ICML 2024 "supervised learning" Papers
8 papers found
Aligned Objective for Soft-Pseudo-Label Generation in Supervised Learning
Ning Xu, Yihao Hu, Congyu Qiao et al.
ICML 2024poster
ConvNet vs Transformer, Supervised vs CLIP: Beyond ImageNet Accuracy
Kirill Vishniakov, Zhiqiang Shen, Zhuang Liu
ICML 2024poster
Differentially Private Domain Adaptation with Theoretical Guarantees
Raef Bassily, Corinna Cortes, Anqi Mao et al.
ICML 2024poster
Fair Resource Allocation in Multi-Task Learning
Hao Ban, Kaiyi Ji
ICML 2024poster
Position: The No Free Lunch Theorem, Kolmogorov Complexity, and the Role of Inductive Biases in Machine Learning
Micah Goldblum, Marc Finzi, Keefer Rowan et al.
ICML 2024spotlight
60
citations
Rethinking Independent Cross-Entropy Loss For Graph-Structured Data
Rui Miao, Kaixiong Zhou, Yili Wang et al.
ICML 2024poster
When and How Does In-Distribution Label Help Out-of-Distribution Detection?
Xuefeng Du, Yiyou Sun, Sharon Li
ICML 2024poster
When is Transfer Learning Possible?
My Phan, Kianté Brantley, Stephanie Milani et al.
ICML 2024poster