This work investigates how these complexities necessarily arise for feature learning in the presence of computational-statistical gaps.

General V alue Functions (GVFs) (Sutton et al., 2011) represent predictive knowledge in reinforcement learning.

These theoretical findings are supported by experimental results.

BERT, and GPT models show GRACE's state-of-the-art performance in making

Based on our definitions, we identify and analyze six real-world benchmarks spanning from homophilic to heterophilic link prediction settings, with graphs containing up to 30M edges.