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Estimating the Number of Components in Finite Mixture Models via the
  Group-Sort-Fuse Procedure
v1v2 (latest)

Estimating the Number of Components in Finite Mixture Models via the Group-Sort-Fuse Procedure

24 May 2020
Tudor Manole
Abbas Khalili
ArXiv (abs)PDFHTML

Papers citing "Estimating the Number of Components in Finite Mixture Models via the Group-Sort-Fuse Procedure"

8 / 8 papers shown
Statistical Perspective of Top-K Sparse Softmax Gating Mixture of
  Experts
Statistical Perspective of Top-K Sparse Softmax Gating Mixture of ExpertsInternational Conference on Learning Representations (ICLR), 2023
Huy Nguyen
Pedram Akbarian
Fanqi Yan
Nhat Ho
MoE
418
27
0
25 Sep 2023
Towards Convergence Rates for Parameter Estimation in Gaussian-gated
  Mixture of Experts
Towards Convergence Rates for Parameter Estimation in Gaussian-gated Mixture of ExpertsInternational Conference on Artificial Intelligence and Statistics (AISTATS), 2023
Huy Nguyen
TrungTin Nguyen
Khai Nguyen
Nhat Ho
MoE
398
24
0
12 May 2023
On Excess Mass Behavior in Gaussian Mixture Models with
  Orlicz-Wasserstein Distances
On Excess Mass Behavior in Gaussian Mixture Models with Orlicz-Wasserstein DistancesInternational Conference on Machine Learning (ICML), 2023
Aritra Guha
N. Ho
X. Nguyen
243
7
0
27 Jan 2023
Bayesian nonparametric mixture inconsistency for the number of
  components: How worried should we be in practice?
Bayesian nonparametric mixture inconsistency for the number of components: How worried should we be in practice?
Yannis Chaumeny
Johan Van der Molen Moris
A. Davison
Paul D. W. Kirk
294
3
0
29 Jul 2022
Estimation and inference for the Wasserstein distance between mixing
  measures in topic models
Estimation and inference for the Wasserstein distance between mixing measures in topic models
Xin Bing
F. Bunea
Jonathan Niles-Weed
391
6
0
26 Jun 2022
Beyond EM Algorithm on Over-specified Two-Component Location-Scale
  Gaussian Mixtures
Beyond EM Algorithm on Over-specified Two-Component Location-Scale Gaussian Mixtures
Zhaolin Ren
Fuheng Cui
Sujay Sanghavi
Nhat Ho
200
3
0
23 May 2022
Refined Convergence Rates for Maximum Likelihood Estimation under Finite
  Mixture Models
Refined Convergence Rates for Maximum Likelihood Estimation under Finite Mixture ModelsInternational Conference on Machine Learning (ICML), 2022
Tudor Manole
Nhat Ho
305
26
0
17 Feb 2022
Learning latent causal graphs via mixture oracles
Learning latent causal graphs via mixture oraclesNeural Information Processing Systems (NeurIPS), 2021
Bohdan Kivva
Goutham Rajendran
Pradeep Ravikumar
Bryon Aragam
CML
449
59
0
29 Jun 2021
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