Statistical Perspective of Top-K Sparse Softmax Gating Mixture of Experts
Fuente:
arXiv
Saved in:
| Main Authors: | Nguyen, Huy, Akbarian, Pedram, Yan, Fanqi, Ho, Nhat |
|---|---|
| Format: | Preprint |
| Published: |
2023
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
Is Temperature Sample Efficient for Softmax Gaussian Mixture of Experts?
by: Nguyen, Huy, et al.
Published: (2024)
by: Nguyen, Huy, et al.
Published: (2024)
A General Theory for Softmax Gating Multinomial Logistic Mixture of Experts
by: Nguyen, Huy, et al.
Published: (2023)
by: Nguyen, Huy, et al.
Published: (2023)
Sigmoid Self-Attention has Lower Sample Complexity than Softmax Self-Attention: A Mixture-of-Experts Perspective
by: Yan, Fanqi, et al.
Published: (2025)
by: Yan, Fanqi, et al.
Published: (2025)
On Minimax Estimation of Parameters in Softmax-Contaminated Mixture of Experts
by: Yan, Fanqi, et al.
Published: (2025)
by: Yan, Fanqi, et al.
Published: (2025)
Quadratic Gating Mixture of Experts: Statistical Insights into Self-Attention
by: Akbarian, Pedram, et al.
Published: (2024)
by: Akbarian, Pedram, et al.
Published: (2024)
Understanding Expert Structures on Minimax Parameter Estimation in Contaminated Mixture of Experts
by: Yan, Fanqi, et al.
Published: (2024)
by: Yan, Fanqi, et al.
Published: (2024)
Convergence Rates for Softmax Gating Mixture of Experts
by: Nguyen, Huy, et al.
Published: (2025)
by: Nguyen, Huy, et al.
Published: (2025)
On Least Square Estimation in Softmax Gating Mixture of Experts
by: Nguyen, Huy, et al.
Published: (2024)
by: Nguyen, Huy, et al.
Published: (2024)
Statistical Advantages of Perturbing Cosine Router in Mixture of Experts
by: Nguyen, Huy, et al.
Published: (2024)
by: Nguyen, Huy, et al.
Published: (2024)
Sigmoid Gating is More Sample Efficient than Softmax Gating in Mixture of Experts
by: Nguyen, Huy, et al.
Published: (2024)
by: Nguyen, Huy, et al.
Published: (2024)
On Bayesian Softmax-Gated Mixture-of-Experts Models
by: Bariletto, Nicola, et al.
Published: (2026)
by: Bariletto, Nicola, et al.
Published: (2026)
On Expert Estimation in Hierarchical Mixture of Experts: Beyond Softmax Gating Functions
by: Nguyen, Huy, et al.
Published: (2024)
by: Nguyen, Huy, et al.
Published: (2024)
Improving Minimax Estimation Rates for Contaminated Mixture of Multinomial Logistic Experts via Expert Heterogeneity
by: Yan, Fanqi, et al.
Published: (2026)
by: Yan, Fanqi, et al.
Published: (2026)
A Statistical Theory of Gated Attention through the Lens of Hierarchical Mixture of Experts
by: Nguyen, Viet, et al.
Published: (2026)
by: Nguyen, Viet, et al.
Published: (2026)
On Parameter Estimation in Deviated Gaussian Mixture of Experts
by: Nguyen, Huy, et al.
Published: (2024)
by: Nguyen, Huy, et al.
Published: (2024)
Rethinking Multinomial Logistic Mixture of Experts with Sigmoid Gating Function
by: Pham, Tuan Minh, et al.
Published: (2026)
by: Pham, Tuan Minh, et al.
Published: (2026)
Dendrograms of Mixing Measures for Softmax-Gated Gaussian Mixture of Experts: Consistency without Model Sweeps
by: Hai, Do Tien, et al.
Published: (2025)
by: Hai, Do Tien, et al.
Published: (2025)
Fast Model Selection and Stable Optimization for Softmax-Gated Multinomial-Logistic Mixture of Experts Models
by: Tran, TrungKhang, et al.
Published: (2026)
by: Tran, TrungKhang, et al.
Published: (2026)
Towards Convergence Rates for Parameter Estimation in Gaussian-gated Mixture of Experts
by: Nguyen, Huy, et al.
Published: (2023)
by: Nguyen, Huy, et al.
Published: (2023)
One-Prompt Strikes Back: Sparse Mixture of Experts for Prompt-based Continual Learning
by: Le, Minh, et al.
Published: (2025)
by: Le, Minh, et al.
Published: (2025)
RepLoRA: Reparameterizing Low-Rank Adaptation via the Perspective of Mixture of Experts
by: Truong, Tuan, et al.
