GitHub

A novel granular ball computing-based fuzzy rough set for feature selection in label distribution learning

This repository contains the implementation of the granular ball-based feature selection algorithm for multi-label learning, as described in the research paper published in Knowledge-Based Stems. Note ...
InfoQ

Autonomous Big Data Optimization: Multi-Agent Reinforcement Learning to Achieve Self-Tuning Apache Spark

A monthly overview of things you need to know as an architect or aspiring architect. Unlock the full InfoQ experience by logging in! Stay updated with your favorite authors and topics, engage with ...
Fast Company

Reinforcement learning and organizational management

I took Berkeley’s CS 188 course in artificial intelligence years ago, and like most students, I left with only a basic understanding of reinforcement learning. When I began coding and working in the ...
IEEE

Epsilon-Guided Spatiotemporal Transformer: An Exponential Error Reduction for Multi-Memory Multilingual Sign Interpreter

Abstract: Sign language recognition faces critical challenges including temporal inconsistencies, inadequate cross-cultural feature representation, and limited real-time adaptability with poor ...
www.cs.cmu.edu

Reinforcement Learning

Before diving into the details, let’s look at a high-level overview outlining vocabulary terms we’ll see come up and contrasting different methods. It would also be useful to revisit this section ...
IEEE

HQC-Bend: A Python Package of Hybrid Quantum-Classical Multi-cuts Benders’ Decomposition Algorithm

Abstract: This article introduces the Hybrid Quantum-Classical Multi-Cut Benders’ Decomposition (HQC-Bend) algorithm, an efficient, open-source Python script designed to tackle complex Mixed-Binary ...