Search Results for author:
Found 7 papers, 3 papers with code
SymBa: Symmetric Backpropagation-Free Contrastive Learning with Forward-Forward Algorithm for Optimizing Convergence
The paper proposes a new algorithm called SymBa that aims to achieve more biologically plausible learning than Back-Propagation (BP).
X-ViT: High Performance Linear Vision Transformer without Softmax
Vision transformers have become one of the most important models for computer vision tasks.
Proxyless Neural Architecture Adaptation for Supervised Learning and Self-Supervised Learning
Recently, Neural Architecture Search (NAS) methods have been introduced and show impressive performance on many benchmarks.
SmoothMix: Training Confidence-calibrated Smoothed Classifiers for Certified Robustness
Randomized smoothing is currently a state-of-the-art method to construct a certifiably robust classifier from neural networks against $\ell_2$-adversarial perturbations.
SmoothMix: Training Confidence-calibrated Smoothed Classifiers for Certified Adversarial Robustness
Randomized smoothing is currently a state-of-the-art method to construct a certifiably robust classifier from neural networks against $\ell_2$-adversarial perturbations.
Differentiable Neural Architecture Transformation for Reproducible Architecture Improvement
Recently, Neural Architecture Search (NAS) methods are introduced and show impressive performance on many benchmarks.
Efficient Decoupled Neural Architecture Search by Structure and Operation Sampling
We propose a novel neural architecture search algorithm via reinforcement learning by decoupling structure and operation search processes.
