Gaussian Mixture Models

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Period ending 2026-09-14

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  1. Federated Soft Clustering via Generalized Total Variation Minimization

    Sep 16, 2026Shamsiiat Abdurakhmanova, Alexander JungClusteringGaussian Mixture Models

  2. How Wrong Can a Good Predictor Be? Diverging Updates with Vanishing Predictive KL

    Sep 11, 2026Qifu Wen, Shuaijun Liu, Zihan Zhou +2PosteriorKullback-Leibler Divergence

  3. Bridging Network Psychometrics and Artificial Intelligence: An Ising-Potts Model with LLM-Derived Weights

    Sep 8, 2026Matthias von DavierRaterMixture Models

  4. SGD in Multiclass Logistic Regression: Sequential Learning and Scaling Laws

    Sep 7, 2026Konstantinos Christopher Tsiolis, Denny Wu, Christos Thrampoulidis +1Multiclass ClassificationScaling Laws

  5. Geometric Ceilings on Time-Frequency Masking for Single-Channel Separation

    Sep 3, 2026Maxime BaeldeChannel EstimationTime-Frequency

  6. Semi-Supervised Classification with Informative Missing Labels in Weibull Mixture Models

    Sep 1, 2026Jinran Wu, You-Gan Wang, Geoffrey J. McLachlanSemi-Supervised LearningMixture Models

  7. DK-GBMKKM: Dynamic Kernel-Space Granular-Ball Multiple Kernel k-Means Clustering

    Sep 1, 2026Xiaoyu Lian, Yuchao Zhang, Shuyin Xia +2Granular-Ball ComputingK$-Means

  8. Structure Aware Neural Architecture Search for Mixture of Experts

    Aug 30, 2026Petr Babkin, Oleg BakhteevNeural Architecture SearchExperts

  9. MoPLEx: Estimating Plackett-Luce Mixture Models for Multi-Objective Alignment

    Aug 25, 2026Dongyue Li, Ziniu Zhang, Lu Wang +1Preference AlignmentGeneralizable Ranking Purpose

  10. Foundations of Independent Component Analysis

    Aug 13, 2026Patrick ForréIndependent Component AnalysisIdentifiability

  11. Gromov-Wasserstein Quantization and Clustering: Structure, Rates, and Algorithms

    Aug 11, 2026Florian Beier, Stephan EcksteinGromov--WassersteinK$-Means

  12. Dynamic Distribution-Aware Uncertainty Tracking in Vision-Language Representation Learning

    Aug 10, 2026Ao Zhou, Zhiwei Jiang, Zifeng Cheng +4Vision-Language ReasoningGaussian Mixture Models

  13. Multi-kernel spectral clustering: Entrywise eigenvector perturbation bounds and exact recovery

    Aug 9, 2026Zeqin Lin, Guangming Pan, Zhixiang Zhang +1Spectral AlgorithmsHigh-Dimensional

  14. A cylindrical neural approximation theorem for conditional laws of McKean-Vlasov equations with common noise

    Aug 8, 2026Nacira Agram, Reda Hmioui, Jan RemsNeural-Network ApproximationFokker--Planck Equation

  15. FUSE: Feature-Wise Unified Specialization with Cross-Column Exchange for Mixed-Type Tabular Flow Matching

    Aug 7, 2026Suman Cha, Seongchan Lee, Dohyun Ko +1Semantic-Aware Feature Re-FusionMixture Models

  16. Mixture of Geodesic Factor Analyzers on Riemannian Homogeneous Spaces

    Aug 7, 2026Hengchao Chen, Yuanyao Tan, Chao Huang +2Gaussian Mixture ModelsRiemannian Manifolds

  17. Minimax Optimal Early-Stopped Gradient Descent for Gaussian Mixture Classification

    Aug 6, 2026Alex Buna, Shirley Xiaoqi Liu, Patrick RebeschiniEmpirical Risk MinimizationGaussian Mixture Models

  18. Variational Bounds for Perceptron Learning from Structured Data

    Aug 5, 2026Francesco Camilli, Pierluigi Contucci, Federica Gerace +1Tight BoundsGaussian Mixture Models

  19. Encryption-Compatible Clustered Federated Learning via Distributed Expectation-Maximization over Metadata

    Jul 30, 2026Michael Ben Ali, Imen Megdiche, André Péninou +1Robust Federated LearningOne-Shot Federated Learning

  20. Equilibrium Training of Energy-Based Models with Parallel Trajectory Tempering

    Jul 29, 2026Nicolas Béreux, Aurélien Decelle, Cyril Furtlehner +1Monte Carlo SamplingExpectation-Maximization

