{"total":107,"rows":[{"id":"2105.02375","title":"A Geometric Analysis of Neural Collapse with Unconstrained Features","created":"2021-05-06","cited_by_count":227,"area":null},{"id":"2110.10832","title":"Ensemble of Averages: Improving Model Selection and Boosting Performance in Domain Generalization","created":"2021-10-21","cited_by_count":144,"area":null},{"id":"2210.06313","title":"The Lazy Neuron Phenomenon: On Emergence of Activation Sparsity in Transformers","created":"2022-10-12","cited_by_count":122,"area":null},{"id":"2102.00650","title":"Rethinking Soft Labels for Knowledge Distillation: A Bias-Variance Tradeoff Perspective","created":"2021-02-01","cited_by_count":119,"area":"distill"},{"id":"2203.01238","title":"On the Optimization Landscape of Neural Collapse under MSE Loss: Global Optimality with Unconstrained Features","created":"2022-03-02","cited_by_count":97,"area":null},{"id":"2202.14026","title":"Robust Training under Label Noise by Over-parameterization","created":"2022-02-28","cited_by_count":93,"area":null},{"id":"2310.18689","title":"Foundational Models in Medical Imaging: A Comprehensive Survey and Future Vision","created":"2023-10-28","cited_by_count":76,"area":null},{"id":"2301.03962","title":"A Unified Theory of Diversity in Ensemble Learning","created":"2023-01-10","cited_by_count":71,"area":null},{"id":"2106.04149","title":"To Smooth or Not? When Label Smoothing Meets Noisy Labels","created":"2021-06-08","cited_by_count":70,"area":null},{"id":"2109.02355","title":"A Farewell to the Bias-Variance Tradeoff? An Overview of the Theory of Overparameterized Machine Learning","created":"2021-09-06","cited_by_count":57,"area":null},{"id":"2203.08124","title":"Can Neural Nets Learn the Same Model Twice? Investigating Reproducibility and Double Descent from the Decision Boundary Perspective","created":"2022-03-15","cited_by_count":57,"area":null},{"id":"2203.04913","title":"Leveling Down in Computer Vision: Pareto Inefficiencies in Fair Deep Classifiers","created":"2022-03-09","cited_by_count":53,"area":null},{"id":"2207.04630","title":"On the Principles of Parsimony and Self-Consistency for the Emergence of Intelligence","created":"2022-07-11","cited_by_count":50,"area":"lr"},{"id":"2112.06074","title":"Early Stopping for Deep Image Prior","created":"2021-12-11","cited_by_count":44,"area":null},{"id":"2107.11228","title":"Taxonomizing local versus global structure in neural network loss landscapes","created":"2021-07-23","cited_by_count":34,"area":null},{"id":"2110.03128","title":"On the Generalization of Models Trained with SGD: Information-Theoretic Bounds and Implications","created":"2021-10-07","cited_by_count":31,"area":null},{"id":"2206.08684","title":"Sparse Double Descent: Where Network Pruning Aggravates Overfitting","created":"2022-06-17","cited_by_count":26,"area":null},{"id":"2112.03215","title":"Multi-scale Feature Learning Dynamics: Insights for Double Descent","created":"2021-12-06","cited_by_count":24,"area":null},{"id":"2103.10919","title":"Robustness via Cross-Domain Ensembles","created":"2021-03-19","cited_by_count":23,"area":null},{"id":"2210.12256","title":"Uncertainty Estimates of Predictions via a General Bias-Variance Decomposition","created":"2022-10-21","cited_by_count":20,"area":null},{"id":"2108.11489","title":"The Interplay Between Implicit Bias and Benign Overfitting in Two-Layer Linear Networks","created":"2021-08-25","cited_by_count":18,"area":null},{"id":"2209.08615","title":"Membership Inference Attacks and Generalization: A Causal Perspective","created":"2022-09-18","cited_by_count":17,"area":"safety"},{"id":"2105.06791","title":"Agree to Disagree: When Deep Learning Models With Identical Architectures Produce Distinct Explanations","created":"2021-05-14","cited_by_count":15,"area":null},{"id":"2110.03135","title":"Label Noise in Adversarial Training: A Novel Perspective to Study Robust Overfitting","created":"2021-10-07","cited_by_count":14,"area":null},{"id":"2103.04554","title":"Exact Gap between Generalization Error and Uniform Convergence in Random Feature