ICML "knowledge transfer" Papers
12 papers found
A Statistical Theory of Regularization-Based Continual Learning
Xuyang Zhao, Huiyuan Wang, Weiran Huang et al.
ICML 2024poster
Enhancing Storage and Computational Efficiency in Federated Multimodal Learning for Large-Scale Models
Zixin Zhang, Fan Qi, Changsheng Xu
ICML 2024poster
Federated Continual Learning via Prompt-based Dual Knowledge Transfer
Hongming Piao, Yichen WU, Dapeng Wu et al.
ICML 2024poster
FlashST: A Simple and Universal Prompt-Tuning Framework for Traffic Prediction
Zhonghang Li, Lianghao Xia, Yong Xu et al.
ICML 2024oral
Knowledge Transfer from Vision Foundation Models for Efficient Training of Small Task-specific Models
Raviteja Vemulapalli, Hadi Pouransari, Fartash Faghri et al.
ICML 2024poster
Learning Causal Domain-Invariant Temporal Dynamics for Few-Shot Action Recognition
Yuke Li, Guangyi Chen, Ben Abramowitz et al.
ICML 2024oral
More Flexible PAC-Bayesian Meta-Learning by Learning Learning Algorithms
Hossein Zakerinia, Amin Behjati, Christoph Lampert
ICML 2024poster
Self-Composing Policies for Scalable Continual Reinforcement Learning
Mikel Malagón, Josu Ceberio, Jose A Lozano
ICML 2024poster
SF-DQN: Provable Knowledge Transfer using Successor Feature for Deep Reinforcement Learning
Shuai Zhang, Heshan Fernando, Miao Liu et al.
ICML 2024poster
Sparse Model Inversion: Efficient Inversion of Vision Transformers for Data-Free Applications
Zixuan Hu, Yongxian Wei, Li Shen et al.
ICML 2024poster
Tabular Insights, Visual Impacts: Transferring Expertise from Tables to Images
Jun-Peng Jiang, Han-Jia Ye, Leye Wang et al.
ICML 2024spotlight
Transferring Knowledge From Large Foundation Models to Small Downstream Models
Shikai Qiu, Boran Han, Danielle Robinson et al.
ICML 2024poster