"supervised learning" Papers

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Paper Type

poster (24,624)paper (8,558)oral (1,594)spotlight (1,421)highlight (975)

Agnostic Active Learning Is Always Better Than Passive Learning

Steve Hanneke

NEURIPS 2025oral

AIMS.au: A Dataset for the Analysis of Modern Slavery Countermeasures in Corporate Statements

Adriana-Eufrosina Bora, Pierre-Luc St-Charles, Mirko Bronzi et al.

ICLR 2025arXiv:2502.07022
2
citations

Learning Juntas under Markov Random Fields

Gautam Chandrasekaran, Adam Klivans

NEURIPS 2025arXiv:2506.00764
1
citations

Specialized Foundation Models Struggle to Beat Supervised Baselines

Zongzhe Xu, Ritvik Gupta, Wenduo Cheng et al.

ICLR 2025arXiv:2411.02796
24
citations

WardropNet: Traffic Flow Predictions via Equilibrium-Augmented Learning

Kai Jungel, Dario Paccagnan, Axel Parmentier et al.

ICLR 2025arXiv:2410.06656
3
citations

Aligned Objective for Soft-Pseudo-Label Generation in Supervised Learning

Ning Xu, Yihao Hu, Congyu Qiao et al.

ICML 2024

ConvNet vs Transformer, Supervised vs CLIP: Beyond ImageNet Accuracy

Kirill Vishniakov, Zhiqiang Shen, Zhuang Liu

ICML 2024arXiv:2311.09215
26
citations

Differentially Private Domain Adaptation with Theoretical Guarantees

Raef Bassily, Corinna Cortes, Anqi Mao et al.

ICML 2024arXiv:2306.08838

Fair Resource Allocation in Multi-Task Learning

Hao Ban, Kaiyi Ji

ICML 2024arXiv:2402.15638
35
citations

Leveraging Imperfect Restoration for Data Availability Attack

YI HUANG, Jeremy Styborski, Mingzhi Lyu et al.

ECCV 2024
1
citations

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

Real-Fake: Effective Training Data Synthesis Through Distribution Matching

Jianhao Yuan, Jie Zhang, Shuyang Sun et al.

ICLR 2024arXiv:2310.10402
45
citations

Rethinking Independent Cross-Entropy Loss For Graph-Structured Data

Rui Miao, Kaixiong Zhou, Yili Wang et al.

ICML 2024arXiv:2405.15564
5
citations

When and How Does In-Distribution Label Help Out-of-Distribution Detection?

Xuefeng Du, Yiyou Sun, Sharon Li

ICML 2024arXiv:2405.18635
11
citations

When is Transfer Learning Possible?

My Phan, Kianté Brantley, Stephanie Milani et al.

ICML 2024