Optimization & Theory

Time-aware Large Kernel Convolutions ICML 2020 TinyLSTMs: Efficient Neural Speech Enhancement for Hearing Aids Interspeech 2020 TinyTL: Reduce Memory, Not Parameters for Efficient On-Device Learning NeurIPS 2020 TKD: Temporal Knowledge Distillation for Active Perception WACV 2020 Token-level Adaptive Training for Neural Machine Translation EMNLP 2020 TomoFluid: Reconstructing Dynamic Fluid From Sparse View Videos CVPR 2020 TopicBERT for Energy Efficient Document Classification EMNLP 2020 Towards Accurate Low Bit-Width Quantization with Multiple Phase Adaptations AAAI 2020 Towards Certificated Model Robustness Against Weight Perturbations AAAI 2020 Towards Efficient Model Compression via Learned Global Ranking CVPR 2020 Towards Fully 8-bit Integer Inference for the Transformer Model IJCAI 2020 Towards Holistic and Automatic Evaluation of Open-Domain Dialogue Generation ACL 2020 Towards Interpretable Semantic Segmentation via Gradient-Weighted Class Activation Mapping (Student Abstract) AAAI 2020 Towards Unified INT8 Training for Convolutional Neural Network CVPR 2020 Towards Verifying Robustness of Neural Networks Against A Family of Semantic Perturbations CVPR 2020 Training Binary Neural Networks through Learning with Noisy Supervision ICML 2020 Training Binary Neural Networks using the Bayesian Learning Rule ICML 2020 Training Decision Trees as Replacement for Convolution Layers AAAI 2020 Training Deep Energy-Based Models with f-Divergence Minimization ICML 2020 Training Flexible Depth Model by Multi-Task Learning for Neural Machine Translation EMNLP 2020 Training Quantized Neural Networks With a Full-Precision Auxiliary Module CVPR 2020 Training-Time-Friendly Network for Real-Time Object Detection AAAI 2020 Transferring Optimality Across Data Distributions via Homotopy Methods ICLR 2020 Transformation of ReLU-based recurrent neural networks from discrete-time to continuous-time ICML 2020 TRENDNERT: A Benchmark for Trend and Downtrend Detection in a Scientific Domain AAAI 2020