Models","created":"2021-03-08","cited_by_count":13,"area":null},{"id":"2302.01576","title":"ResMem: Learn what you can and memorize the rest","created":"2023-02-03","cited_by_count":13,"area":null},{"id":"2303.01475","title":"Over-training with Mixup May Hurt Generalization","created":"2023-03-02","cited_by_count":13,"area":null},{"id":"2310.18765","title":"Rethinking Semi-Supervised Imbalanced Node Classification from Bias-Variance Decomposition","created":"2023-10-28","cited_by_count":13,"area":null},{"id":"2110.05481","title":"Which Samples Should be Learned First: Easy or Hard?","created":"2021-10-11","cited_by_count":12,"area":null},{"id":"2502.05075","title":"Discrepancies are Virtue: Weak-to-Strong Generalization through Lens of Intrinsic Dimension","created":"2025-02-07","cited_by_count":12,"area":null},{"id":"2202.04167","title":"Understanding the bias-variance tradeoff of Bregman divergences","created":"2022-02-08","cited_by_count":11,"area":null},{"id":"2204.05023","title":"Machine Learning and Deep Learning -- A review for Ecologists","created":"2022-04-11","cited_by_count":11,"area":null},{"id":"2103.09947","title":"Understanding Generalization in Adversarial Training via the Bias-Variance Decomposition","created":"2021-03-17","cited_by_count":10,"area":null},{"id":"2307.14239","title":"Revisiting the Performance-Explainability Trade-Off in Explainable Artificial Intelligence (XAI)","created":"2023-07-26","cited_by_count":10,"area":null},{"id":"2601.23045","title":"The Hot Mess of AI: How Does Misalignment Scale With Model Intelligence and Task Complexity?","created":"2026-01-30","cited_by_count":10,"area":null},{"id":"2106.03485","title":"Redundant representations help generalization in wide neural networks","created":"2021-06-07","cited_by_count":9,"area":null},{"id":"2112.15131","title":"Resource-Efficient Deep Learning: A Survey on Model-, Arithmetic-, and Implementation-Level Techniques","created":"2021-12-30","cited_by_count":9,"area":null},{"id":"2206.01378","title":"Regularization-wise double descent: Why it occurs and how to eliminate it","created":"2022-06-03","cited_by_count":9,"area":null},{"id":"2212.00261","title":"Task Discovery: Finding the Tasks that Neural Networks Generalize on","created":"2022-12-01","cited_by_count":9,"area":null},{"id":"2301.04850","title":"Understanding Difficulty-based Sample Weighting with a Universal Difficulty Measure","created":"2023-01-12","cited_by_count":9,"area":null},{"id":"2403.09101","title":"Soften to Defend: Towards Adversarial Robustness via Self-Guided Label Refinement","created":"2024-03-14","cited_by_count":9,"area":null},{"id":"2201.11440","title":"An Analysis on Ensemble Learning optimized Medical Image Classification with Deep Convolutional Neural Networks","created":"2022-01-27","cited_by_count":8,"area":null},{"id":"2209.10080","title":"Deep Double Descent via Smooth Interpolation","created":"2022-09-21","cited_by_count":8,"area":null},{"id":"2310.15444","title":"Fast Propagation is Better: Accelerating Single-Step Adversarial Training via Sampling Subnetworks","created":"2023-10-24","cited_by_count":8,"area":null},{"id":"2507.05121","title":"LVM4CSI: Enabling Direct Application of Pre-Trained Large Vision Models for Wireless Channel Tasks","created":"2025-07-07","cited_by_count":8,"area":null},{"id":"2103.02761","title":"Comparing the Value of Labeled and Unlabeled Data in Method-of-Moments Latent Variable Estimation","created":"2021-03-03","cited_by_count":7,"area":null},{"id":"2203.05443","title":"Bias-variance decomposition of overparameterized regression with random linear features","created":"2022-03-10","cited_by_count":7,"area":null},{"id":"2401.06864","title":"Deep Learning With DAGs","created":"2024-01-12","cited_by_count":7,"area":null},{"id":"2410.06851","title":"Understanding Model Ensemble in Transferable Adversarial Attack","created":"2024-10-09","cited_by_count":7,"area":null},{"id":"2502.13593","title":"Toward Robust Non-Transferable Learning: A Survey and Benchmark","created":"2025-02-19","cited_by_count":7,"area":null},{"id":"2201.09209","title":"Weight Expansion: A New Perspective on