Loss Function

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Period ending 2026-09-21

7 new papers

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Period ending 2026-09-14

11 new papers

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Period ending 2026-09-07

3 new papers

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220 papers

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  1. Medical Image Segmentation based on Deep Active Contour and Mean Curvature Loss Function

    Jul 14, 2026Xiao-qiang Zhai, Zhi-feng Pang, Peng Zheng +2Medical Image SegmentationLoss Function

  2. Are we Merging the Right Models? Impact of Expert Training Duration on Model Merging for LLMs

    Jul 13, 2026Nikita Kozodoi, Zainab Afolabi, Jack ButlerContinual Model MergingModel Merging

  3. Enhanced Byzantine-Robust Federated Learning Via Truncated-Quadratic Loss for Heterogeneous Data

    Jul 13, 2026Zhi-Yong Wang, Hao Nan Sheng, Werner Stefan +3Federated LearningByzantine Attacks

  4. Echoes Across Vietnam's Highlands, Delta, and Coast: A Multilingual Corpus for Cham, Khmer, and Tay-Nung

    Jul 9, 2026Anh Trac Duc Dinh, Khang Nhat Hoang Vo, Vinh Cong Doan +2Multilingual Language ModelsLow-Resource Languages

  5. Deep Learning Method for Stationary Distribution of Reflected Brownian Motion

    Jul 9, 2026Jim Dai, Zhanhao ZhangStochastic Differential EquationsLoss Function

  6. Nonlinear Bandit

    Jul 8, 2026Tianshuo Zheng, Ting Wu, Zhi-Hua Zhou +1Generalized Linear BanditLong-Tailed Distribution

  7. UASPL: Uncertainty-Aware Self-Paced Learning with Evidential Neural Networks

    Jul 7, 2026Yifan Zhang, Yuxin Hu, Zhuobin Hao +2Uncertainty-Aware InferenceLoss Function

  8. Comparison of Loss Functions for Robust Deep Learning-based Echocardiography Segmentation when Learning with Partially Labelled Data from Multiple Domains

    Jul 6, 2026Iman Islam, Esther Puyol-Antón, Bram Ruijsink +2Whole-Heart SegmentationCardiac Motion

  9. A Structural Interpretation of GELU and Threshold-Transmission Activations via the First-Order Loss Function

    Jul 4, 2026Roberto RossiGated Recurrent UnitLoss Function

  10. Object-centric LeJEPA

    Jul 2, 2026Jakob Geusen, Ender KonukogluObject DetectionObject-Centric Learning

  11. Deep Multitask Learning for Mixed-Type Outcomes with Shared Sparsity

    Jul 1, 2026Huichao Li, Tong Wang, Sanguo Zhang +1Multi--Task LearningMulticlass Classification

  12. An automated method of identifying incorrectly labelled images based on the sequences of loss functions of deep learning networks

    Jul 1, 2026Zhipeng Zhang, Wenhui Shou, Wengting Ma +5Fundus ImagesMedical Imaging

  13. Language-Assisted Super-Resolution from Real-World Low-Resolution Patches

    Jun 30, 2026Joonkyu Park, Kyoung Mu LeeGenerative Super-ResolutionDiffusion-Based Super-Resolution Framework

  14. Fast approximation and learning of binary classification tasks in o-minimal structures using ReLU neural networks

    Jun 29, 2026Clemens Kinn, Philipp PetersenRectified Linear Unit NetworksBinary Classification

  15. Simple Supervision Is Hard to Beat: A Bitter Lesson from Sparse Target Labels in Domain-Adaptive Object Detection

    Jun 29, 2026Lijun Zhang, Ruinian Xu, Mudit AgrawalDomain AdaptationPseudo-Labeling

  16. Optimization Dynamics Imprint Semantic Specificity in Contrastive Embedding Norms

    Jun 29, 2026Ziwei Su, Junyu Ren, Victor VeitchCosine SimilarityContrastive

  17. Critical Interval MSE: Toward Reliable Offline Validation for Robot Manipulation Policies

    Jun 29, 2026Haoxu Huang, Tongsam Zheng, Yifan Chen +2Robot PoliciesMean Squared Error

  18. Smooth Scaling Laws Hide Stepwise Token Learning

    Jun 29, 2026Pingjie Wang, Zechen Hu, Peiru Yang +2Scaling LawsLarge Models

  19. Underwater Source Detection and Classification for Signal-based Surveillance: Audio Dataset Curation and Cross-Domain Evaluation

    Jun 27, 2026Quoc Thinh Vo, David K. HanUnderwater Image EnhancementPassive Acoustic Monitoring

