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Loss Functions

1162 directly classified papers

Papers per year

Papers

On Learning Text Style Transfer with Direct Rewards NAACL 2021
Towards Better Understanding of Training Certifiably Robust Models against Adversarial Examples NIPS 2021
Predicting Numerals in Natural Language Text Using a Language Model Considering the Quantitative Aspects of Numerals NAACL 2021
A Surprisingly Effective Perimeter-based Loss for Medical Image Segmentation MIDL 2021
Beyond pixel-wise supervision for segmentation: A few global shape descriptors might be surprisingly good! MIDL 2021
PML: Progressive Margin Loss for Long-Tailed Age Classification CVPR 2021
Guided Filter Regularization for Improved Disentanglement of Shape and Appearance in Diffeomorphic Autoencoders MIDL 2021
Learning Cross-Modal Retrieval With Noisy Labels CVPR 2021
Focal Frequency Loss for Image Reconstruction and Synthesis ICCV 2021
Adaptive Weighted Discriminator for Training Generative Adversarial Networks CVPR 2021
Towards Robustness of Deep Neural Networks via Regularization ICCV 2021
Spatial and Semantic Consistency Regularizations for Pedestrian Attribute Recognition ICCV 2021
Log-Likelihood-Ratio Cost Function as Objective Loss for Speaker Verification Systems INTERSPEECH 2021
Asymmetric Loss Functions for Learning with Noisy Labels ICML 2021
Improving Dialogue State Tracking with Turn-based Loss Function and Sequential Data Augmentation EMNLP 2021
One for More: Selecting Generalizable Samples for Generalizable ReID Model AAAI 2021
Adversarial Mixing Policy for Relaxing Locally Linear Constraints in Mixup EMNLP 2021
Motion Forecasting with Unlikelihood Training in Continuous Space CORL 2021
Hierarchical Modeling of Label Dependency and Label Noise in Fine-grained Entity Typing IJCAI 2021
On Biasing Transformer Attention Towards Monotonicity NAACL 2021
Searching for Robustness: Loss Learning for Noisy Classification Tasks ICCV 2021
ASAM: Adaptive Sharpness-Aware Minimization for Scale-Invariant Learning of Deep Neural Networks ICML 2021
LocalGAN: Modeling Local Distributions for Adversarial Response Generation JMLR 2021
von Mises-Fisher Loss: An Exploration of Embedding Geometries for Supervised Learning ICCV 2021
Hierarchical Class-Based Curriculum Loss IJCAI 2021