Related papers: Variance Reduction Methods for Sublinear Reinforce…
%auto-ignore This paper has been withdrawn by the author, due to a crucial error.
This paper is withdrawn because the results in the paper are included in a paper to be published in Mathematical and Computer Modelling.
This paper was withdrawn by the author because severe errors were discovered.
Building reliable AI decision support systems requires a robust set of data on which to train models; both with respect to quantity and diversity. Obtaining such datasets can be difficult in resource limited settings, or for applications in…
This paper has been withdrawn by the author due to an error.
This paper has been withdrawn by the authors due to an unlikely results.
This paper has been withdrawn by the author due to a sheaf-theoretic error, in the end of the proof of the main theorem.
In this work, we discuss what we refer to as reduction techniques for survival analysis, that is, techniques that "reduce" a survival task to a more common regression or classification task, without ignoring the specifics of survival data.…
The paper has been withdrawn by the author.
This manuscript has been withdrawn, since the authors have detected numerical inaccuracies that invalidate their main results concerning the existence of repulsive Casimir forces within a rectangular piston. Formulas presented in the…
This paper was withdrawn by arXiv admin due to authors' misrepresentation of identity/affiliation.
This paper is withdrawn. See quant-ph/9806031 for a discussion.
This paper is withdrawn because of an error in Lemma 3.1
This paper has been withdrawn by the author, due to an error in relation (11).
In recent years, challenging control problems became solvable with deep reinforcement learning (RL). To be able to use RL for large-scale real-world applications, a certain degree of reliability in their performance is necessary. Reported…
Reinforcement learning (RL) has become a standard technique for post-training diffusion-based image synthesis models, as it enables learning from reward signals to explicitly improve desirable aspects such as image quality and prompt…
The paper was withdrawn by the author. Further research is needed.
This paper has been withdrawn by the author due to a crucial sign error in equation 1
This paper has been withdrawn.
This paper has been withdrawn by the authors, since it has been merged with Part I (ID 0802.3570)