2 citations · 3 across the 7 of their papers we have counts for
9 papers
ExpertMuon-Compass: Alignment-Guided Step Sizes for Mixture-of-Experts Training
Omatharv Bharat Vaidya, Ashwin Vinod, Pedram Akbarian +3
Mixture-of-experts (MoE) language models send each token to a few experts, so each expert is trained on a different part of the data, and this part changes during training. With a…
On Minimax Estimation of Parameters in Softmax-Contaminated Mixture of Experts
Fanqi Yan, Huy Nguyen, Dung Le +3
The softmax-contaminated mixture of experts (MoE) model is deployed when a large-scale pre-trained model, which plays the role of a fixed expert, is fine-tuned for learning downstr…
Sigmoid Self-Attention has Lower Sample Complexity than Softmax Self-Attention: A Mixture-of-Experts Perspective
Fanqi Yan, Huy Nguyen, Pedram Akbarian +2
At the core of the popular Transformer architecture is the self-attention mechanism, which dynamically assigns softmax weights to each input token so that the model can focus on th…
Understanding Expert Structures on Minimax Parameter Estimation in Contaminated Mixture of Experts
Fanqi Yan, Huy Nguyen, Dung Le +2
We conduct the convergence analysis of parameter estimation in the contaminated mixture of experts. This model is motivated from the prompt learning problem where ones utilize prom…
Quadratic Gating Mixture of Experts: Statistical Insights into Self-Attention
Pedram Akbarian, Huy Nguyen, Xing Han +1
Mixture of Experts (MoE) models are well known for effectively scaling model capacity while preserving computational overheads. In this paper, we establish a rigorous relation betw…
Statistical Advantages of Perturbing Cosine Router in Mixture of Experts
Huy Nguyen, Pedram Akbarian, Trang Pham +3
The cosine router in Mixture of Experts (MoE) has recently emerged as an attractive alternative to the conventional linear router. Indeed, the cosine router demonstrates favorable…
Is Temperature Sample Efficient for Softmax Gaussian Mixture of Experts?
Huy Nguyen, Pedram Akbarian, Nhat Ho
Dense-to-sparse gating mixture of experts (MoE) has recently become an effective alternative to a well-known sparse MoE. Rather than fixing the number of activated experts as in th…
A General Theory for Softmax Gating Multinomial Logistic Mixture of Experts
Huy Nguyen, Pedram Akbarian, TrungTin Nguyen +1
Mixture-of-experts (MoE) model incorporates the power of multiple submodels via gating functions to achieve greater performance in numerous regression and classification applicatio…
Statistical Perspective of Top-K Sparse Softmax Gating Mixture of Experts
Huy Nguyen, Pedram Akbarian, Fanqi Yan +1
Top-K sparse softmax gating mixture of experts has been widely used for scaling up massive deep-learning architectures without increasing the computational cost. Despite its popula…