Networks