Towards Explaining the Regularization Effect of Initial Large Learning Rate in Training Neural NetworksStochastic gradient descent with a large initial learning rate is widely used for training modern neural net architectures. Although a small initial learning rate allows for faster training and better ...
Specifically, during China’s legal holidays, the return rate of the cryptocurrency market has seen a notable rise. While positive investor sentiment can boost the market’s return rate, it simultaneously can diminish the holiday effect. A plausible explanation could be the shift in investor ...
Ritter H, Kukla M, Zhang C, Li Y (2021) Sparse uncertainty representation in deep learning with inducing weights. Adv Neural Inf Proces Syst 34:6515–6528 Google Scholar Ruder S (2016) An overview of gradient descent optimization algorithms. arXiv Prepr arXiv160904747 Saha S, Obukhov A, ...
which can be used to assess its regulatory activity. Using a machine learning model trained on numerous ChIP-seq datasets of various histone marks, QHistone can accurately cluster a regulatory
The training functions in the mnist object is defined as:L def training(loss, learning_rate, var_list): # Add a scalar summary for the snapshot loss. tf.summary.scalar('loss', loss) # Create the gradient descent optimizer with the given learning rate. optimizer = tf.train.GradientDescent...
Deep-learning (DL) applications, associated challenges, and the need for in-memory computing (IMC) with Non-Volatile Memory (NVM) devices. (a) Holistic view of DL applications, the architecture of a fully connected neural network, and the challenges that allow IMC to complement. (b) IMC and...
6e), which include a CRP-RNAP interaction energy of ΔGI=−2.598±0.018 kcal/mol, largely match those of Kinney et al., but were obtained far more rapidly (in ∼10 min versus multiple days) thanks to the use of stochastic gradient descent rather than Metropolis Monte Carlo. ...
In this study, we investigated the effect of principal component analysis (PCA) in congestive heart failure (CHF) diagnosis using various machine learning algorithms from 5-min HRV data. The extracted 59 heart rate variability (HRV) features consist of statistical time-domain measures, frequency-dom...
Histone modifications can regulate transcription epigenetically by marking specific genomic loci, which can be mapped using chromatin immunoprecipitation sequencing (ChIP-seq). Here we present QHistone, a predictive database of 1534 ChIP-seqs from 27 his
In this work we set out to characterise the trade-off between learning \varvec{z} that is biologically meaningful and, simultaneously, disentangled from batch effects. For now, let V_n(\varvec{\phi }) be some measure of batch effect in the learned latent variable \varvec{z}, where we...