Mixture Models

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Period ending 2026-09-21

3 new papers

A weekly snapshot of new work published in Mixture Models.

Period ending 2026-09-14

2 new papers

A weekly snapshot of new work published in Mixture Models.

Period ending 2026-09-07

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A weekly snapshot of new work published in Mixture Models.

78 papers

Latest in Mixture Models

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Distributionally Robust Federated Learning with Multi-Source Data
Sep 17, 2026Yingzhu Liu, Zhongkui Li, Pengcheng You +1Federated Learning Distributional Learning
Bracketing Uncertainty in Clustering Under the Manifold Hypothesis
Sep 15, 2026Savik Kinger, Luciano Dyballa, Steven W. ZuckerManifold Learning Method Input Uncertainties
The Free Inference Dimension: Complexity Measure for Zero-Collision Navigation under Hypothesis Mixtures
Sep 15, 2026Luiz Carlos Castro Guedes, Edward Hermann HaeuslerCollision-Free Trajectories Model-Free Reinforcement Learning
Generative Marketing Mix Modeling: A Causal Inference Framework Linking GEO and GEM to Business Impact
Sep 12, 2026Masahiro Kato, Daiki Honma, Taka KatoGenerative Causal Inferences
How Wrong Can a Good Predictor Be? Diverging Updates with Vanishing Predictive KL
Sep 11, 2026Qifu Wen, Shuaijun Liu, Zihan Zhou +2Posterior Kullback-Leibler Divergence
Semi-Supervised Classification with Informative Missing Labels in Weibull Mixture Models
Sep 1, 2026Jinran Wu, You-Gan Wang, Geoffrey J. McLachlanSemi-Supervised Learning Mixture Models
MoPLEx: Estimating Plackett-Luce Mixture Models for Multi-Objective Alignment
Aug 25, 2026Dongyue Li, Ziniu Zhang, Lu Wang +1Preference Alignment Late-Stage Ranker
BPG: Balancing Plasticity and Generalization for Domain Incremental Learning
Aug 11, 2026Qiang Wang, Songlin Dong, Shaokun Wang +5Domain Incremental Learning Multimodal Domain Generalization
Multi-kernel spectral clustering: Entrywise eigenvector perturbation bounds and exact recovery
Aug 9, 2026Zeqin Lin, Guangming Pan, Zhixiang Zhang +1Kernel Method Largest Eigenvalue
A cylindrical neural approximation theorem for conditional laws of McKean-Vlasov equations with common noise
Aug 8, 2026Nacira Agram, Reda Hmioui, Jan RemsNeural-Network Approximation Fokker--Planck Equation
Capacity Confounds and Coverage Guarantees in Adaptive Sub-model Federated Learning
Aug 7, 2026Alireza Moayedikia, Alicia Troncoso LoraFederated Learning Finite-Sample Coverage Guarantees
Harnessing the Potential of Optimizing Data Mixtures via Bayesian Domain Reweighting
Jul 30, 2026Xiang Yuan, Kaiqing Lei, Zhenyu Jin +3Reweighting Model Weights
Multiclass Classification without Labels via Posterior Simplex Geometry
Jul 27, 2026Raphaël Bonnet-Guerrini, Johann Ioannou-Nikolaides, Troels Petersen +1Multiclass Classification Unlabeled Data
PYPM-GGD: Pitman-Yor Process Mixture with Generalized Gaussian Density using ADAM
Jul 27, 2026Kart-Leong LimVariational Inference Adam
Logit-Coordinate Generative Models for Mixed Continuous-Categorical Tabular Data
Jul 25, 2026Yuefei Shen, Xiaotong ShenMixture Models Logit Lens
Distributional Determinantal Point Process for Repulsive Clustering of Distributions
Jul 23, 2026Khai Nguyen, Yang Ni, Elizabeth Juarez-Colunga +1Determinantal Point Process Mixture Models
Team DACTYL at PAN 2026: Bayesian Data Mixing and Empirical X-risk Minimization for AI-text Detection
Jul 19, 2026Shantanu ThoratMachine-Generated Text Detection Modernbert
Robust Chance-Constrained Optimization using a Continuous Parameter Space Wasserstein-2 Ambiguity Set of Gaussian Mixtures
Jul 19, 2026Shibshankar Dey, Sanjay MehrotraRobust Optimization Gaussian Mixture Models
Von Mises-Fisher Mixture Model with Dynamic Shrinkage for Realistic Test-Time Transduction
Jul 17, 2026Jiazhen Huang, Zhiming Liu, Changhu Wang +3Vision-Language Model Adaptation Transductive Active Labeling
