2024 Poster "knowledge transfer" Papers

13 papers found

A Statistical Theory of Regularization-Based Continual Learning

Xuyang Zhao, Huiyuan Wang, Weiran Huang et al.

ICML 2024poster

Encapsulating Knowledge in One Prompt

Qi Li, Runpeng Yu, Xinchao Wang

ECCV 2024posterarXiv:2407.11902
3
citations

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

Knowledge Transfer from Vision Foundation Models for Efficient Training of Small Task-specific Models

Raviteja Vemulapalli, Hadi Pouransari, Fartash Faghri et al.

ICML 2024poster

Knowledge Transfer with Simulated Inter-Image Erasing for Weakly Supervised Semantic Segmentation

Tao Chen, Xiruo Jiang, Gensheng Pei et al.

ECCV 2024posterarXiv:2407.02768
17
citations

Learn from the Learnt: Source-Free Active Domain Adaptation via Contrastive Sampling and Visual Persistence

Mengyao Lyu, Tianxiang Hao, Xinhao Xu et al.

ECCV 2024posterarXiv:2407.18899
10
citations

Learning to Adapt SAM for Segmenting Cross-domain Point Clouds

Xidong Peng, Runnan Chen, Feng Qiao et al.

ECCV 2024posterarXiv:2310.08820
21
citations

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

Transferring Knowledge From Large Foundation Models to Small Downstream Models

Shikai Qiu, Boran Han, Danielle Robinson et al.

ICML 2024poster