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← Optimization & Theory
Deep Learning
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Optimization & Theory
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Loss Functions
122 directly classified papers
Papers per year
2012: 1
2016: 1
2017: 3
2018: 7
2019: 15
2020: 20
2021: 18
2022: 18
2023: 11
2024: 16
2025: 12
Papers
A Symmetric Relative-Error Loss Function for Intermittent Multiscale Signal Modelling
IJCAI 2025
A Unified Loss for Handling Inter-Class and Intra-Class Imbalance in Medical Image Segmentation
AAAI 2025
Feature Clipping for Uncertainty Calibration
AAAI 2025
Logit Space Constrained Fine-Tuning for Mitigating Hallucinations in LLM-Based Recommender Systems
EMNLP 2025
Parametric ρ-Norm Scaling Calibration
AAAI 2025
Debiased All-in-one Image Restoration with Task Uncertainty Regularization
AAAI 2025
Improving Accuracy and Calibration via Differentiated Deep Mutual Learning
CVPR 2025
Auto-Encoded Supervision for Perceptual Image Super-Resolution
CVPR 2025
Training Deep Neural Networks with Virtual Smoothing Classes
AAAI 2025
GT-Mean Loss: A Simple Yet Effective Solution for Brightness Mismatch in Low-Light Image Enhancement
ICCV 2025
Fossils at SemEval-2025 Task 9: Tasting Loss Functions for Food Hazard Detection in Text Reports
ACL 2025
WaveLoss: An Adaptive Dynamic Loss for Deep Gait Recognition
AAAI 2025
On the Importance of Large Objects in CNN Based Object Detection Algorithms
WACV 2024
CR-SAM: Curvature Regularized Sharpness-Aware Minimization
AAAI 2024
$\epsilon$-Softmax: Approximating One-Hot Vectors for Mitigating Label Noise
NIPS 2024
Enhancing Language Model Factuality via Activation-Based Confidence Calibration and Guided Decoding
EMNLP 2024
Learning with Fitzpatrick Losses
NIPS 2024
MaxEnt Loss: Constrained Maximum Entropy for Calibration under Out-of-Distribution Shift
AAAI 2024
Controlled Text Generation for Large Language Model with Dynamic Attribute Graphs
ACL 2024
Towards Calibrated Multi-label Deep Neural Networks
CVPR 2024
A Computation-Aware Shape Loss Function for Point Cloud Completion
AAAI 2024
Batch Normalization Is Blind to the First and Second Derivatives of the Loss
AAAI 2024
Moderate Message Passing Improves Calibration: A Universal Way to Mitigate Confidence Bias in Graph Neural Networks
AAAI 2024
Misalignment-Robust Frequency Distribution Loss for Image Transformation
CVPR 2024
Decoupled Kullback-Leibler Divergence Loss
NIPS 2024
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