Published: (2025)
by: Truong, Tuan, et al.
Published: (2025)
On DeepSeekMoE: Statistical Benefits of Shared Experts and Normalized Sigmoid Gating
by: Nguyen, Huy, et al.
Published: (2025)
by: Nguyen, Huy, et al.
Published: (2025)
FuseMoE: Mixture-of-Experts Transformers for Fleximodal Fusion
by: Han, Xing, et al.
Published: (2024)
by: Han, Xing, et al.
Published: (2024)
Mixture of Experts Meets Prompt-Based Continual Learning
by: Le, Minh, et al.
Published: (2024)
by: Le, Minh, et al.
Published: (2024)
CompeteSMoE -- Effective Training of Sparse Mixture of Experts via Competition
by: Pham, Quang, et al.
Published: (2024)
by: Pham, Quang, et al.
Published: (2024)
Modeling Expert Interactions in Sparse Mixture of Experts via Graph Structures
by: Nguyen-Nhat, Minh-Khoi, et al.
Published: (2025)
by: Nguyen-Nhat, Minh-Khoi, et al.
Published: (2025)
Expert Merging in Sparse Mixture of Experts with Nash Bargaining
by: Nguyen, Dung V., et al.
Published: (2025)
by: Nguyen, Dung V., et al.
Published: (2025)
Revisiting Prefix-tuning: Statistical Benefits of Reparameterization among Prompts
by: Le, Minh, et al.
Published: (2024)
by: Le, Minh, et al.
Published: (2024)
Revisit Visual Prompt Tuning: The Expressiveness of Prompt Experts
by: Le, Minh, et al.
Published: (2025)
by: Le, Minh, et al.
Published: (2025)
On Zero-Initialized Attention: Optimal Prompt and Gating Factor Estimation
by: Diep, Nghiem T., et al.
Published: (2025)
by: Diep, Nghiem T., et al.
Published: (2025)
Improving Routing in Sparse Mixture of Experts with Graph of Tokens
by: Nguyen, Tam, et al.
Published: (2025)
by: Nguyen, Tam, et al.
Published: (2025)
Selective Sinkhorn Routing for Improved Sparse Mixture of Experts
by: Nguyen, Duc Anh, et al.
Published: (2025)
by: Nguyen, Duc Anh, et al.
Published: (2025)
Model Selection for Gaussian-gated Gaussian Mixture of Experts Using Dendrograms of Mixing Measures
by: Thai, Tuan, et al.
Published: (2025)
by: Thai, Tuan, et al.
Published: (2025)
Adaptive Sparse Softmax: An Effective and Efficient Softmax Variant
by: Lv, Qi, et al.
Published: (2025)
by: Lv, Qi, et al.
Published: (2025)
From Top-1 to Top-K: A Reproducibility Study and Benchmarking of Counterfactual Explanations for Recommender Systems
by: Nguyen, Quang-Huy, et al.
Published: (2026)
by: Nguyen, Quang-Huy, et al.
Published: (2026)
Gaussian Process-Gated Hierarchical Mixtures of Experts
by: Liu, Yuhao, et al.
Published: (2023)
by: Liu, Yuhao, et al.
Published: (2023)
CompeteSMoE -- Statistically Guaranteed Mixture of Experts Training via Competition
by: Nguyen, Nam V., et al.
Published: (2025)
by: Nguyen, Nam V., et al.
Published: (2025)
Optimal Transport Aggregation for Distributed Mixture-of-Experts
by: Chamroukhi, Faïcel, et al.
Published: (2023)
by: Chamroukhi, Faïcel, et al.
Published: (2023)
On the Role of Discrete Representation in Sparse Mixture of Experts
by: Do, Giang, et al.
Published: (2024)
by: Do, Giang, et al.
Published: (2024)
BatchTopK Sparse Autoencoders
by: Bussmann, Bart, et al.
Published: (2024)
by: Bussmann, Bart, et al.
Published: (2024)
Similar Items
-
Is Temperature Sample Efficient for Softmax Gaussian Mixture of Experts?
by: Nguyen, Huy, et al.
Published: (2024) -
A General Theory for Softmax Gating Multinomial Logistic Mixture of Experts
by: Nguyen, Huy, et al.
Published: (2023) -
Sigmoid Self-Attention has Lower Sample Complexity than Softmax Self-Attention: A Mixture-of-Experts Perspective
by: Yan, Fanqi, et al.
Published: (2025) -
On Minimax Estimation of Parameters in Softmax-Contaminated Mixture of Experts
by: Yan, Fanqi, et al.
Published: (2025) -
Quadratic Gating Mixture of Experts: Statistical Insights into Self-Attention
by: Akbarian, Pedram, et al.
Published: (2024)