Distributional Learning

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16 papers in the last 28 days · 0.3% of indexed attention

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Period ending 2026-09-21

7 new papers

A weekly snapshot of new work published in Distributional Learning.

Period ending 2026-09-14

6 new papers

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Period ending 2026-09-07

3 new papers

A weekly snapshot of new work published in Distributional Learning.

229 papers

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  1. Personalized Federated Learning for Gradient Alignment

    May 4, 2026Dongwon Kim, Gyuejeong LeeFederated LearningPersonalization

  2. Stable GFlowNets with Probabilistic Guarantees

    May 3, 2026Zengxiang Lei, Ananth Shreekumar, Jonathan Rosenthal +6Generative Flow NetworksDistributional Learning

  3. Stability and Generalization for Decentralized Markov SGD

    May 3, 2026Jiahuan Wang, Ziqing Wen, Ping Luo +2Stochastic Gradient DescentGeneralization Bounds

  4. FedKPer: Tackling Generalization and Personalization in Medical Federated Learning via Knowledge Personalization

    May 1, 2026Zoe Fowler, Ghassan AlRegibFederated LearningFedavg

  5. Learning While Deploying: Fleet-Scale Reinforcement Learning for Generalist Robot Policies

    May 1, 2026Yi Wang, Xinchen Li, Pengwei Xie +13Flow-Matching Vision-Language-ActionRobot Policies

  6. FMCL: Class-Aware Client Clustering with Foundation Model Representations for Heterogeneous Federated Learning

    Apr 30, 2026Mahad Ali, Laura J. BrattainHeterogeneous Federated LearningFederated Learning

  7. Toward a Functional Geometric Algebra for Natural Language Semantics

    Apr 28, 2026James PustejovskyDistributional Learning

  8. Subspace Optimization for Efficient Federated Learning under Heterogeneous Data

    Apr 28, 2026Shuchen Zhu, Zhengyang Huang, Yuqi Xu +1Heterogeneous Federated LearningFederated Learning

  9. 8DNA: 8D Neural Asset Light Transport by Distribution Learning

    Apr 28, 2026Liwen Wu, Haolin Lu, Bing Xu +2Neural Rendering3D Assets

  10. The Power of Power Law: Asymmetry Enables Compositional Reasoning

    Apr 24, 2026Zixuan Wang, Xingyu Dang, Jason D. Lee +1Power-Law DistributionDistributional Learning

  11. Data-Free Contribution Estimation in Federated Learning using Gradient von Neumann Entropy

    Apr 24, 2026Asim Ukaye, Mubarak Abdu-Aguye, Nurbek Tastan +1Federated LearningEntropy-Regularized Equilibrium Selection

  12. Differentially Private Clustered Federated Learning with Privacy-Preserving Initialization and Normality-Driven Aggregation

    Apr 22, 2026Jie Xu, Haaris Mehmood, Rogier Van Dalen +2Federated LearningDifferential Privacy

  13. Decision-Focused Federated Learning Under Heterogeneous Objectives and Constraints

    Apr 21, 2026Konstantinos Ziliaskopoulos, Alexander VinelFederated LearningHeterogeneity

  14. FedSEA: Achieving Benefit of Parallelization in Federated Online Learning

    Apr 21, 2026Harekrushna Sahu, Pratik Jawanpuria, Pranay SharmaFederated LearningFederated Reinforcement Learning

  15. Semantic-based Distributed Learning for Diverse and Discriminative Representations

    Apr 20, 2026Zhuojun Tian, Chaouki Ben Issaid, Mehdi BennisDistributional LearningRepresentation Learning

  16. Training Time Prediction for Mixed Precision-based Distributed Training

    Apr 17, 2026Minchul Kang, Changyong Shin, Jinwoo Jeong +5Training TimeFull-Precision Performance

  17. Robust Synchronisation for Federated Learning in The Face of Correlated Device Failure

    Apr 17, 2026Stefan Behfar, Richard MortierFederated LearningFairness-Aware Learning

  18. FedIDM: Achieving Fast and Stable Convergence in Byzantine Federated Learning through Iterative Distribution Matching

    Apr 16, 2026He Yang, Dongyi Lv, Wei Xi +3Federated LearningByzantine Attacks

  19. Tight Bounds for Learning Polyhedra with a Margin

    Apr 16, 2026Shyamal Patel, Santosh VempalaPolytopesLower Bounds

  20. Salt: Self-Consistent Distribution Matching with Cache-Aware Training for Fast Video Generation

    Apr 3, 2026Xingtong Ge, Yi Zhang, Yushi Huang +6Autoregressive Video GenerationImage Denoising

  21. Relatively Smart: A New Approach for Instance-Optimal Learning

    Mar 2, 2026Shaddin Dughmi, Alireza F. PourSemi-Supervised LearningDistributional Learning

  22. Communication-Efficient Byzantine-Robust Federated Conformal Prediction via Partial Sharing

    Feb 20, 2026Ehsan Lari, Reza Arablouei, Stefan WernerFederated LearningConformal Prediction

  23. Decentralized SGD with Controlled Disagreement Finds Flatter Minima

    Feb 2, 2026Zesen Wang, Mikael JohanssonStochastic Gradient DescentDistributional Learning

  24. Efficient Public Verification of Private ML via Regularization

    Dec 3, 2025Zoë Ruha Bell, Anvith Thudi, Olive Franzese-McLaughlin +2Differential PrivacyPrivacy-Utility Trade-Offs