The Hyperspherical Geometry of CLIP Latent Space: A Semantic Mixture Model
Jul 15, 2026Zijie Yu, Gaowen Liu, Ramana Rao Kompella +2Hyperbolic Space Mixture Models
DP-BOA: Dirichlet-Process Birth-or-Assign for On-the-Fly Category Discovery
Jul 15, 2026Peiyan Gu, Zixin Teng, Xuming HeGeneralized Category Discovery Mixture Models
Remembering Distinct Items, Not Tokens: A Learnable Dirichlet-Process Cache Between State-Space Models and Attention
Jul 10, 2026Siddharth Pal, Viktoria RojkovaRecurrent State Cache
BACH: A Bayesian Admixture of Contrastive Heads for Multi-Interest Two-Tower Retrieval
Jul 9, 2026Quoc Phong Nguyen, Paul Albert, Long Vuong +2Retrievers Mixture Models
FedSPM: Routing-Enabled Federated Learning under Dual Heterogeneity via Semiparametric Mixture
Jul 5, 2026Zijian Wang, Pengfei Li, Guangyu Yang +1Heterogeneous Federated Learning Federated Learning
Mixture-Constrained Max Pooling Improves Separation-Based Bird Species Classification
Jul 3, 2026Yuzhu Wang, Kalle Lahtinen, Patrik Lauha +4Speech Separation Mixture Models
WARP: Weight-Space Analysis for Recovering Training Data Portfolios
Jul 2, 2026Tzu-Heng Huang, Aditya Goyal, John Cooper +1Weight-Space Training Data
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 Data Synthetic Data
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 Adaptation Pseudo-Labeling
Simplifying Flow Matching Transformations with Low-Rank Mixture Models
Jun 29, 2026Liam A. Kruse, Houjun Liu, Alexandros E. Tzikas +2Normalizing Flows Conditional Flow Matching
Nonlinear mixture model motivated subspace clustering
Jun 28, 2026Ivica KoprivaMixture Models Speech Separation
Score Approximation for Diffusion Models on Arbitrary Low-Dimensional Structures
Jun 18, 2026Xinhe Mu, Zaijiu Shang, Zhaoqi Zhou +4Score-Based Diffusion Model Low-Dimensional Structure
An Information Theoretic Framework for Graph Novelty Generation via Latent Mixture Modeling
Jun 18, 2026Itsuki Nakagawa, Kenji YamanishiGraph Representation Learning Generative Models
Variational Consensus Monte Carlo for Bayesian Mixture
Jun 17, 2026Julie Fendler, Francesca L. Crowe, Tom Marshall +2Mixture Models Federated Learning
Integrated Marketing Attribution: A Bayesian Framework for Privacy-Safe Granular Measurement Anchored in MMM
Jun 15, 2026Meghana R. Bhat, Ankit Umare, Utsav Aggarwal +4Visual Attribution Mixture Models
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 +1Contamination Noisy Labels
Information Gap and Feasibility-Aware Inference in Binomial Logistic Mixtures
Jun 14, 2026Yuta Hayashida, Shonosuke SugasawaMixture Models Bayesian
FastMix: Fast Data Mixture Optimization via Gradient Descent
Jun 12, 2026Haoru Tan, Sitong Wu, Yanfeng Chen +5Model Pretraining Mixture Models
A theoretical model for task routing in mixture-of-expert transformers
Jun 12, 2026Vinoth Nandakumar, Yongli Xiang, Yunzhi Yao +2Mixture-of-Experts Models Transformer Layers
Simultaneous Latent Budget Trees for Stratified Classification
Jun 11, 2026Simultaneous Latent Budget Trees for Stratified Classification Cristian Buoncompagni, Stefano Pellegrino, Giulia Vannucci +2Decision Trees Stratification
Brick: Spatial Capability Routing for the Mixture-of-Models (MoM) Paradigm
Jun 11, 2026Francesco Massa, Marco CristofanilliLarge Language Model Routing Craft
Probabilistic Salary Prediction with Graph Attention Networks and a Mixture Density Network
Jun 10, 2026Zhipei Qin, Mohammad Shokri, N. van Weeren +1Mixture Models
Explaining Data Mixing Scaling Laws
Jun 6, 2026Rui Dai, Shuran ZhengScaling Laws Mixture Models
Identifiability and Estimation for Unlabeled Finite Mixtures under Marginal Independence
Jun 6, 2026Takafumi Kanamori, Yushi Hirose, Shohei YamamotoMixture Models Identifiability
TANDEM: Bi-Level Data Mixture Optimization with Twin Networks
Jun 3, 2026Jiaxing Wang, Deping Xiang, Jin Xu +9Mixture Models Reweighting
Folded Transport MCMC: Eliminating Label Switching by Sampling on a Fundamental Domain
