Statistical Advantages of Perturbing Cosine Router in Mixture of Experts
Fuente:
arXiv
Saved in:
| Main Authors: | Nguyen, Huy, Akbarian, Pedram, Pham, Trang, Nguyen, Trang, Zhang, Shujian, Ho, Nhat |
|---|---|
| Format: | Preprint |
| Published: |
2024
|
| 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)
Quadratic Gating Mixture of Experts: Statistical Insights into Self-Attention
by: Akbarian, Pedram, et al.
Published: (2024)
by: Akbarian, Pedram, et al.
Published: (2024)
Statistical Perspective of Top-K Sparse Softmax Gating Mixture of Experts
by: Nguyen, Huy, et al.
Published: (2023)
by: Nguyen, Huy, et al.
Published: (2023)
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)
Mixture of Experts Meets Prompt-Based Continual Learning
by: Le, Minh, et al.
Published: (2024)
by: Le, Minh, 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)
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)
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)
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 Parameter Estimation in Deviated Gaussian Mixture of Experts
by: Nguyen, Huy, et al.
Published: (2024)
by: Nguyen, Huy, 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)
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)
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)
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)
Attack On Prompt: Backdoor Attack in Prompt-Based Continual Learning
by: Nguyen, Trang, et al.
Published: (2024)
by: Nguyen, Trang, 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)
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)
FuseMoE: Mixture-of-Experts Transformers for Fleximodal Fusion
by: Han, Xing, et al.
Published: (2024)
by: Han, Xing, 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)
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)
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)
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)
CompeteSMoE -- Effective Training of Sparse Mixture of Experts via Competition
by: Pham, Quang, et al.
Published: (2024)
by: Pham, Quang, et al.
Published: (2024)
Improving Time Series Encoding with Noise-Aware Self-Supervised Learning and an Efficient Encoder
by: Nguyen, Duy A., et al.
Published: (2023)
by: Nguyen, Duy A., et al.
Published: (2023)
Revisit Visual Prompt Tuning: The Expressiveness of Prompt Experts
by: Le, Minh, et al.
Published: (2025)
by: Le, Minh, 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)
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)
Sliced Wasserstein with Random-Path Projecting Directions
by: Nguyen, Khai, et al.
Published: (2024)
by: Nguyen, Khai, et al.
Published: (2024)
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)
Robust Explainer Recommendation for Time Series Classification
by: Nguyen, Thu Trang, et al.
Published: (2023)
by: Nguyen, Thu Trang, et al.
Published: (2023)
Optimal Transport Aggregation for Distributed Mixture-of-Experts
by: Chamroukhi, Faïcel, et al.
Published: (2023)
by: Chamroukhi, Faïcel, et al.
Published: (2023)
Tree-Sliced Wasserstein Distance: A Geometric Perspective
by: Tran, Viet-Hoang, et al.
Published: (2024)
by: Tran, Viet-Hoang, 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)
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)
Lightspeed Geometric Dataset Distance via Sliced Optimal Transport
by: Nguyen, Khai, et al.
Published: (2025)
by: Nguyen, Khai, 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)
Load Balancing Mixture of Experts with Similarity Preserving Routers
by: Omi, Nabil, et al.
Published: (2025)
by: Omi, Nabil, et al.
Published: (2025)
Fast Estimation of Wasserstein Distances via Regression on Sliced Wasserstein Distances
by: Nguyen, Khai, et al.
Published: (2025)
by: Nguyen, Khai, et al.
Published: (2025)
Coupling Experts and Routers in Mixture-of-Experts via an Auxiliary Loss
by: Lv, Ang, et al.
Published: (2025)
by: Lv, Ang, et al.
Published: (2025)
Similar Items
-
Is Temperature Sample Efficient for Softmax Gaussian Mixture of Experts?
by: Nguyen, Huy, et al.
Published: (2024) -
Quadratic Gating Mixture of Experts: Statistical Insights into Self-Attention
by: Akbarian, Pedram, et al.
Published: (2024) -
Statistical Perspective of Top-K Sparse Softmax Gating Mixture of Experts
by: Nguyen, Huy, et al.
Published: (2023) -
A General Theory for Softmax Gating Multinomial Logistic Mixture of Experts
by: Nguyen, Huy, et al.
Published: (2023) -
Mixture of Experts Meets Prompt-Based Continual Learning
by: Le, Minh, et al.
Published: (2024)