Work done as a visiting student at MIT. 38th Conference on Neural Information Processing Systems (NeurIPS 2024).

Invariant Risk Minimization (IRM) is a recently proposed framework for outof-distribution (o.o.d) generalization.

We demonstrate the efficiency of our protocol for distributed optimization with strongtheoreticalguarantees.

Time series forecasting has become a critical task due to its high practicality in real-world applications such as traffic, energy consumption, economics and finance,anddiseaseanalysis.

Nevertheless, theperformance guarantee of adaptive TD with neural network approximation remains widely unknown.