Visual Studio Magazine

Support Vector Regression with SGD Training Using C#

Support vector regression can predict numeric values effectively, and this article shows how to implement and train a kernel SVR model in C# using stochastic sub-gradient descent.
Microsoft

Minibatch Selection for Language Models via Partition Matroid Constrained Gradient Matching

Training large language models (LLMs) on heterogeneous data requires selecting minibatches that balance convergence speed with coverage across domains. Existing methods either select samples ...
IEEE

SA-MARL: Novel Self-Attention-Based Multi-Agent Reinforcement Learning With Stochastic Gradient Descent

Abstract: In the rapidly advancing Reinforcement Learning (RL) field, Multi-Agent Reinforcement Learning (MARL) has emerged as a key player in solving complex real-world challenges. A pivotal ...
Scientific Research Publishing

Kingma, D.P. and Ba, J. (2015) Adam: A Method for Stochastic Optimization. arXiv: 1412.6980.

ABSTRACT: This paper develops a fuzzy stochastic volatility framework for pricing and calibrating copper futures contracts under parameter uncertainty. The classical Heston model is extended by ...
GitHub

Probabilistic programming with programmable variational inference

This repository contains the JAX implementation that accompanies the paper Probabilistic programming with programmable variational inference, as well as the experiments used to generate figures and ...
IEEE

An Improved Distributed Nesterov Gradient Tracking Algorithm for Smooth Convex Optimization Over Directed Networks

Abstract: This article explores the problem of distributed optimization for functions that are smooth and nonstrongly convex over directed networks. To address this issue, an improved distributed ...