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.

Doctors look at an analysis of cellular data as part of their research into using artificial intelligence to repurpose existing drugs to fight rare diseases, in Philadelphia, Pennsylvania, in February 2025. There is concern some apps that claim to offer medical guidance may not have an adequate data set to accurately asses information their users submit. Artificial intelligence is shaking up industries from software and law to entertainment and education. And as physicians like Dr. Cem Aksoy are learning, it's posing special challenges in medicine as patients tap the technology for advice. Aksoy, a medical resident at a hospital in Ankara, Turkey, says an 18-year-old patient and his family recently panicked after the young man was diagnosed with a cancerous tumor on his left leg.

Table 1: Finetuning pruned models with more training steps. Note that the only difference lies in the position of the summation. It is easy to observe that our model achieves convergence rapidly. The dataset size of LSUN Bedroom is 44.48GB, which is We conducted further investigations to explore the effectiveness of knowledge distillation in enhancing pruning techniques. Table 3 profiles the pre-trained and the pruned models on a single A5000, with a batch size of 1.