stp2y

As the Data Platform team at Databricks, we leverage our own platform to provide an intuitive, composable, and comprehensive Data and AI platform to internal data practitioners so that they can safely analyze usage and improve our product and business operations. As our company matures, we are especially motivated to establish data governance to enable secure, compliant and cost-effective data operations. With thousands of employees and hundreds of teams analyzing data, we have to frame and implement consistent standards to achieve data governance at scale and continued compliance. We identified Unity Catalog (UC), generally available as of August 2022, as…

arXiv:2407.14653v1 Announce Type: new Abstract: Offline safe reinforcement learning (RL) aims to train a policy that satisfies constraints using a pre-collected dataset. Most current methods struggle with the mismatch between imperfect demonstrations and the desired safe and rewarding performance. In this paper, we introduce OASIS (cOnditionAl diStributIon Shaping), a new paradigm in offline safe RL designed to overcome these critical limitations. OASIS utilizes a conditional diffusion model to synthesize offline datasets, thus shaping the data distribution toward a beneficial target domain. Our approach makes compliance with safety constraints through effective data utilization and regularization techniques to benefit offline safe RL…

arXiv:2407.14655v1 Announce Type: new Abstract: The complexity of state-of-the-art Transformer-based models for skeleton-based action recognition poses significant challenges in terms of computational efficiency and resource utilization. In this paper, we explore the application of Singular Value Decomposition (SVD) to effectively reduce the model sizes of these pre-trained models, aiming to minimize their resource consumption while preserving accuracy. Our method, LORTSAR (LOw-Rank Transformer for Skeleton-based Action Recognition), also includes a fine-tuning step to compensate for any potential accuracy degradation caused by model compression, and is applied to two leading Transformer-based models, "Hyperformer" and "STEP-CATFormer". Experimental results on the "NTU RGB+D" and…