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Poster
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Wed 8:45
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Partial Multi-Label Learning with Probabilistic Graphical Disambiguation
Jun-Yi Hang · Min-Ling Zhang
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Workshop
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Turn Down the Noise: Leveraging Diffusion Models for Test-time Adaptation via Pseudo-label Ensembling
Mrigank Raman · Rohan Shah · Akash Kannan · Pranit Chawla
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Poster
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Wed 8:45
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HQA-Attack: Toward High Quality Black-Box Hard-Label Adversarial Attack on Text
Han Liu · Zhi Xu · Xiaotong Zhang · Feng Zhang · Fenglong Ma · Hongyang Chen · Hong Yu · Xianchao Zhang
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Poster
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Wed 8:45
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SLaM: Student-Label Mixing for Distillation with Unlabeled Examples
Vasilis Kontonis · Fotis Iliopoulos · Khoa Trinh · Cenk Baykal · Gaurav Menghani · Erik Vee
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Poster
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Wed 8:45
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Disambiguated Attention Embedding for Multi-Instance Partial-Label Learning
Wei Tang · Weijia Zhang · Min-Ling Zhang
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Workshop
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Bandit-Driven Batch Selection for Robust Learning under Label Noise
Michal Lisicki · Mihai Nica · Graham Taylor
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Workshop
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Preparation Of Labeled Cryo-ET Datasets For Training And Evaluation Of Machine Learning Models
Aygul Ishemgulova · Alex J. Noble · Tristan Bepler · Alex De Marco
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Affinity Workshop
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Mon 13:30
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Deep Learning from Crowdsourced Labels with Identifiability Guarantees
Shahana Ibrahim · Tri Nguyen · Xiao Fu
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Poster
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Thu 8:45
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Efficient Testable Learning of Halfspaces with Adversarial Label Noise
Ilias Diakonikolas · Daniel Kane · Vasilis Kontonis · Sihan Liu · Nikos Zarifis
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Workshop
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On the Synergy Between Label Noise and Learning Rate Annealing in Neural Network Training
Stanley Wei · Tongzheng Ren · Simon Du
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Poster
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Tue 15:15
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Scale-teaching: Robust Multi-scale Training for Time Series Classification with Noisy Labels
Zhen Liu · ma peitian · Dongliang Chen · Wenbin Pei · Qianli Ma
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Workshop
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Flowering Onset Detection: Deep Learning Performance in a Sparse Label Context
Joel Hempel · Mauricio Soroco · Xinze Xiong · Joséphine Gantois · Mathias Lécuyer
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