  20. Taxonomy-aware deep learning for hierarchical marine species classification in underwater imagery

    Jun 24, 2026Dan Zimmerman, Dimitris A. Pados, George SklivanitisIn-Situ Plankton ClassifiersUnderwater Imagery

  21. EERLoss: A Novel Loss Function for Training Deep Biometric Models. A Case Study in Keystroke Dynamics

    Jun 23, 2026Nahuel Gonzalez, Marta Robledo-Moreno, Ivan DeAndres-Tame +2BiometricsLoss Function

  22. Auto-Configured Explainable Graph Neural Networks for Multi-Site Pollution Prediction

    Jun 23, 2026Abdelkader Dairi, Fouzi Harrou, Ying SunAir PollutionGraph Neural Networks

  23. Don't Go Breaking My LLM: The Impact of Pruning Attention Layers on Explanation Faithfulness and Confidence Calibration

    Jun 23, 2026Pietro Tropeano, Maria Maistro, Tuukka Ruotsalo +1Model InterpretabilityExplanation Faithfulness

  24. Action-BED: Task-Driven Bayesian Experimental Design with Singly Intractable Objectives

    Jun 22, 2026Tom Rossa, Angus Phillips, Tom RainforthBayesian Experimental DesignBayesian

  25. Polynomial Dice Loss for Medical Image Segmentation

    Jun 22, 2026Hiroaki AizawaMedical Image SegmentationLoss Function

  26. Neural Architecture Search of Sample Reweighting Networks for Complex Distribution Shift

    Jun 22, 2026Keisuke Sugawara, Kento Uchida, Shinichi ShirakawaNeural Architecture SearchDistribution Shifts

  27. A Formula-Driven Survey and Research Agenda for On-Policy Distillation

    Jun 22, 2026Bowen ZhangOn-Policy DistillationInformation Gain

  28. Target-Aware Linear Regression Under Distribution Shift

    Jun 22, 2026Zhewen Hou, Tian ZhengEstimatorsCovariate Shift

  29. Clipping the Price of Adaptivity at the Tail

    Jun 21, 2026Itai Kreisler, Yair Carmon, Oliver HinderStochastic Smooth Convex OptimizationLoss Function

  30. Customizing Video Portraits via Identity-ActionDecoupling

    Jun 21, 2026Junxiong Lin, Haoran Wang, Xinji Mai +4Text-To-Video ModelsFacial Expression Recognition

  31. Alternate loss functions and regression models that achieve robustness to outliers by modulating the learning rate

    Jun 20, 2026Mathew Mithra Noel, Arindam Banerjee, Yug D. Oswal +2OutliersLoss Function

  32. Time-Frequency Weighted Losses for Phoneme Reconstruction in DNN-Based Speech Enhancement

    Jun 19, 2026Nasser-Eddine Monir, Paul Magron, Romain SerizelSpeech EnhancementPhoneme-Level Analysis

  33. What Accuracy and Gradient Cosine Miss: Evaluating Feedback Alignment via Scale Stability, Reference Validity, and Depth Utility

    Jun 19, 2026Yuren Hao, Xiang Wan, ChengXiang ZhaiDeep NetworkLoss Function

  34. Interactive Pareto navigation for deep multi-task learning

    Jun 17, 2026Augustina C. Amakor, Konstantin Sonntag, Sebastian PeitzPareto FrontierMulti--Task Learning

  35. Smoothness-Based Derandomization of PAC-Bayes Bounds

    Jun 17, 2026Alexandre Lemire Paquin, Brahim Chaib-Draa, Philippe GiguèreGeneralization BoundsSmoothing

  36. Experimental Analysis of Neural Network-Based Image Classification on the CIFAR-10 Dataset

    Jun 17, 2026Necati Kagan Erkek, Emre Balci, Berkin HalayConvolutional Neural NetworksImage Classification

  37. A Link between Shock-wave Theory and Symmetry-reduced Stochastic Gradient Descent for Artificial Neural Networks

    Jun 16, 2026Taiki MiyagawaTwo-Layer Neural NetworksStochastic Gradient Descent

  38. Neural Bayesian Anomaly Mitigation: A Robust Loss that Doubles as an Unsupervised Contamination Classifier

    Jun 15, 2026S. A. K. Leeney, W. J. Handley, H. T. J. Bevins +1ContaminationNoisy Labels

