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Poster
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Fri 11:00
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Adaptive Labeling for Efficient Out-of-distribution Model Evaluation
Daksh Mittal · Yuanzhe Ma · Shalmali Joshi · Hongseok Namkoong
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Poster
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Fri 16:30
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TAIA: Large Language Models are Out-of-Distribution Data Learners
Shuyang Jiang · Yusheng Liao · Ya Zhang · Yanfeng Wang · Yu Wang
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Poster
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Thu 11:00
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Energy-based Hopfield Boosting for Out-of-Distribution Detection
Claus Hofmann · Simon Schmid · Bernhard Lehner · Daniel Klotz · Sepp Hochreiter
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Poster
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Wed 11:00
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Reconstruct and Match: Out-of-Distribution Robustness via Topological Homogeneity
Chaoqi Chen · Luyao Tang · Hui Huang
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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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Workshop
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Sat 15:45
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Taming False Positives in Out-of-Distribution Detection with Human Feedback
Harit Vishwakarma · Heguang Lin · Ramya Korlakai Vinayak
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Poster
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Fri 11:00
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Expecting The Unexpected: Towards Broad Out-Of-Distribution Detection
Charles Guille-Escuret · Pierre-André Noël · Ioannis Mitliagkas · David Vazquez · Joao Monteiro
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Workshop
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A Stochastic Algorithm for Sinkhorn Distance-Regularized Distributionally Robust Optimization
Yufeng Yang · Yi Zhou · Zhaosong Lu
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Workshop
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Sat 12:30
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Contributed Talk: Patrick O’Hara - Distributionally Robust Optimisation with Bayesian Ambiguity Sets
Patrick O'Hara
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Poster
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Fri 11:00
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Class Distribution Shifts in Zero-Shot Learning: Learning Robust Representations
Yuli Slavutsky · Yuval Benjamini
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Poster
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Fri 16:30
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Distributionally Robust Performative Prediction
Songkai Xue · Yuekai Sun
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Workshop
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Distributionally Robust Optimisation with Bayesian Ambiguity Sets
Harita Dellaporta · Patrick O'Hara · Theodoros Damoulas
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