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Workshop
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AdapTable: Test-Time Adaptation for Tabular Data via Shift-Aware Uncertainty Calibrator and Label Distribution Handler
Changhun Kim · Taewon Kim · Seungyeon Woo · June Yong Yang · Eunho Yang
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Workshop
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DivShift: Exploring Domain-Specific Distribution Shift in Large-Scale, Volunteer-Collected Biodiversity Datasets
Elena Sierra · Lauren Gillespie · Salim Soltani · Moisés Expósito-Alonso · Teja Kattenborn
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Workshop
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Drift-Resilient TabPFN: In-Context Learning Temporal Distribution Shifts on Tabular Data
David Schnurr · Kai Helli · Noah Hollmann · Samuel Müller · Frank Hutter
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Poster
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Thu 16:30
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Efficient Discrepancy Testing for Learning with Distribution Shift
Gautam Chandrasekaran · Adam Klivans · Vasilis Kontonis · Konstantinos Stavropoulos · Arsen Vasilyan
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Workshop
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Task-Relevant Covariance from Manifold Capacity Theory Improves Robustness in Deep Networks
William Yang · Chi-Ning Chou · SueYeon Chung
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Poster
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Thu 11:00
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Label Alignment Regularization for Distribution Shift
Ehsan Imani · Guojun Zhang · Runjia Li · Jun Luo · Pascal Poupart · Philip Torr · Yangchen Pan
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Poster
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Fri 11:00
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Achievable distributional robustness when the robust risk is only partially identified
Julia Kostin · Nicola Gnecco · Fanny Yang
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Poster
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Gradual Domain Adaptation via Manifold-Constrained Distributionally Robust Optimization
seyed amir saberi · Amir Najafi · Amin Behjati · Ala Emrani · Yasaman Zolfimoselo · Shadrooy · Abolfazl Motahari · Babak Khalaj
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Workshop
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LLM Embeddings Improve Test-time Adaptation to Tabular Y|X-Shifts
Yibo Zeng · Jiashuo Liu · Henry Lam · Hongseok Namkoong
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Poster
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Wed 11:00
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Drift-Resilient TabPFN: In-Context Learning Temporal Distribution Shifts on Tabular Data
Kai Helli · David Schnurr · Noah Hollmann · Samuel Müller · Frank Hutter
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Poster
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Thu 11:00
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Bridging Multicalibration and Out-of-distribution Generalization Beyond Covariate Shift
Jiayun Wu · Jiashuo Liu · Peng Cui · Steven Wu
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Workshop
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Sun 9:30
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Lightning Talk: Compositional Generalization Across Distributional Shifts with Sparse Tree Operations
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