Loss Functions
1,220 papers
Papers per year
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Papers
Boundary loss for highly unbalanced segmentation
MIDL 2019
Bounding Box Regression With Uncertainty for Accurate Object Detection
CVPR 2019
Calibrating DNN Posterior Probability Estimates of HMM/DNN Models to Improve Social Signal Detection from Audio Data
Interspeech 2019
CAN: Constrained Attention Networks for Multi-Aspect Sentiment Analysis
EMNLP 2019
CFSNet: Toward a Controllable Feature Space for Image Restoration
ICCV 2019
Class-Balanced Loss Based on Effective Number of Samples
CVPR 2019
Classification with Label Distribution Learning
IJCAI 2019
Clickbait? Sensational Headline Generation with Auto-tuned Reinforcement Learning
EMNLP 2019
Complement Objective Training
ICLR 2019
Conservative Wasserstein Training for Pose Estimation
ICCV 2019
Continual Learning by Asymmetric Loss Approximation With Single-Side Overestimation
ICCV 2019
COP: Customized Deep Model Compression via Regularized Correlation-Based Filter-Level Pruning
IJCAI 2019
Cost-sensitive Regularization for Label Confusion-aware Event Detection
ACL 2019
Countdown Regression: Sharp and Calibrated Survival Predictions
UAI 2019
Countering the Effects of Lead Bias in News Summarization via Multi-Stage Training and Auxiliary Losses
EMNLP 2019
Deep Reinforcement Learning with Distributional Semantic Rewards for Abstractive Summarization
EMNLP 2019
Deep Single Image Camera Calibration With Radial Distortion
CVPR 2019
Deep Speaker Embedding Extraction with Channel-Wise Feature Responses and Additive Supervision Softmax Loss Function
Interspeech 2019
Describing Like Humans: On Diversity in Image Captioning
CVPR 2019
Diagnosing and Enhancing VAE Models
ICLR 2019
Differentiated Distribution Recovery for Neural Text Generation
AAAI 2019
Dropout as a Structured Shrinkage Prior
ICML 2019
DTeam @ VarDial 2019: Ensemble based on skip-gram and triplet loss neural networks for Moldavian vs. Romanian cross-dialect topic identification
NAACL 2019
EASSE: Easier Automatic Sentence Simplification Evaluation
EMNLP 2019
End-to-End Losses Based on Speaker Basis Vectors and All-Speaker Hard Negative Mining for Speaker Verification
Interspeech 2019