by instadatahelp | Sep 6, 2023 | AI Blogs
Introducing a new distributed computing framework that is resilient to slow compute nodes and capable of both approximate and exact linear operations. This innovative approach combines randomized sketching and polar codes within the context of coded computation. We...
by instadatahelp | Sep 6, 2023 | AI Blogs
[Submitted on 1 Sep 2023] Click here to download a PDF of the paper titled “Taken out of context: On measuring situational awareness in LLMs,” written by Lukas Berglund and 7 other authors: Download PDF Abstract: The purpose of this study is to gain a...
by instadatahelp | Sep 6, 2023 | AI Blogs
This work presents enhancements to the stability and applicability of Cyclic DARTS (CDARTS), which is a Differentiable Architecture Search (DARTS) based method for neural architecture search (NAS). CDARTS employs a cyclic feedback mechanism to concurrently train the...
by instadatahelp | Sep 6, 2023 | AI Blogs
The content describes the use of black-box optimization in finding optimal parameters for systems like Neural Networks or complex simulations. It introduces Polynomial-Model-Based Optimization (PMBO) as a novel black-box optimizer that fits a polynomial surrogate to...
by instadatahelp | Sep 6, 2023 | AI Blogs
We focus on studying the learning of $\\epsilon$-optimal strategies in zero-sum imperfect information games (IIG) with trajectory feedback. In this scenario, players update their policies sequentially based on their observations throughout a fixed number of episodes,...
by instadatahelp | Sep 6, 2023 | AI Blogs
In today’s era of data-driven technology, there is a growing interest in synthetic data. This refers to artificially generated data that resembles real-world data but does not contain any personal information. The rise in popularity of synthetic data is driven...
