Boolean TensorDecomposition (BTD)factorizes abinarytensorintotheBoolean sumof multiple rank-1 tensors, which is an NP-hard problem.

To address this challenge, methods need to accommodate target domains with different temporal dynamics and be capable of doing so without seeing any target examples during pre-training.

These algorithms iterate with first-order oracle and achieve linear convergence.

In recent years, model-free reinforcement learning (MFRL) has achieved tremendous success on a wide range of simulated domains, e .