  25. Distributed Dynamic Associative Memory via Online Convex Optimization

    Nov 28, 2025Bowen Wang, Matteo Zecchin, Osvaldo SimeoneDense Associative MemoryLearning-Augmented Algorithms

  26. A Nesterov-Accelerated Byzantine-Robust Federated Learning

    Nov 4, 2025Lihan Xu, Xiaoyi Fan, Gang Wang +3Byzantine AttacksFederated Learning

  27. CogniDir: Combating Cognitive Malicious Comments via Adaptive Distributional Learning for Robust Fake News Detection

    Oct 10, 2025Zhao Tong, Chunlin Gong, Yimeng Gu +5Fake News DetectionLanguage Model Evasion Attacks

  28. How Does the Pretraining Distribution Shape In-Context Learning? A Fundamental Trade-Off

    Oct 1, 2025Waïss Azizian, Ali HasanIn-Context LearningDistributional Learning

  29. Task-Agnostic Federated Continual Learning via Replay-Free Gradient Projection

    Sep 25, 2025Seohyeon Cha, Huancheng Chen, Haris VikaloEfficient Continual LearningContinual Learning Methods

  30. A Discrepancy-Based Perspective on Dataset Condensation

    Sep 12, 2025Tong Chen, Raghavendra SelvanMaximum Mean DiscrepancySynthetic Dataset

  31. FAIRVAR: Fair Federated Learning via Variance Regularization

    Aug 16, 2025Zahra Kharaghani, Ali Dadras, Tommy LöfstedtFairness-Aware LearningFederated Learning

  32. Random Walk Learning and the Pac-Man Attack

    Aug 1, 2025Xingran Chen, Parimal Parag, Rohit Bhagat +2Worst-CaseAdversarial Training

  33. Tight Stability Bounds for Robust Distributed Learning: Byzantine Failures Hurt Generalization More than Data Poisoning

    Jun 22, 2025Thomas Boudou, Batiste Le Bars, Nirupam Gupta +1Distributional LearningGeneralization Bounds

  34. Chisme: Heterogeneity-Aware Gossip Learning

    May 14, 2025Harikrishna Kuttivelil, Katia ObraczkaHeterogeneous Edge DevicesFederated Learning

  35. Sufficient Decision Proxies for Decision-Focused Learning

    May 6, 2025Noah Schutte, Grigorii Veviurko, Krzysztof Postek +1Sequential Decision MakingDistributional Learning

  36. Distributionally Robust Optimization via Iterative Algorithms in Continuous Probability Spaces

    Dec 29, 2024Linglingzhi Zhu, Yunqin Zhu, Yao XieRobust OptimizationDistributional Learning

  37. Discrete distributions are learnable from metastable samples

    Oct 17, 2024Abhijith Jayakumar, Andrey Y. Lokhov, Sidhant Misra +1Two-Dimensional Ising ModelDistributional Learning

  38. Adaptive teachers for amortized samplers

    Oct 2, 2024Minsu Kim, Sanghyeok Choi, Taeyoung Yun +7SamplersAdaptive Testing

  39. Breaking the Curse of Dimensionality: Diffusion Models Efficiently Learn Low-Dimensional Distributions

    Sep 4, 2024Peng Wang, Huijie Zhang, Zekai Zhang +3Low-Dimensional StructureDistributional Learning

  40. Certified Robust Invariant Polytope Training in Neural Controlled ODEs

    Aug 2, 2024Akash Harapanahalli, Samuel CooganNeural ControlLyapunov Function

  41. Distributionally Robust Reinforcement Learning with Interactive Data Collection: Fundamental Hardness and Near-Optimal Algorithms

    Apr 4, 2024Miao Lu, Han Zhong, Tong Zhang +1Markov Decision ProcessesDistributional Learning

  42. Convergence Analysis of Sequential Federated Learning on Heterogeneous Data

    Nov 6, 2023Yipeng Li, Xinchen LyuFederated LearningConvergence Analysis

  43. Consistent Distributed Ranking of Generative Models via Kernel Distances

    Oct 18, 2023Zixiao Wang, Farzan Farnia, Zhenghao Lin +2Late-Stage RankerModel Evaluation

  44. Reinforcement Federated Learning Method Based on Adaptive OPTICS Clustering

    Jun 22, 2023Tianyu Zhao, Junping Du, Yingxia Shao +1Federated LearningDistributional Learning

  45. Reliable learning in challenging environments

    Apr 6, 2023Maria-Florina Balcan, Steve Hanneke, Rattana Pukdee +1Distributional LearningMachine Learning

  46. GFlowNets and variational inference

    Oct 2, 2022Esmeralda S. Whitammer, Salem Lahlou, Tristan Deleu +5Variational InferenceGenerative Flow Networks

  47. Learning from a Biased Sample

    Sep 5, 2022Roshni Sahoo, Lihua Lei, Stefan WagerEmpirical Risk MinimizationSelection Bias

  48. Multi-Source Wasserstein Distributionally Robust Graph Learning

    Date pendingChuansen Peng, Yifan Xia, Jinshan Zhong +1Graph Representation LearningWasserstein Distance

  49. Guided Adversarial Robust Transfer Learning with Source Mixing

    Date pendingXin Xiong, Zijian Guo, Tianxi CaiTransfer LearningAdversarial Transferability