| Efficient One Pass Self-distillation with Zipf’s Label Smoothing
|
2022 |
Liang, Jiajun |
| Deep Partial Updating: Towards Communication Efficient Updating for On-Device Inference
|
2022 |
Qu, Zhongnan |
| L3: Accelerator-Friendly Lossless Image Format for High-Resolution, High-Throughput DNN Training
|
2022 |
Bae, Jonghyun |
| Mixed-Precision Neural Network Quantization via Learned Layer-Wise Importance
|
2022 |
Tang, Chen |
| Equivariance and Invariance Inductive Bias for Learning from Insufficient Data
|
2022 |
Wad, Tan |
| Event Neural Networks
|
2022 |
Dutson, Matthew |
| IDa-Det: An Information Discrepancy-Aware Distillation for 1-Bit Detectors
|
2022 |
Xu, Sheng |
| Disentangled Differentiable Network Pruning
|
2022 |
Gao, Shangqian |
| Adaptive Token Sampling for Efficient Vision Transformers
|
2022 |
Fayyaz, Mohsen |
| Multi-granularity Pruning for Model Acceleration on Mobile Devices
|
2022 |
Zhao, Tianli |
| Helpful or Harmful: Inter-task Association in Continual Learning
|
2022 |
Jin, Hyundong |
| Soft Masking for Cost-Constrained Channel Pruning
|
2022 |
Humble, Ryan |
| Towards Ultra Low Latency Spiking Neural Networks for Vision and Sequential Tasks Using Temporal Pruning
|
2022 |
Chowdhury, Sayeed Shafayet |
| Masked Generative Distillation
|
2022 |
Yang, Zhendong |
| Prune Your Model Before Distill It
|
2022 |
Park, Jinhyuk |
| Fine-grained Data Distribution Alignment for Post-Training Quantization
|
2022 |
Zhong, Yunshan |
| SP-Net: Slowly Progressing Dynamic Inference Networks
|
2022 |
Wang, Huanyu |
| EdgeViTs: Competing Light-Weight CNNs on Mobile Devices with Vision Transformers
|
2022 |
Pan, Junting |
| PalQuant: Accelerating High-Precision Networks on Low-Precision Accelerators
|
2022 |
Hu, Qinghao |
| AdaBin: Improving Binary Neural Networks with Adaptive Binary Sets
|
2022 |
Tu, Zhijun |
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