  39. ALCL: An Adaptive Log-Correntropy Loss for Robust Learning under Non-Gaussian Noise

    Jun 14, 2026Mainak Kundu, Ria Kanjilal, Ismail UysalNoise-AwareLoss Function

  40. A Bifurcation Theory Framework for Gradient Descent on the Edge of Stability

    Jun 14, 2026Eric GanGradient DescentBifurcation

  41. Beyond Backbone Backpropagation: A Decoupled Strategy for Efficient Transfer Learning

    Jun 13, 2026Daniel Vila-Cruz, Laura Morán-Fernández, Verónica Bolón-CanedoTransfer LearningHybrid Transformer

  42. Identification and Inference for Algorithmic Frontiers with Selective Labels

    Jun 12, 2026Yiqi Liu, Francesca Molinari, Amilcar VelezSelection BiasStatistical Inference

  43. FastMix: Fast Data Mixture Optimization via Gradient Descent

    Jun 12, 2026Haoru Tan, Sitong Wu, Yanfeng Chen +5Model PretrainingMixture Models

  44. Distributional Loss for Robust Classification

    Jun 11, 2026Kathleen Anderson, Thomas MartinetzCandidate Label DistributionsLoss Function

  45. Loss-Shift Transfer via Bayes Quotients

    Jun 11, 2026Vasileios SevetlidisDistribution ShiftsLoss Function

  46. Multi-Bitwidth Quantization for LLMs Using Additive Codebooks

    Jun 11, 2026Liza Babaoglu, Shuangyi Chen, Ashish KhistiLarge Language Model QuantizationWeight-Only Quantization

  47. Physics-Aware Auxiliary Losses Improve Out-of-Distribution Generalization of a GNN Synthesizability Filter

    Jun 10, 2026Riya Bisht, Dhruv AgarwalOut-Of-DistributionGraph Neural Networks

  48. Conservation Laws from Data Symmetry in Neural Networks

    Jun 9, 2026Jakob Galley, Vahid Shahverdi, Axel FlinthEquivariant Neural NetworksSymmetry

  49. Operator learning for solving Fokker-Planck equations with various initial conditions

    Jun 8, 2026Li Zeng, Xiaoliang Wan, Yaobin Wang +2Fokker--Planck EquationStochastic Dynamics

  50. vesselFM-CT: Segmenting All Blood Vessels in CT Images for System-Level Cardiovascular Analysis

    Jun 8, 2026Bastian Wittmann, Chinmay Prabhakar, Suprosanna Shit +1Whole-Heart SegmentationVessels

  51. Improving the sharpness in neural network-based parametric post-processing of ensemble forecasts

    Jun 7, 2026Ágnes Baran, Máté MihalinaNumerical Weather PredictionPost-Processing

  52. Explaining Data Mixing Scaling Laws

    Jun 6, 2026Rui Dai, Shuran ZhengScaling LawsMixture Models

  53. LEGS: Laplacian-Enhanced Gaussian Splatting with a Nonlinear Weighted Loss

    Jun 6, 2026Yongfei Guo, Qizhou Huo, Xuan Sun +1Gaussian SplattingWireless Radiance Field

  54. 3D Oral Modelling with Improved Vertex Distribution Using Matching-Based Learning

    Jun 6, 2026Jihun Cho, Soo-Yeon Jeong, Eun-Jeong Bae +1Mobilenetv2Loss Function

  55. Entropy as a Structural Prior: How a Log-Barrier on DiT Belief Space Drives Musical Diversity and Development

    Jun 5, 2026Zixi Li, Youzhen LiLoss FunctionBarrier Functions

  56. Double Preconditioning (DoPr): Optimization for Test-Time Performance, not Validation Loss

    Jun 4, 2026Thomas T. Zhang, Alok Shah, Yifei Zhang +3Downstream Fine-TuningLoss Function

  57. Robust and sparse support vector machine via hybrid truncated loss for supervised classification

    Jun 4, 2026Yuliang Yang, Chen Chen, Yuxiang Liu +1Support Vector MachinesMulti-View

  58. ScoreStop: Gradient-based early stopping using functional score tests

    Jun 1, 2026Oliver J. Hines, Christian L. HinesEarly StoppingGradient Boosted Tree

  59. Doing well with less! On Sampling Techniques for Empirical Pairwise Loss Estimation/Minimization

    Jun 1, 2026Louise Davy, Stephan Clémençon, Charlotte LaclauLoss FunctionFlat Minima

  60. DENSER: Depth-Guided Ensemble with Staged EFA-GS Reconstruction for Soccer Novel View Synthesis

    May 31, 2026Parthsarthi RawatNovel View SynthesisMonocular Depth Estimation