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Poster
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Wed 16:30
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Decision-Focused Learning with Directional Gradients
Michael Huang · Vishal Gupta
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Poster
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Wed 11:00
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Guided Trajectory Generation with Diffusion Models for Offline Model-based Optimization
Taeyoung Yun · Sujin Yun · Jaewoo Lee · Jinkyoo Park
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Poster
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Thu 11:00
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Variational Multi-scale Representation for Estimating Uncertainty in 3D Gaussian Splatting
Ruiqi Li · Yiu-ming Cheung
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Poster
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Wed 11:00
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To Believe or Not to Believe Your LLM: Iterative Prompting for Estimating Epistemic Uncertainty
Yasin Abbasi Yadkori · Ilja Kuzborskij · András György · Csaba Szepesvari
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Poster
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Thu 16:30
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Stochastic Optimization Schemes for Performative Prediction with Nonconvex Loss
Qiang LI · Hoi-To Wai
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Poster
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Thu 11:00
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Deterministic Uncertainty Propagation for Improved Model-Based Offline Reinforcement Learning
Abdullah Akgül · Manuel Haussmann · Melih Kandemir
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Poster
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Wed 11:00
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Multi-Stage Predict+Optimize for (Mixed Integer) Linear Programs
Xinyi HU · Jasper Lee · Jimmy Lee · Peter Stuckey
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Poster
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Thu 16:30
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Contextual Linear Optimization with Bandit Feedback
Yichun Hu · Nathan Kallus · Xiaojie Mao · Yanchen Wu
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Poster
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Fri 16:30
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Mitigating Reward Overoptimization via Lightweight Uncertainty Estimation
Xiaoying Zhang · Jean-Francois Ton · Wei Shen · Hongning Wang · Yang Liu
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Poster
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Thu 11:00
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Energy-based Epistemic Uncertainty for Graph Neural Networks
Dominik Fuchsgruber · Tom Wollschläger · Stephan Günnemann
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Poster
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Wed 16:30
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Fair and Welfare-Efficient Constrained Multi-Matchings under Uncertainty
Elita Lobo · Justin Payan · Cyrus Cousins · Yair Zick
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Session
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Wed 11:00
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Creative Loss: Ambiguity, Uncertainty and Indeterminacy
Tom Holberton
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