2024 "feature learning" Papers
10 papers found
Asymptotics of feature learning in two-layer networks after one gradient-step
Hugo Cui, Luca Pesce, Yatin Dandi et al.
ICML 2024spotlightarXiv:2402.04980
A Theory of Non-Linear Feature Learning with One Gradient Step in Two-Layer Neural Networks
Behrad Moniri, Donghwan Lee, Hamed Hassani et al.
ICML 2024posterarXiv:2310.07891
Catapults in SGD: spikes in the training loss and their impact on generalization through feature learning
Libin Zhu, Chaoyue Liu, Adityanarayanan Radhakrishnan et al.
ICML 2024posterarXiv:2306.04815
Diffusion Models Demand Contrastive Guidance for Adversarial Purification to Advance
Mingyuan Bai, Wei Huang, Li Tenghui et al.
ICML 2024poster
LoRA+: Efficient Low Rank Adaptation of Large Models
Soufiane Hayou, Nikhil Ghosh, Bin Yu
ICML 2024posterarXiv:2402.12354
Mean-field Analysis on Two-layer Neural Networks from a Kernel Perspective
Shokichi Takakura, Taiji Suzuki
ICML 2024posterarXiv:2403.14917
Mean Field Langevin Actor-Critic: Faster Convergence and Global Optimality beyond Lazy Learning
Kakei Yamamoto, Kazusato Oko, Zhuoran Yang et al.
ICML 2024oral
Provable Benefits of Local Steps in Heterogeneous Federated Learning for Neural Networks: A Feature Learning Perspective
Yajie Bao, Michael Crawshaw, Mingrui Liu
ICML 2024poster
Provable Multi-Task Representation Learning by Two-Layer ReLU Neural Networks
Liam Collins, Hamed Hassani, Mahdi Soltanolkotabi et al.
ICML 2024posterarXiv:2307.06887
Provably Neural Active Learning Succeeds via Prioritizing Perplexing Samples
Dake Bu, Wei Huang, Taiji Suzuki et al.
ICML 2024posterarXiv:2406.03944