Dropout and Generalization","created":"2022-01-23","cited_by_count":6,"area":null},{"id":"2205.11359","title":"Towards Size-Independent Generalization Bounds for Deep Operator Nets","created":"2022-05-23","cited_by_count":6,"area":null},{"id":"2206.10566","title":"Ensembling over Classifiers: a Bias-Variance Perspective","created":"2022-06-21","cited_by_count":6,"area":null},{"id":"2302.03068","title":"Evaluating Self-Supervised Learning via Risk Decomposition","created":"2023-02-06","cited_by_count":6,"area":null},{"id":"2309.00064","title":"Ethical Framework for Harnessing the Power of AI in Healthcare and Beyond","created":"2023-08-31","cited_by_count":6,"area":null},{"id":"2310.13572","title":"Unraveling the Enigma of Double Descent: An In-depth Analysis through the Lens of Learned Feature Space","created":"2023-10-20","cited_by_count":6,"area":null},{"id":"2312.04542","title":"SoK: Unintended Interactions among Machine Learning Defenses and Risks","created":"2023-12-07","cited_by_count":6,"area":null},{"id":"2110.06910","title":"On the Double Descent of Random Features Models Trained with SGD","created":"2021-10-13","cited_by_count":5,"area":null},{"id":"2405.08276","title":"Scalable Subsampling Inference for Deep Neural Networks","created":"2024-05-14","cited_by_count":5,"area":null},{"id":"2512.22579","title":"SANet: A Semantic-aware Agentic AI Networking Framework for Cross-layer Optimization in 6G","created":"2025-12-27","cited_by_count":5,"area":"agents"},{"id":"2103.14108","title":"The Geometry of Over-parameterized Regression and Adversarial Perturbations","created":"2021-03-25","cited_by_count":4,"area":null},{"id":"2106.01714","title":"Optimization Variance: Exploring Generalization Properties of DNNs","created":"2021-06-03","cited_by_count":4,"area":null},{"id":"2112.00980","title":"Trap of Feature Diversity in the Learning of MLPs","created":"2021-12-02","cited_by_count":4,"area":null},{"id":"2112.04094","title":"The Effect of Model Size on Worst-Group Generalization","created":"2021-12-08","cited_by_count":4,"area":null},{"id":"2205.07427","title":"Exploring the Learning Difficulty of Data Theory and Measure","created":"2022-05-16","cited_by_count":4,"area":null},{"id":"2304.09758","title":"K-means Clustering Based Feature Consistency Alignment for Label-free Model Evaluation","created":"2023-04-17","cited_by_count":4,"area":null},{"id":"2405.16639","title":"A direct proof of a unified law of robustness for Bregman divergence losses","created":"2024-05-26","cited_by_count":4,"area":null},{"id":"2505.24313","title":"Weak-to-Strong Generalization via Bregman Bias-Variance Decomposition","created":"2025-05-30","cited_by_count":4,"area":null},{"id":"2107.00797","title":"Mitigating deep double descent by concatenating inputs","created":"2021-07-02","cited_by_count":3,"area":null},{"id":"2208.08003","title":"Investigating the Impact of Model Width and Density on Generalization in Presence of Label Noise","created":"2022-08-17","cited_by_count":3,"area":null},{"id":"2406.12222","title":"BadSampler: Harnessing the Power of Catastrophic Forgetting to Poison Byzantine-robust Federated Learning","created":"2024-06-18","cited_by_count":3,"area":null},{"id":"2408.05116","title":"Concept learning of parameterized quantum models from limited measurements","created":"2024-08-09","cited_by_count":3,"area":null},{"id":"2505.22602","title":"One Rank at a Time: Cascading Error Dynamics in Sequential Learning","created":"2025-05-28","cited_by_count":3,"area":null},{"id":"2204.12155","title":"Bias-Variance Decompositions for Margin Losses","created":"2022-04-26","cited_by_count":2,"area":null},{"id":"2206.03515","title":"How does overparametrization affect performance on minority groups?","created":"2022-06-07","cited_by_count":2,"area":null},{"id":"2211.10322","title":"Understanding the double descent curve in Machine Learning","created":"2022-11-18","cited_by_count":2,"area":null},{"id":"2401.16611","title":"Accelerating superconductor discovery through tempered deep learning of the electron-phonon spectral