Copertina

Local Minima Structures in Gaussian Mixture Models

Fuente: arXiv

Salvato in:

Dettagli Bibliografici
Autori principali:	Chen, Yudong, Song, Dogyoon, Xi, Xumei, Zhang, Yuqian
Natura:	Preprint
Pubblicazione:	2020
Soggetti:	Machine Learning Statistics Theory
Accesso online:	Acceder al recurso
Tags:	Aggiungi Tag Nessun Tag, puoi essere il primo ad aggiungerne!!

Documenti analoghi

Algebraic and Statistical Properties of the Ordinary Least Squares Interpolator
di: Shen, Dennis, et al.
Pubblicazione: (2023)

Adaptive Mean Estimation in the Hidden Markov sub-Gaussian Mixture Model
di: Karagulyan, Vahe, et al.
Pubblicazione: (2024)

Gaussian Mixture Model with unknown diagonal covariances via continuous sparse regularization
di: Giard, Romane, et al.
Pubblicazione: (2025)

Posterior Covariance Structures in Gaussian Processes
di: Cai, Difeng, et al.
Pubblicazione: (2024)

Robust Unsupervised Multi-task and Transfer Learning on Gaussian Mixture Models
di: Tian, Ye, et al.
Pubblicazione: (2022)

Optimal Confidence Band for Kernel Gradient Flow Estimator
di: Cheng, Yuqian, et al.
Pubblicazione: (2026)

The Decaying Missing-at-Random Framework: Model Doubly Robust Causal Inference with Partially Labeled Data
di: Zhang, Yuqian, et al.
Pubblicazione: (2023)

Neumann-series corrections for regression adjustment in randomized experiments
di: Song, Dogyoon
Pubblicazione: (2025)

Design-based finite-sample analysis for regression adjustment
di: Song, Dogyoon
Pubblicazione: (2025)

Causal inference through multi-stage learning and doubly robust deep neural networks
di: Zhang, Yuqian, et al.
Pubblicazione: (2024)

Sharp Inequalities between Total Variation and Hellinger Distances for Gaussian Mixtures
di: Jung, Joonhyuk, et al.
Pubblicazione: (2026)

Nonparametric MLE for Gaussian Location Mixtures: Certified Computation and Generic Behavior
di: Polyanskiy, Yury, et al.
Pubblicazione: (2025)

Model Selection for Gaussian-gated Gaussian Mixture of Experts Using Dendrograms of Mixing Measures
di: Thai, Tuan, et al.
Pubblicazione: (2025)

Dimension-Free Convergence of Diffusion Models for Approximate Gaussian Mixtures
di: Li, Gen, et al.
Pubblicazione: (2025)

Identifiability of Potentially Degenerate Gaussian Mixture Models With Piecewise Affine Mixing
di: Xu, Danru, et al.
Pubblicazione: (2026)

The $φ$ Curve: The Shape of Generalization through the Lens of Norm-based Capacity Control
di: Wang, Yichen, et al.
Pubblicazione: (2025)

Adaptive Split Balancing for Optimal Random Forest
di: Zhang, Yuqian, et al.
Pubblicazione: (2024)

Double Robust Semi-Supervised Inference for the Mean: Selection Bias under MAR Labeling with Decaying Overlap
di: Zhang, Yuqian, et al.
Pubblicazione: (2021)

Learning Mixtures of Gaussians Using Diffusion Models
di: Gatmiry, Khashayar, et al.
Pubblicazione: (2024)

Eventually LIL Regret: Almost Sure $\ln\ln T$ Regret for a sub-Gaussian Mixture on Unbounded Data
di: Agrawal, Shubhada, et al.
Pubblicazione: (2025)

Distributed Estimation and Inference for Semi-parametric Binary Response Models
di: Chen, Xi, et al.
Pubblicazione: (2022)

Dendrograms of Mixing Measures for Softmax-Gated Gaussian Mixture of Experts: Consistency without Model Sweeps
di: Hai, Do Tien, et al.
Pubblicazione: (2025)

Sample-Efficient Private Learning of Mixtures of Gaussians
di: Ashtiani, Hassan, et al.
Pubblicazione: (2024)

Structural Foundations for Leading Digit Laws: Beyond Probabilistic Mixtures
di: Berman, Vladimir
Pubblicazione: (2025)

Dynamic treatment effects: high-dimensional inference under model misspecification
di: Zhang, Yuqian, et al.
Pubblicazione: (2021)

Further Understanding of a Local Gaussian Process Approximation: Characterising Convergence in the Finite Regime
di: Stephenson, Anthony, et al.
Pubblicazione: (2024)

The Collusion of Memory and Nonlinearity in Stochastic Approximation With Constant Stepsize
di: Huo, Dongyan, et al.
Pubblicazione: (2024)

Exact Recovery of Community Detection in dependent Gaussian Mixture Models
di: Li, Zhongyang, et al.
Pubblicazione: (2022)

Robust Model Selection of Gaussian Graphical Models
di: Zahin, Abrar, et al.
Pubblicazione: (2022)

Variational Approach for Efficient KL Divergence Estimation in Dirichlet Mixture Models
di: Pal, Samyajoy, et al.
Pubblicazione: (2024)

Likelihood Matching for Diffusion Models
di: Qian, Lei, et al.
Pubblicazione: (2025)

Gaussian and Non-Gaussian Universality of Data Augmentation
di: Huang, Kevin Han, et al.
Pubblicazione: (2022)

A Piecewise Lyapunov Analysis of Sub-quadratic SGD: Applications to Robust and Quantile Regression
di: Zhang, Yixuan, et al.
Pubblicazione: (2025)

Smoothed SGD for quantiles: Bahadur representation and Gaussian approximation
di: Chen, Likai, et al.
Pubblicazione: (2025)

Mixture of multilayer stochastic block models for multiview clustering
di: De Santiago, Kylliann, et al.
Pubblicazione: (2024)

Higher-Order Causal Structure Learning with Additive Models
di: Enouen, James, et al.
Pubblicazione: (2025)

Estimating the Number of Components in Finite Mixture Models via Variational Approximation
di: Wang, Chenyang, et al.
Pubblicazione: (2024)

The Role of Pseudo-labels in Self-training Linear Classifiers on High-dimensional Gaussian Mixture Data
di: Takahashi, Takashi
Pubblicazione: (2022)

Bayesian Semiparametric Mixture Cure (Frailty) Models
di: Kızılaslan, Fatih, et al.
Pubblicazione: (2025)

An Overview of Diffusion Models: Applications, Guided Generation, Statistical Rates and Optimization
di: Chen, Minshuo, et al.
Pubblicazione: (2024)