by instadatahelp | Sep 2, 2023 | AI Blogs
Learning Good State and Action Representations for Markov Decision Process via Tensor Decomposition Chengzhuo Ni, Yaqi Duan, Munther Dahleh, Mengdi Wang, Anru R. Zhang; 24(115):1−53, 2023. Abstract This paper presents a novel unsupervised learning approach that...
by instadatahelp | Sep 2, 2023 | AI Blogs
The detection of Extreme Mass Ratio Inspirals (EMRIs) is challenging due to their complex waveforms, long duration, and low signal-to-noise ratio (SNR). This makes them harder to identify compared to compact binary coalescences. While matched filtering techniques are...
by instadatahelp | Sep 2, 2023 | AI Blogs
Learning a Predictive Function for Hyper-parameters Conditioned on Tasks Authors: Jun Shu, Deyu Meng, Zongben Xu; Published in 2023, Volume 24, Issue 186, Pages 1-74. Abstract Recently, meta learning has gained significant attention in the machine learning community....
by instadatahelp | Sep 2, 2023 | AI Blogs
The field of integrated circuits has long struggled with automating the design of analog circuits. This is due to the complexity of circuit specifications and the vast design space. Previous research has mainly focused on automating transistor sizing within a given...
by instadatahelp | Sep 2, 2023 | AI Blogs
Deep linear networks can overfit benignly when shallow ones do Authors: Niladri S. Chatterji, Philip M. Long; Published in 2023, Vol. 24(117), Pages 1-39. Abstract This study focuses on bounding the excess risk of interpolating deep linear networks trained using...
