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Found 8 papers, 1 papers with code
A Quantum Computing-based System for Portfolio Optimization using Future Asset Values and Automatic Reduction of the Investment Universe
One of the problems in quantitative finance that has received the most attention is the portfolio optimization problem.
Hybrid Approach for Solving Real-World Bin Packing Problem Instances Using Quantum Annealers
Efficient packing of items into bins is a common daily task.
Analyzing the behaviour of D'WAVE quantum annealer: fine-tuning parameterization and tests with restrictive Hamiltonian formulations
Despite being considered as the next frontier in computation, Quantum Computing is still in an early stage of development.
Focusing on the Hybrid Quantum Computing -- Tabu Search Algorithm: new results on the Asymmetric Salesman Problem
Quantum Computing is an emerging paradigm which is gathering a lot of popularity in the current scientific and technological community.
Hybrid Quantum Computing -- Tabu Search Algorithm for Partitioning Problems: preliminary study on the Traveling Salesman Problem
Quantum Computing is considered as the next frontier in computing, and it is attracting a lot of attention from the current scientific community.
Deep Echo State Networks for Short-Term Traffic Forecasting: Performance Comparison and Statistical Assessment
Results from this comparison benchmark and the analysis of the statistical significance of the reported performance gaps are decisive: Deep Echo State Networks achieve more accurate traffic forecasts than the rest of considered modeling counterparts.
Exploiting a Stimuli Encoding Scheme of Spiking Neural Networks for Stream Learning
Stream data processing has gained progressive momentum with the arriving of new stream applications and big data scenarios.
jMetalPy: a Python Framework for Multi-Objective Optimization with Metaheuristics
This paper describes jMetalPy, an object-oriented Python-based framework for multi-objective optimization with metaheuristic techniques.