  21. Rethinking Likelihood distributions: Student's t Likelihood Boosts Bayesian Neural Network Performance

    Jul 28, 2026Pei-Hsuan Hsia, Lars H. Heyen, Arvid Weyrauch +4Bayesian Neural NetworksVariational Inference

  22. Lloyd's K-Means Clustering Algorithm Is Frank-Wolfe in Disguise

    Jul 28, 2026Michael Pokojovy, J. Marcus Jobe, Simon Lacoste-JulienK$-MeansClustering

  23. Multiclass Classification without Labels via Posterior Simplex Geometry

    Jul 27, 2026Raphaël Bonnet-Guerrini, Johann Ioannou-Nikolaides, Troels Petersen +1Multiclass ClassificationUnlabeled Data

  24. PYPM-GGD: Pitman-Yor Process Mixture with Generalized Gaussian Density using ADAM

    Jul 27, 2026Kart-Leong LimVariational InferenceAdam

  25. Logit-Coordinate Generative Models for Mixed Continuous-Categorical Tabular Data

    Jul 25, 2026Yuefei Shen, Xiaotong ShenMixture ModelsLogit Lens

  26. Nesterov acceleration in optimizing over probability measures

    Jul 25, 2026Jiaqi Tang, Qin Li, Wilfrid GangboNesterovProbability Measures

  27. Distributional Determinantal Point Process for Repulsive Clustering of Distributions

    Jul 23, 2026Khai Nguyen, Yang Ni, Elizabeth Juarez-Colunga +1Determinantal Point ProcessMixture Models

  28. Incomplete Observations Boost Evolutionary Performance in Ocean Modeling

    Jul 21, 2026Yangyang Kong, Yutong Jiang, Yanhai Gan +3Data AssimilationOcean Dynamics

  29. AMICA-Python: Adaptive Mixture Independent Component Analysis with Anderson Acceleration

    Jul 20, 2026Scott Huberty, Christian O'ReillyElectroencephalogramIndependent Component Analysis

  30. Mixing-Free and Signal-Optimal Learning of Gaussian Graphical Models from Glauber Dynamics

    Jul 20, 2026Vignesh Tirukkonda, Gautam DasarathyGaussian Mixture Models3D Gaussian Splatting

  31. RayOcc: Occlusion-Aware Ray Occupancy Estimation via Gaussian Mixture Intensity

    Jul 20, 2026Junho Kim, Seongwon Lee3D Semantic Occupancy PredictionDifferentiable Polarized Path Tracing

  32. Team DACTYL at PAN 2026: Bayesian Data Mixing and Empirical X-risk Minimization for AI-text Detection

    Jul 19, 2026Shantanu ThoratMachine-Generated Text DetectionOut-Of-Distribution Detection Performance

  33. Robust Chance-Constrained Optimization using a Continuous Parameter Space Wasserstein-2 Ambiguity Set of Gaussian Mixtures

    Jul 19, 2026Shibshankar Dey, Sanjay MehrotraMulti-Objective OptimizationGaussian Mixture Models

  34. Dimension-Calibrated Unexplained Mass: An Interpretable Drift Statistic for Contamination Monitoring in Data Streams

    Jul 18, 2026Behnam AsadiDrift StatisticGaussian Mixture Models

  35. Von Mises-Fisher Mixture Model with Dynamic Shrinkage for Realistic Test-Time Transduction

    Jul 17, 2026Jiazhen Huang, Zhiming Liu, Changhu Wang +3Mixture ModelsHyperparameter

  36. Spectral Concentration and Recovery in Sparse High-Dimensional Random Geometric Graphs

    Jul 15, 2026Manuel Fernandez, Yizhe ZhuExponential Random Graph ModelsLatent Cluster Geometry

  37. An Efficient Newton Algorithm for Nonnegative Matrix Factorization with the Kullback-Leibler Divergence

    Jul 15, 2026Damien Lesens, Jérémy E. Cohen, Bora UçarNonnegative Matrix FactorizationKullback-Leibler Divergence

  38. Heavy-Tailed Flow Matching via Random Clocks

    Jul 15, 2026Zhouhao Yang, Yezhen Wang, Kenji Kawaguchi +2Conditional Flow MatchingHeavy-Tailed Noise

  39. The Hyperspherical Geometry of CLIP Latent Space: A Semantic Mixture Model

    Jul 15, 2026Zijie Yu, Gaowen Liu, Ramana Rao Kompella +2Contrastive Language-Image Pre-TrainingHyperspherical Embedding Geometry

  40. DP-BOA: Dirichlet-Process Birth-or-Assign for On-the-Fly Category Discovery

    Jul 15, 2026Peiyan Gu, Zixin Teng, Xuming HeGeneralized Category DiscoveryMixture Models

