Cover Image

On Computing Total Variation Distance Between Mixtures of Product Distributions

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Feng, Weiming, Fu, Yucheng, Yang, Minji, Zhang, Anqi
Format:	Preprint
Published:	2026
Subjects:	Data Structures and Algorithms Machine Learning Probability
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Approximating the Total Variation Distance between Gaussians
by: Bhattacharyya, Arnab, et al.
Published: (2025)

On approximating the $f$-divergence between two Ising models
by: Feng, Weiming, et al.
Published: (2025)

Rapid mixing in positively weighted restricted Boltzmann machines
by: Feng, Weiming, et al.
Published: (2026)

Approximating the total variation distance between spin systems
by: Feng, Weiming, et al.
Published: (2025)

Rapid Mixing of Glauber Dynamics for Monotone Systems via Entropic Independence
by: Feng, Weiming, et al.
Published: (2025)

Private Synthetic Graph Generation and Fused Gromov-Wasserstein Distance
by: Wirth, Leoni Carla, et al.
Published: (2025)

Adversarially-Robust Inference on Trees via Belief Propagation
by: Hopkins, Samuel B., et al.
Published: (2024)

A General Reduction for High-Probability Analysis with General Light-Tailed Distributions
by: Attia, Amit, et al.
Published: (2024)

Rapid Mixing via Coupling Independence for Spin Systems with Unbounded Degree
by: Chen, Xiaoyu, et al.
Published: (2024)

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

Improved sampling algorithms and functional inequalities for non-log-concave distributions
by: He, Yuchen, et al.
Published: (2025)

Distance Estimation for High-Dimensional Discrete Distributions
by: Kumar, Gunjan, et al.
Published: (2023)

Leaf Stripping on Uniform Attachment Trees
by: Addario-Berry, Louigi, et al.
Published: (2024)

Simple, unified analysis of Johnson-Lindenstrauss with applications
by: Li, Yingru
Published: (2024)

Efficiently learning and sampling multimodal distributions with data-based initialization
by: Koehler, Frederic, et al.
Published: (2024)

The graph alignment problem: fundamental limits and efficient algorithms
by: Ganassali, Luca
Published: (2024)

Computational and statistical lower bounds for low-rank estimation under general inhomogeneous noise
by: De, Debsurya, et al.
Published: (2025)

Learning CNF formulas from uniform random solutions in the local lemma regime
by: Feng, Weiming, et al.
Published: (2025)

Spectral Independence Beyond Total Influence on Trees and Related Graphs
by: Chen, Xiaoyu, et al.
Published: (2024)

Data organization limits the predictability of binary classification
by: Jing, Fei, et al.
Published: (2024)

The Transient Cost of Learning in Queueing Systems
by: Freund, Daniel, et al.
Published: (2023)

Quality control in sublinear time: a case study via random graphs
by: Marcussen, Cassandra, et al.
Published: (2025)

Computational and Statistical Hardness of Calibration Distance
by: Qiao, Mingda
Published: (2026)

Learning bounded-degree polytrees with known skeleton
by: Choo, Davin, et al.
Published: (2023)

Perspectives on Stochastic Localization
by: Shi, Bobby, et al.
Published: (2025)

Parallel Sampling via Autospeculation
by: Anari, Nima, et al.
Published: (2025)

Optimal Mixing for Randomly Sampling Edge Colorings on Trees Down to the Max Degree
by: Carlson, Charlie, et al.
Published: (2024)

Total Variation Distance Meets Probabilistic Inference
by: Bhattacharyya, Arnab, et al.
Published: (2023)

Functional Stochastic Localization
by: Gu, Anming, et al.
Published: (2026)

High-accuracy log-concave sampling with stochastic queries
by: Chen, Fan, et al.
Published: (2026)

A computational phase transition for learning-to-sample from Ising models
by: Risteski, Andrej, et al.
Published: (2026)

Well-Conditioned Oblivious Perturbations in Linear Space
by: Chenakkod, Shabarish, et al.
Published: (2026)

Universality of first-order methods on random and deterministic matrices
by: Gorini, Nicola, et al.
Published: (2026)

SCaLE: Switching Cost aware Learning and Exploration
by: Bhuyan, Neelkamal, et al.
Published: (2026)

A polynomial time iterative algorithm for matching Gaussian matrices with non-vanishing correlation
by: Ding, Jian, et al.
Published: (2022)

Complexity of High-Dimensional Identity Testing with Coordinate Conditional Sampling
by: Blanca, Antonio, et al.
Published: (2022)

Parallel Sampling via Counting
by: Anari, Nima, et al.
Published: (2024)

Nonlinear Laplacians: Tunable principal component analysis under directional prior information
by: Ma, Yuxin, et al.
Published: (2025)

Active Learning for Non-Parametric Choice Models
by: Susan, Fransisca, et al.
Published: (2022)

Orthogonal Nonnegative Matrix Factorization with Sparsity Constraints
by: Basiri, Salar, et al.
Published: (2022)