function","created":"2024-01-29","cited_by_count":2,"area":null},{"id":"2404.12481","title":"Understanding Optimal Feature Transfer via a Fine-Grained Bias-Variance Analysis","created":"2024-04-18","cited_by_count":2,"area":null},{"id":"2406.10090","title":"Over-parameterization and Adversarial Robustness in Neural Networks: An Overview and Empirical Analysis","created":"2024-06-14","cited_by_count":2,"area":null},{"id":"2505.20123","title":"Understanding Generalization in Diffusion Distillation via Probability Flow Distance","created":"2025-05-26","cited_by_count":2,"area":"diffusion"},{"id":"2103.00500","title":"Asymptotic Risk of Overparameterized Likelihood Models: Double Descent Theory for Deep Neural Networks","created":"2021-02-28","cited_by_count":1,"area":null},{"id":"2301.09869","title":"Image Super-Resolution using Efficient Striped Window Transformer","created":"2023-01-24","cited_by_count":1,"area":null},{"id":"2305.10110","title":"Adaptive aggregation of Monte Carlo augmented decomposed filters for efficient group-equivariant convolutional neural network","created":"2023-05-17","cited_by_count":1,"area":null},{"id":"2306.06948","title":"Rethinking Translation Memory Augmented Neural Machine Translation","created":"2023-06-12","cited_by_count":1,"area":null},{"id":"2310.09250","title":"It's an Alignment, Not a Trade-off: Revisiting Bias and Variance in Deep Models","created":"2023-10-13","cited_by_count":1,"area":null},{"id":"2406.01825","title":"Reliable OOD Virtual Screening with Extrapolatory Pseudo-Label Matching","created":"2024-06-03","cited_by_count":1,"area":null},{"id":"2503.08589","title":"Integration of nested cross-validation, automated hyperparameter optimization, high-performance computing to reduce and quantify the variance of test performance estimation of deep learning models","created":"2025-03-11","cited_by_count":1,"area":null},{"id":"2511.21715","title":"DNNs, Dataset Statistics, and Correlation Functions","created":"2025-11-18","cited_by_count":1,"area":null},{"id":"2605.18022","title":"Unveiling Memorization-Generalization Coexistence: A Case Study on Arithmetic Tasks with Label Noise","created":"2026-05-18","cited_by_count":1,"area":null},{"id":"2606.31536","title":"Beyond the Expressivity-Trainability Paradox: A Dynamical Lie Algebra Perspective on Navigating Barren Plateaus in Quantum Machine Learning","created":"2026-06-30","cited_by_count":1,"area":null},{"id":"2105.14117","title":"About Explicit Variance Minimization: Training Neural Networks for Medical Imaging With Limited Data Annotations","created":"2021-05-28","cited_by_count":0,"area":null},{"id":"2106.05522","title":"A Mathematical Foundation for Robust Machine Learning based on Bias-Variance Trade-off","created":"2021-06-10","cited_by_count":0,"area":null},{"id":"2211.15081","title":"Mitigating Overfitting in Graph Neural Networks via Feature and Hyperplane Perturbation","created":"2022-11-28","cited_by_count":0,"area":null},{"id":"2305.15907","title":"Double Descent of Discrepancy: A Task-, Data-, and Model-Agnostic Phenomenon","created":"2023-05-25","cited_by_count":0,"area":null},{"id":"2306.05583","title":"Gibbs-Based Information Criteria and the Over-Parameterized Regime","created":"2023-06-08","cited_by_count":0,"area":null},{"id":"2308.16456","title":"Least Squares Maximum and Weighted Generalization-Memorization Machines","created":"2023-08-31","cited_by_count":0,"area":null},{"id":"2312.03951","title":"Understanding the Role of Optimization in Double Descent","created":"2023-12-06","cited_by_count":0,"area":null},{"id":"2405.07679","title":"Class-wise Activation Unravelling the Engima of Deep Double Descent","created":"2024-05-13","cited_by_count":0,"area":null},{"id":"2411.02184","title":"Double Descent Meets Out-of-Distribution Detection: Theoretical Insights and Empirical Analysis on the role of model complexity","created":"2024-11-04","cited_by_count":0,"area":null},{"id":"2501.16289","title":"Multi-view Structural Convolution Network for Domain-Invariant Point Cloud Recognition of Autonomous Vehicles","created":"2025-01-27","cited_by_count":0,"area":null}],"next_cursor":"100"}