A Gift from Knowledge Distillation: Fast Optimization, Network Minimization and Transfer Learning
Junho Yim low, Donggyu Joo, Ji‐Hoon Bae, Junmo Kim
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- AutoML: A survey of the state-of-the-art→A Gift from Knowledge Distillation: Fast Optimization, Network Minimization and Transfer …Legacy edge — source detail unavailable
- Relational Knowledge Distillation→A Gift from Knowledge Distillation: Fast Optimization, Network Minimization and Transfer …Legacy edge — source detail unavailable
- A Gift from Knowledge Distillation: Fast Optimization, Network Minimization and Transfer …→Adam: A Method for Stochastic OptimizationLegacy edge — source detail unavailable
- A Gift from Knowledge Distillation: Fast Optimization, Network Minimization and Transfer …→[No title in the source record — DROPS (Schloss Dagstuhl – Leibniz Center for Informatics…Legacy edge — source detail unavailable
- A Gift from Knowledge Distillation: Fast Optimization, Network Minimization and Transfer …→Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Sh…Legacy edge — source detail unavailable
- A Gift from Knowledge Distillation: Fast Optimization, Network Minimization and Transfer …→Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Sh…Legacy edge — source detail unavailable
- A Gift from Knowledge Distillation: Fast Optimization, Network Minimization and Transfer …→Distilling the Knowledge in a Neural NetworkLegacy edge — source detail unavailable
- A Gift from Knowledge Distillation: Fast Optimization, Network Minimization and Transfer …→Understanding the difficulty of training deep feedforward neural networksLegacy edge — source detail unavailable
- A Gift from Knowledge Distillation: Fast Optimization, Network Minimization and Transfer …→Adaptive Subgradient Methods for Online Learning and Stochastic OptimizationLegacy edge — source detail unavailable
- A Gift from Knowledge Distillation: Fast Optimization, Network Minimization and Transfer …→ADADELTA: An Adaptive Learning Rate MethodLegacy edge — source detail unavailable
- A Gift from Knowledge Distillation: Fast Optimization, Network Minimization and Transfer …→Why Does Unsupervised Pre-training Help Deep Learning?Legacy edge — source detail unavailable
- Adam: A Method for Stochastic Optimization→Adaptive Subgradient Methods for Online Learning and Stochastic OptimizationLegacy edge — source detail unavailable
- Adam: A Method for Stochastic Optimization→ADADELTA: An Adaptive Learning Rate MethodLegacy edge — source detail unavailable
- Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Sh…→Understanding the difficulty of training deep feedforward neural networksLegacy edge — source detail unavailable
- Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Sh…→Adaptive Subgradient Methods for Online Learning and Stochastic OptimizationLegacy edge — source detail unavailable
- Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Sh…→Adaptive Subgradient Methods for Online Learning and Stochastic OptimizationLegacy edge — source detail unavailable
- Relational Knowledge Distillation→Distilling the Knowledge in a Neural NetworkLegacy edge — source detail unavailable
- AutoML: A survey of the state-of-the-art→Adam: A Method for Stochastic OptimizationLegacy edge — source detail unavailable
- AutoML: A survey of the state-of-the-art→Distilling the Knowledge in a Neural NetworkLegacy edge — source detail unavailable
- AutoML: A survey of the state-of-the-art→[No title in the source record — DROPS (Schloss Dagstuhl – Leibniz Center for Informatics…Legacy edge — source detail unavailable
What this paper cites, inside the corpus
What cites it, inside the corpus
| Paper | Year | Cited |
|---|---|---|
| AutoML: A survey of the state-of-the-art | 2020 | 1,705 |
| Relational Knowledge Distillation | 2019 | 1,669 |
Links
Topics
| Domain Adaptation and Few-Shot Learning | Computer Science |
| Advanced Neural Network Applications | Computer Science |
| Adversarial Robustness in Machine Learning | Computer Science |
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