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Workshop
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Incentivizing Honesty among Competitors in Collaborative Learning
Florian Dorner · Nikola Konstantinov · Georgi Pashaliev · Martin Vechev
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Poster
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Thu 16:30
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Learning Regions of Interest for Bayesian Optimization with Adaptive Level-Set Estimation
Fengxue Zhang · Jialin Song · James Bowden · Alexander Ladd · Yisong Yue · Thomas Desautels · Yuxin Chen
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Workshop
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Learning to Optimize Non-Convex Sum-Rate Maximization Problems
Qingyu Song · Guochen Liu · Hong Xu
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Workshop
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MOLE: MOdular Learning FramEwork via Mutual Information Maximization
Tianchao Li · Yulong Pei
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Poster
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Thu 16:30
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Representation Learning with Multi-Step Inverse Kinematics: An Efficient and Optimal Approach to Rich-Observation RL
Zakaria Mhammedi · Dylan Foster · Alexander Rakhlin
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Oral
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Tue 20:54
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Representation Learning with Multi-Step Inverse Kinematics: An Efficient and Optimal Approach to Rich-Observation RL
Zakaria Mhammedi · Dylan Foster · Alexander Rakhlin
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Poster
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Wed 17:00
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Simplifying Momentum-based Positive-definite Submanifold Optimization with Applications to Deep Learning
Wu Lin · Valentin Duruisseaux · Melvin Leok · Frank Nielsen · Khan Emtiyaz · Mark Schmidt
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Poster
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Thu 13:30
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The Power of Learned Locally Linear Models for Nonlinear Policy Optimization
Daniel Pfrommer · Max Simchowitz · Tyler Westenbroek · Nikolai Matni · Stephen Tu
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Workshop
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Mathematical Theory of Adversarial Deep Learning
Xiao-Shan Gao · Lijia Yu · Shuang Liu
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Poster
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Thu 13:30
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PFNs4BO: In-Context Learning for Bayesian Optimization
Samuel Gabriel Müller · Matthias Feurer · Noah Hollmann · Frank Hutter
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Workshop
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Learning Observation Models with Incremental Non-Differentiable Graph Optimizers in the Loop for Robotics State Estimation
Mohamad Qadri · Michael Kaess
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Workshop
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Improving and Generalizing Flow-Based Generative Models with Minibatch Optimal Transport
Alexander Tong · Nikolay Malkin · Guillaume Huguet · Yanlei Zhang · Jarrid Rector-Brooks · Kilian Fatras · Guy Wolf · Yoshua Bengio
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