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cs.RO2026
Memorize, Adapt, Ignore: Diagnosing Robot Learning Mechanisms under Training Data Variation
Ke Zhang, Danica J. Sutherland, Chao Liu
Training data variation, whether through designing a domain randomization (DR) scheme in simulation or curating demonstrations for imitation learning, is a primary lever for improv…
stat.ML2026
Understanding Generalization Requires Universal Induction
Aram Ebtekar, Marcus Hutter, Danica J. Sutherland
Classical statistical theory is insufficient to explain the successes of general-purpose AI models, because it depends on handcrafted inductive biases that it cannot justify. No Fr…