Business Insider

WiMi Studies Hybrid Quantum-Classical Convolutional Neural Network Model

BEIJING, Oct. 23, 2025 (GLOBE NEWSWIRE) -- BEIJING, Oct. 23, 2025––WiMi Hologram Cloud Inc. (NASDAQ: WiMi) ("WiMi" or the "Company"), a leading global Hologram Augmented Reality ("AR") Technology ...
GitHub

batch_size in DAPO/GRPO config

Just wanted to share a bit of experience that might help if you're training the DAPO or GRPO algorithm using VERL with FSDP. Here’s the setup I was working with: TP = 4 8 GPUs per node 8 nodes total ...
IEEE

Mini-batch gradient descent: Faster convergence under data sparsity

Abstract: The practical performance of stochastic gradient descent on large-scale machine learning tasks is often much better than what current theoretical tools can guarantee. This indicates that ...
marktechpost

Privacy Implications and Comparisons of Batch Sampling Methods in Differentially Private Stochastic Gradient Descent (DP-SGD)

Differentially Private Stochastic Gradient Descent (DP-SGD) is a key method for training machine learning models like neural networks while ensuring privacy. It modifies the standard gradient descent ...
Hacker

Extending Stochastic Gradient Optimization with ADAM

Gradient descent is a method to minimize an objective function F(θ) It’s like a “fitness tracker” for your model — it tells you how good or bad your model’’ predictions are. Gradient descent isn’t a ...
GitHub

index.md

SGD (Stochastic Gradient Descent): Using Partial Data to Update Weights in Each Iteration An efficient optimization technique using partial data to update weights in each iteration during model ...