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NeurIPS 2026OralUniversitys of Waterloo U Waterloo Stanford Yale Semi- & weakly supervised learning

Surprises in Proper Positive-Only Learning

Shai Ben-David, Farnam Mansouri, Anay Mehrotra, Manolis Zampetakis

Sydney Poster Session 1, Tue, Dec 8, 10:00 AM–1:00 PM, Hall 1-4 · Published 2026

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NeurIPS 2026Stanford Semi- & weakly supervised learning

Partially Performative Prediction

Jaewook Lee, Tijana Zrnic

Sydney Poster Session 2, Tue, Dec 8, 5:00 PM–8:00 PM, Hall 1-4 · Published 2026

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NeurIPS 2026U Toronto TELUS Communications Semi- & weakly supervised learning

Integrated Imputation-Classification for Supervised Learning with Missing Data

Yue Liu, Ben Liang, Ali Tizghadam, Ilijc Albanese

Sydney Poster Session 5, Thu, Dec 10, 10:00 AM–1:00 PM, Hall 1-4 · Published 2026

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NeurIPS 2026Beijing Jiaotong Communication University of Chin Semi- & weakly supervised learning

Decoupled Optimization for Teacher-Student Semi-Supervised Learning via a Pioneer Student

Haorong Han, Jidong Yuan, Chixuan Wei, Yongqi Sun

Sydney Poster Session 3, Wed, Dec 9, 10:00 AM–1:00 PM, Hall 1-4 · Published 2026

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NeurIPS 2026VinUniversity CAIR, VinUniversity Semi- & weakly supervised learning

Trajectory-Matching Meta Pseudo-Labeling for Semi-Supervised Learning

Minh Duc Le, Minh-Duong Nguyen, Dung Le

Sydney Poster Session 1, Tue, Dec 8, 10:00 AM–1:00 PM, Hall 1-4 · Published 2026

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NeurIPS 2026U Tokyo RIKEN The University of Tokyo / RIKEN The University of Tokyo; RIKEN A RIKEN/University of Tokyo Semi- & weakly supervised learning

Rethinking Learning from Label Proportions via Moment Matching

Tianhao Ma, Wei Wang, Yivan Zhang, Dong-Dong Wu and 3 more

Sydney Poster Session 1, Tue, Dec 8, 10:00 AM–1:00 PM, Hall 1-4 · Published 2026

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NeurIPS 2026Southeast Chinese Academy of Sciences Tsinghua Shenzhen Institute of Advanced T U Arizona Semi- & weakly supervised learning

Seen-Constrained Model-Order Selection for Unknown-$K$ Generalized Category Discovery

Mingfu Yan, Jiancheng Huang, HAIPENG LUO, Yi Huang and 3 more

Sydney Poster Session 6, Thu, Dec 10, 5:00 PM–8:00 PM, Hall 1-4 · Published 2026

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NeurIPS 2026Southeast Caritas Institute of Higher Educ City University of Hong Kong, Ho Semi- & weakly supervised learning

Exploiting Negative Multi-Cluster Structure in Class-Wise Embeddings for Weakly Supervised Multi-Label Learning

Bo Han, Zhuoming Li, Yaxin Hou, Xiaoyu Wang and 3 more

Sydney Poster Session 3, Wed, Dec 9, 10:00 AM–1:00 PM, Hall 1-4 · Published 2026

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NeurIPS 2026Nankai Shanghai Jiaotong Semi- & weakly supervised learning

Resilient Semi-Supervised Inference with Heterogeneous Unlabeled Data

Mengyuan Wang, Chengde Qian, Haojie Ren, Changliang Zou

Sydney Poster Session 2, Tue, Dec 8, 5:00 PM–8:00 PM, Hall 1-4 · Published 2026

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NeurIPS 2026OralShanxi University, School of Co Shanxi University School of Comp Shanxi Shanxi university Semi- & weakly supervised learning

Mitigating Confidence Miscalibration in Open-World Semi-Supervised Learning

Wenqiang Wu, Feng Wang, Jiye Liang, Liang Bai

Sydney Poster Session 6, Thu, Dec 10, 5:00 PM–8:00 PM, Hall 1-4 · Published 2026

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NeurIPS 2026Southern university of science a The Chinese University of Hong K Mohamed bin Zayed University of U Electronic Science and Technol zzmc@scut.edu.cn Semi- & weakly supervised learning

Provable Selective Auto-labeling with Reliability Guarantees

Huipeng Huang, Wenbo Liao, Huajun Xi, Hao Zeng and 2 more

Sydney Poster Session 1, Tue, Dec 8, 10:00 AM–1:00 PM, Hall 1-4 · Published 2026

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NeurIPS 2026Vrije Universiteit Brussel Ataraxis.ai Hasselt Semi- & weakly supervised learning

Estimating Continuous Treatment Effects with Recourse Data

Alessandro Marchese, Jeroen Berrevoets, Niels Martin, Sam Verboven

Sydney Poster Session 2, Tue, Dec 8, 5:00 PM–8:00 PM, Hall 1-4 · Published 2026

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NeurIPS 2026U Western Ontario Semi- & weakly supervised learning

Dual-Granularity Learning for Regression with Continuous Noisy Labels

Hui GUO, Boyu Wang, Grace Yi

Atlanta Poster Session 3, Thu, Dec 10, 10:00 AM–1:00 PM, Hall C1 · Published 2026

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NeurIPS 2026U Würzburg Julius-Maximilians-Universität W KU Leuven Semi- & weakly supervised learning

Online Decision-Focused Learning under Semi-Bandit Feedback

Aabhash Dhakal, Tim Lachner, Jayanta Mandi, Marco Foschini and 1 more

Sydney Poster Session 2, Tue, Dec 8, 5:00 PM–8:00 PM, Hall 1-4 · Published 2026

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NeurIPS 2026Tsinghua Shenzhen International Tsinghua Nanyang Technological Great Bay Shenzhen Semi- & weakly supervised learning

View Confidence Perception-Driven Incremental Prediction for Incomplete Multi-view Multi-label Learning

Pingzhu Liu, Chunming He, Zunnan Xu, Zhirui Fang and 3 more

Sydney Poster Session 3, Wed, Dec 9, 10:00 AM–1:00 PM, Hall 1-4 · Published 2026

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71%Highly rated

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NeurIPS 2026KU Leuven Semi- & weakly supervised learning

EM-NeSy: Expectation Maximization for Neurosymbolic Learning

EM-NeSy casts neurosymbolic learning as expectation-maximization to enable approximate symbolic reasoning without requiring differentiable reasoning components.

Annegret Seibt, Luc De Raedt, Giuseppe Marra

Paris Poster Session 1, Wed, Dec 9, 12:30 PM–2:30 PM, Paris Poster Hall · Published 2026

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7/20 AI panelreviewers recommend it

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80%Must read

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NeurIPS 2026Queen Mary University London Amazon Utrecht Semi- & weakly supervised learning

An Assessment of Human vs. Model Uncertainty in Soft-Label Learning and Calibration

Human soft-labels improve calibration and training stability by regularizing models and mirroring human uncertainty, mainly via regularization rather than correcting mislabeled data.

Maja Pavlovic, Silviu Paun, Massimo Poesio

Sydney Poster Session 6, Thu, Dec 10, 5:00 PM–8:00 PM, Hall 1-4 · Published 2026

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AI panel: 12 of 20 reviewers recommend it

lenient 4/5

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83%Must read

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