Unsupervised Knowledge Transfer Using Similarity Embeddings
Explore this paper's citation graph
- Type
- article
- Published
- 2019-03-01
- Cited by
- 32
- References
- 21
- Access
- Open access
- OpenAlex
- https://openalex.org/W30047908
- Semantic Scholar
- https://api.semanticscholar.org/CorpusID:51721116
Keywords
Crossbreed, Animal science, Body weight, Pennisetum, Veterinary medicine
References
- Scene Recognition by Manifold Regularized Deep Learning Architecture
- Deep Transfer Network: Unsupervised Domain Adaptation
- Recurrent neural network training with dark knowledge transfer
- Distilling the Knowledge in a Neural Network
- Deep transfer metric learning
- Knowledge Transfer Pre-training
- Learning Deep and Wide: A Spectral Method for Learning Deep Networks
- Annotated Facial Landmarks in the Wild: A large-scale, real-world database for facial landmark localization
- Weakly-Shared Deep Transfer Networks for Heterogeneous-Domain Knowledge Propagation
- Dropout: a simple way to prevent neural networks from overfitting
- Gradient-based learning applied to document recognition
- ImageNet classification with deep convolutional neural networks
- Deep transfer via second-order Markov logic
- Net2Net: Accelerating Learning via Knowledge Transfer
- Deep Residual Learning for Image Recognition
- SqueezeNet: AlexNet-level accuracy with 50x fewer parameters and <1MB model size
- Model compression
- Simultaneous Deep Transfer Across Domains and Tasks
- Transferring knowledge from a RNN to a DNN
- Adam: A Method for Stochastic Optimization
Cited by
- Open Set Domain Adaptation: Theoretical Bound and Algorithm
- Curriculum-based Teacher Ensemble for Robust Neural Network Distillation
- Ternary Compression for Communication-Efficient Federated Learning
- Tridirectional Transfer Learning for Predicting Gastric Cancer Morbidity
- CAME: Content- and Context-Aware Music Embedding for Recommendation
- Heterogeneous Knowledge Distillation Using Information Flow Modeling
- Probabilistic Knowledge Transfer for Lightweight Deep Representation Learning
- A Novel Deep Forest-Based Active Transfer Learning Method for PolSAR Images
- Delving Deep Into Label Smoothing
- Improving knowledge distillation using unified ensembles of specialized teachers
- Online Subclass Knowledge Distillation
- Preparing Lessons: Improve Knowledge Distillation with Better Supervision
- Learning to learn by yourself: Unsupervised meta‐learning with self‐knowledge distillation for COVID‐19 diagnosis from pneumonia cases
- Efficient Online Subclass Knowledge Distillation for Image Classification
- Elastic Knowledge Distillation by Learning From Recollection
- Open Set Domain Adaptation via Joint Alignment and Category Separation
- Probabilistic online self-distillation
- Collaborative Knowledge Distillation via Multiknowledge Transfer
- Efficient Asynchronous Federated Learning Research in the Internet of Vehicles
- Bias-Based Soft Label Learning for Facial Expression Recognition
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