Specifically, we extend the Catalyst approach originally designed fordeterministic objectives tothe stochastic setting.

We consider hk to be either Eq. 4 (proximal point), Eq. 9 (proximal gradient), or Eq. In the appendix, we conduct an experiment with an extremely7 high condition number (much higher than what is traditionally used for these problems). We agree that the clarity of our paper is subject to improvement and we thank the reviewer for his12 suggestions,whichwewilltakeintoaccount,ifthepaperisaccepted. NIPS 2014.", which displays moderate gains on text classification tasks. We agree that direct acceleration methods are appealing.

Wefurther propose newtraining methods todisentangle the embeddings, making them both distinctive signatures of the environments and tasks and effective building blocks for composing the policies.

We achieve an average task solve rate of 66% compared to a 29% solve rate by GPT -4's intrinsic planning with chain-of-thought prompting.

Howeverwhat is perhaps more surprising, is that in stark contrast to our classic understanding of generalization in machine learning models, this does not seem to degrade the generalization capabilities of the learned model in spite of the significant increase in its capacity.

In the reinforcement learning context, anOption means a temporally extended sequence of actions [30],andisregarded asuseful formanypurposes, such asspeeding uplearning, transferring skills across domains, and solving long-term planning problems.

In this section, we report the hyperparameters of each base model used in our paper, details in Table 2. The only hyperparameter that is tuned is done per dataset using a 10% validation split. In this Section, we discuss the experimental convergence of our U-DIF algorithm to the global optimum. In order to approximately compute the true global optimum, we use the following numerical scheme. (exact numbers vary by network and are given in Figure 4).

To combat this, there has been a surge of interest in algorithmic fairness metrics (Mehrabi et al., 2021).