  41. UD-ASD: A Unified Diffusion Model for Anomalous Sound Detection

    Jul 14, 2026Pengxiang Gao, Yu Qiu, Yanzhi SongMel-Frequency Cepstral CoefficientGaussian Mixture Models

  42. Gaussian Mixture Modeling for Event-Aware Visual Allocation in Long Video Understanding

    Jul 14, 2026Yifan Lu, Ziqi Zhang, Chunfeng Yuan +3Video UnderstandingLong-Video Benchmarks

  43. Cluster-Weighted EDMD

    Jul 14, 2026Lorenzo Tomaz, Judd Rosenblatt, Flavio Kicis +2Koopman OperatorPhase Space

  44. Remembering Distinct Items, Not Tokens: A Learnable Dirichlet-Process Cache Between State-Space Models and Attention

    Jul 10, 2026Siddharth Pal, Viktoria RojkovaRecurrent StateCache

  45. An interpretable Good--Turing restart criterion for k-means++

    Jul 9, 2026Renato Cordeiro de AmorimK$-MeansMaximum Mean Discrepancy

  46. FedSPM: Routing-Enabled Federated Learning under Dual Heterogeneity via Semiparametric Mixture

    Jul 5, 2026Zijian Wang, Pengfei Li, Guangyu Yang +1HeterogeneityFedavg

  47. Mixture-of-Gaussians-Guided Schedule Design for Brownian Bridge Diffusion Models

    Jul 3, 2026Ron Levi, Michael EladSchrödinger BridgesImage Restoration

  48. Mixture-Constrained Max Pooling Improves Separation-Based Bird Species Classification

    Jul 3, 2026Yuzhu Wang, Kalle Lahtinen, Patrik Lauha +4Source SeparationAudio Classification

  49. WARP: Weight-Space Analysis for Recovering Training Data Portfolios

    Jul 2, 2026Tzu-Heng Huang, Aditya Goyal, John Cooper +1Weight-SpaceTraining Data

  50. eXact-Prior Variational Autoencoder (X-VAE): Learning Data-Adaptive Gaussian Mixture Priors for Latent Distributions

    Jun 30, 2026Qijun Chen, Shaofan LiVariational EncoderGenerative Priors

  51. Accelerated Likelihood Maximization for Diffusion-based Versatile Content Generation

    Jun 30, 2026Hyunsoo Lee, Inwoo Hwang, Young Min KimDiffusion ModelsAi-Generated

  52. TDGT: A Tabular Data Generation Toolkit supporting adaptive GPU-accelerated Bayesian mixture models, diffusion-based models, and latent-space generative modeling

    Jun 30, 2026Vasileios C. Pezoulas, Nikolaos S. Tachos, Eleni Georga +3Synthetic Tabular DataSynthetic Data

  53. Simplifying Flow Matching Transformations with Low-Rank Mixture Models

    Jun 29, 2026Liam A. Kruse, Houjun Liu, Alexandros E. Tzikas +2Normalizing FlowsConditional Flow Matching

  54. Nonlinear mixture model motivated subspace clustering

    Jun 28, 2026Ivica KoprivaMixture ModelsSpeech Separation

  55. Multi-Contact Force Estimation for Continuum Robots via Gaussian-Parameterized Factor Graphs

    Jun 28, 2026Aditya Prakash, Panagiotis TsiotrasForce SensingEdge-Sdf Contacts

  56. Fast algorithms for learning a Gaussian under halfspace truncation with optimal sample complexity

    Jun 25, 2026Haitong Liu, Deepak Narayanan Sridharan, David Steurer +1Optimal Sample ComplexityGaussian Mixture Models

  57. Rethinking Training & Inference for Forecasting: Linking Winner-Take-All back to GMMs

    Jun 24, 2026Qiyuan Wu, Katie Z Luo, Bharath Hariharan +2Trajectory PredictionRetrieval-Augmented Forecasting

  58. Stochastic Expectation Maximization for Robust State-Space Radio Interferometric Imaging

    Jun 22, 2026Nawel Arab, Mohammed Nabil El Korso, Isabelle Vin +1State Space ModelsExpectation-Maximization

  59. From Point Estimates to Distributions: GMM Pooling for MIL in Preterm Birth Prediction

    Jun 22, 2026Hussain Alasmawi, Numan Saeed, Soha Said +1Multiple Instance LearningGaussian Mixture Models

  60. Cohort Organized Learning: Clustering Through Agreement

    Jun 19, 2026Finn Henry O'Shea, Maria Elena MonzaniClusteringCluster