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← Optimization & Theory
Machine Learning
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Optimization & Theory
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Loss Functions
1162 directly classified papers
Papers per year
2004: 1
2005: 1
2006: 3
2007: 4
2008: 3
2009: 5
2010: 7
2011: 11
2012: 11
2013: 8
2014: 15
2015: 18
2016: 16
2017: 30
2018: 57
2019: 124
2020: 120
2021: 165
2022: 140
2023: 174
2024: 111
2025: 106
2026: 32
Papers
Improving Accuracy and Calibration via Differentiated Deep Mutual Learning
CVPR 2025
Stop Learning it all to Mitigate Visual Hallucination, Focus on the Hallucination Target.
CVPR 2025
Group-Aware Reinforcement Learning for Output Diversity in Large Language Models
EMNLP 2025
Calibrating Verbal Uncertainty as a Linear Feature to Reduce Hallucinations
EMNLP 2025
Heatmap Regression without Soft-Argmax for Facial Landmark Detection
ICCV 2025
Randomization Can Reduce Both Bias and Variance: A Case Study in Random Forests
JMLR 2025
Structural Entropy Guided Probabilistic Coding
AAAI 2025
Loss Functions for Predictor-based Neural Architecture Search
ICCV 2025
Attack-inspired Calibration Loss for Calibrating Crack Recognition
AAAI 2025
Are Ensembles Getting Better All the Time?
JMLR 2025
Enhancing Noise-Robust Losses for Large-Scale Noisy Data Learning
AAAI 2025
Real-World Summarization: When Evaluation Reaches Its Limits
EMNLP 2025
A Unified Loss for Handling Inter-Class and Intra-Class Imbalance in Medical Image Segmentation
AAAI 2025
Debiased All-in-one Image Restoration with Task Uncertainty Regularization
AAAI 2025
Proper losses regret at least 1/2-order
JMLR 2025
PossLoss: A Reliable and Sensitive Facial Landmark Detection Loss Function
ICCV 2025
SLACE: A Monotone and Balance-Sensitive Loss Function for Ordinal Regression
AAAI 2025
Revisiting Interpolation for Noisy Label Correction
AAAI 2025
Feature Clipping for Uncertainty Calibration
AAAI 2025
Balanced Sharpness-Aware Minimization for Imbalanced Regression
ICCV 2025
CARMA: Enhanced Compositionality in LLMs via Advanced Regularisation and Mutual Information Alignment
EMNLP 2025
NITK-VITAL at SemEval-2025 Task 11: Focal-RoBERTa: Addressing Class Imbalance in Multi-Label Emotion Classification
ACL 2025
YNU-HPCC at SemEval-2025 Task 10: A Two-Stage Approach to Solving Multi-Label and Multi-Class Role Classification Based on DeBERTa
ACL 2025
R-VLM: Region-Aware Vision Language Model for Precise GUI Grounding
ACL 2025
Dynamic Pseudo Labeling via Gradient Cutting for High-Low Entropy Exploration
CVPR 2025
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