ICML 2024 "mixture of experts" Papers
10 papers found
Acquiring Diverse Skills using Curriculum Reinforcement Learning with Mixture of Experts
Onur Celik, Aleksandar Taranovic, Gerhard Neumann
ICML 2024poster
A Provably Effective Method for Pruning Experts in Fine-tuned Sparse Mixture-of-Experts
Mohammed Nowaz Rabbani Chowdhury, Meng Wang, Kaoutar El Maghraoui et al.
ICML 2024poster
BECoTTA: Input-dependent Online Blending of Experts for Continual Test-time Adaptation
Daeun Lee, Jaehong Yoon, Sung Ju Hwang
ICML 2024poster
Exploring Training on Heterogeneous Data with Mixture of Low-rank Adapters
Yuhang Zhou, Zhao Zihua, Siyuan Du et al.
ICML 2024poster
Is Temperature Sample Efficient for Softmax Gaussian Mixture of Experts?
Huy Nguyen, Pedram Akbarian, Nhat Ho
ICML 2024poster
Merging Multi-Task Models via Weight-Ensembling Mixture of Experts
Anke Tang, Li Shen, Yong Luo et al.
ICML 2024poster
Mixtures of Experts Unlock Parameter Scaling for Deep RL
Johan Obando Ceron, Ghada Sokar, Timon Willi et al.
ICML 2024spotlight
On Least Square Estimation in Softmax Gating Mixture of Experts
Huy Nguyen, Nhat Ho, Alessandro Rinaldo
ICML 2024poster
Receptive Fields As Experts in Convolutional Neural Architectures
Dongze Lian, Weihao Yu, Xinchao Wang
ICML 2024poster
Scaling Laws for Fine-Grained Mixture of Experts
Jan Ludziejewski, Jakub Krajewski, Kamil Adamczewski et al.
ICML 2024poster