Jun 3, 2026Jun HuMarkov Chain Monte Carlo Mixture Models
Modeling Depth Ambiguity: A Mixture-Density Representation for Flying-Point-Free Depth Estimation
Jun 1, 2026Siyuan Bian, Congrong Xu, Jun GaoDepth Estimation Mixture Models
A Biconvex Formulation for Stable Transport of Mixture Models with a Unique Solution
Jun 1, 2026Yeganeh Marghi, Kelly Jin, Uygar SümbülOptimal Transport Mixture Models
Wasserstein Contraction of Coordinate Ascent Variational Inference
May 28, 2026Rocco Caprio, Adrien Corenflos, Sam PowerVariational Inference Wasserstein Distance
Mixing Vector Model for Copolymer Inference via Mixed Integer Linear Programming
May 28, 2026Jianshen Zhu, Raveena Rai, Taiyo Sohkawa +4Polymer Molecular Property Prediction
A Minimal Bifurcation Model of Load Imbalance in a Softmax Mixture-of-Experts Router
May 27, 2026O. M. KiselevLoad Balancing Mixture-of-Experts Models
Modeling Dynamic Mixtures of Time-Delay Systems from Streaming Time Series
May 25, 2026Ren Fujiwara, Yasuko Matsubara, Yasushi SakuraiDelay Mixture Models
Estimating Mixture Distributions via Stochastic Mirror Descent
May 24, 2026Mohammadreza Ahmadypour, Tara Javidi, Farinaz KoushanfarMixture Models Estimators
GMENet: Generative Mixture of Experts Network for Multi-Center Glioma Diagnosis with Incomplete Imaging Sequences
May 22, 2026Pengfei Song, Fangjin Liu, Wenwen Zeng +5Glioma Magnetic Resonance Imaging
A Mutual Information Lower Bound for Multimodal Regression Active Learning
May 14, 2026Leonardo Ferreira Guilhoto, Akshat Kaushal, Paris PerdikarisActive Learning Robust Multimodal Learning
Black-Box Optimization of Mixed Binary-Continuous Variables: Challenges and Opportunities in Evolutionary Model Merging
May 12, 2026Md. Robiul Islam NiloyModel Merging Large Language Model Pretraining
YOTOnet: Zero-Shot Cross-Domain Fault Diagnosis via Domain-Conditioned Mixture of Experts
May 6, 2026Zesen Wang, Zihao Wu, Yue Hu +2Fault Diagnosis Multimodal Domain Generalization
On Computing Total Variation Distance Between Mixtures of Product Distributions
May 5, 2026Weiming Feng, Yucheng Fu, Minji Yang +1Mixture Models Distance
Soft-to-Hard Routing in Sparse Mixture-of-Experts Models
May 4, 2026Reza RastegarMixture Models Gumbel-Softmax Relaxation
A Quantitative Confirmation of the Currier Language Distinction
Apr 28, 2026Christophe PariselIndistinguishability English
Heterogeneous Variational Inference for Markov Degradation Hazard Models: Discretized Mixture with Interpretable Clusters
Apr 27, 2026Takato YasunoMixture Models Variational Inference

Sep 17, 2026 · cs.LGJ/K move · Enter open · S save

Distributionally Robust Federated Learning with Multi-Source Data

Yingzhu Liu, Zhongkui Li, Pengcheng You, Ashish Cherukuri

Federated learning trains a shared model from private client data. In practice, data-generating distributions may differ, and the true mixture across clients is often unknown, making the underlying group distribution difficult to specify. Existing approaches address cross-client mixture uncertainty by optimizing against the worst-case mixture, yet assume accurate client-wise distribution estimates. However, these estimates can be unreliable when based on finite samples. To handle both cross-client mixture uncertainty and within-client distributional ambiguity, we construct a global ambiguity set as the union of admissible mixtures of local ambiguity sets. The construction allows client-specific ambiguity radii and admits a client-wise separable reformulation. Leveraging this structure, we establish a high-probability out-of-sample performance guarantee. We further develop a federated algorithm for a penalty-based reformulation and prove its convergence under milder regularity conditions. Simulations validate the algorithm's effectiveness.

Federated Learning Distributional Learning Mixture Models Private Data

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