Loss Functions

Generalized Entropy Regularization or: There’s Nothing Special about Label Smoothing ACL 2020 Generalized Focal Loss: Learning Qualified and Distributed Bounding Boxes for Dense Object Detection NeurIPS 2020 GRACE: Gradient Harmonized and Cascaded Labeling for Aspect-based Sentiment Analysis EMNLP 2020 HAL: Improved Text-Image Matching by Mitigating Visual Semantic Hubs AAAI 2020 How Distance Transform Maps Boost Segmentation CNNs: An Empirical Study MIDL 2020 How Ordinal Are Your Data? Interspeech 2020 Implicit Geometric Regularization for Learning Shapes ICML 2020 Improved Natural Language Generation via Loss Truncation ACL 2020 Improving model calibration with accuracy versus uncertainty optimization NeurIPS 2020 Individual Calibration with Randomized Forecasting ICML 2020 Integrating Relation Constraints with Neural Relation Extractors AAAI 2020 Interactive Multi-Label CNN Learning With Partial Labels CVPR 2020 Knowledge-Based Regularization in Generative Modeling IJCAI 2020 Learning a Unified Sample Weighting Network for Object Detection CVPR 2020 Learning by Minimizing the Sum of Ranked Range NeurIPS 2020 Learning Interpretable Models using Soft Integrity Constraints ACML 2020 Learning with Fenchel-Young losses JMLR 2020 Learn with Noisy Data via Unsupervised Loss Correction for Weakly Supervised Reading Comprehension COLING 2020 Light Field Spatial Super-Resolution via Deep Combinatorial Geometry Embedding and Structural Consistency Regularization CVPR 2020 Loss Function Search for Face Recognition ICML 2020 Minimax Classification with 0-1 Loss and Performance Guarantees NeurIPS 2020 Moving in the Right Direction: A Regularization for Deep Metric Learning CVPR 2020 Munchausen Reinforcement Learning NeurIPS 2020 NAAGN: Noise-Aware Attention-Gated Network for Speech Enhancement Interspeech 2020 Naturalness Enhancement with Linguistic Information in End-to-End TTS Using Unsupervised Parallel Encoding Interspeech 2020