Computer Science, Computer Vision and Pattern Recognition
Tag: pruning
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Computation and Language, Computer Science
Pruning vs. Model Compression: Evaluating Adversarial Robustness in Deep Learning Models
Computer Science, Computer Vision and Pattern Recognition
Efficient Vision Transformers with Width & Depth Pruning for Resource-Constrained Devices
Mathematics, Optimization and Control
Computational Trade-Offs of OBBT in ReLU Networks
Computation and Language, Computer Science
Pruning Language Models: Mitigating Performance Degradation with Bias Compensation
Computer Science, Machine Learning
Efficient Elicitation of Aggregated Rankings Under Kemeny’s Rule
Computer Science, Machine Learning
Data-Dependent Sample Complexity of Deep Neural Networks via Lipschitz Augmentation
Computer Science, Machine Learning
Exploring the Robustness of Deep Neural Networks: A Review of Methods and Applications
Computer Science, Machine Learning
Efficient Fairness-Aware Compression of Deep Neural Networks
Computer Science, Machine Learning
Low-Rank Neural Networks for Continual Learning
Computer Science, Computer Vision and Pattern Recognition
Improving 3D Reconstruction via Global Context Capture and Graph Attention
Computer Science, Machine Learning
Learning Robust Constraints for Autonomous Agents
Computer Science, Computer Vision and Pattern Recognition
Supported by Multiple Organizations: Acknowledging Valuable Contributions to the Article
Computer Science, Computer Vision and Pattern Recognition
Efficient and Accurate Conversion of Artificial Neural Networks to Spiking Neural Networks
Computer Science, Machine Learning
Pruning Deep Neural Networks for Efficient Inference and Training
Computer Science, Computer Vision and Pattern Recognition
Pruning Neural Networks: A Comprehensive Review and Future Directions
Computer Science, Machine Learning
Pruning Neural Networks Without Compromising Performance
Computer Science, Machine Learning
Pruning Methods for Neural Networks: A Comparative Analysis
Computation and Language, Computer Science
Pruning Massive Language Models for Accurate and Efficient Natural Language Processing
Computer Science, Computer Vision and Pattern Recognition