A5101558274- Quantum Computing Algorithms and Architecture
- Quantum Information and Cryptography
- Metaheuristic Optimization Algorithms Research
- Advanced Computational Techniques and Applications
- Neural Networks and Reservoir Computing
- Machine Learning and Data Classification
- Machine Learning and Algorithms
- Algorithms and Data Compression
- Advanced Bandit Algorithms Research
- Neural Networks and Applications
- Evolutionary Algorithms and Applications
- Simulation and Modeling Applications
- Stock Market Forecasting Methods
- Context-Aware Activity Recognition Systems
- Advanced Image and Video Retrieval Techniques
- Advanced Measurement and Detection Methods
- Web visibility and informetrics
- Quantum many-body systems
- Bioinformatics and Genomic Networks
- Financial Markets and Investment Strategies
- Bayesian Methods and Mixture Models
- Engineering and Test Systems
- Optimization and Search Problems
- Rough Sets and Fuzzy Logic
- Vehicle Routing Optimization Methods
Jilin University of Finance and Economics
2024
East China Normal University
2023
Chongqing University of Technology
2022
Central South University
2019
Google (United States)
2016-2018
Shanghai Jian Qiao University
2015
Dalian University of Technology
2015
Harbin Normal University
2014
Purdue University West Lafayette
2012
Northwestern Polytechnical University
2007-2008
We report the first electronic structure calculation performed on a quantum computer without exponentially costly precompilation. use programmable array of superconducting qubits to compute energy surface molecular hydrogen using two distinct algorithms. First, we experimentally execute unitary coupled cluster method variational eigensolver. Our efficient implementation predicts correct dissociation within chemical accuracy numerically exact result. Second, demonstrate canonical algorithm...
Quantum annealing is a quantum enhanced heuristic optimization algorithm that exploits tunneling. New work shows it can significantly outperform its classical analog (simulated annealing) as well the most popular for simulating (quantum Monte Carlo).
We propose a non-convex training objective for robust binary classification of data sets in which label noise is present. The design guided by the intention solving resulting problem adiabatic quantum optimization. Two requirements are imposed engineering constraints existing hardware: problems formulated as quadratic unconstrained optimization; and model parameters represented expansions low bit-depth. In present work we validate this approach using heuristic classical solver stand-in...
High-frequency trading is an extraordinarily intricate financial task, which normally treated as a near real-time sequential decision problem. Compared with the traditional two-phase approach, forecasting equity's trend and then weighting them by combinatorial optimization, deep reinforcement learning (DRL) methods have shown advances in reward chasing optimal policies. However, existing DRL-based either leverage portfolio optimization on low-frequency scenarios or only support very limited...
Xu, F.; Lu, H.; Ding, N., and Liu, J., 2015. Game theory analysis of container port alliance.Since the reform opening up, China's transport industry has developed rapidly. For many years, it been largest country that demands for in world. As an important node global transportation network, status our ports become increasingly However, with decline external demand recent years reconstruction economy, promoted competition among various shipping companies fierce. This paper applies game to...
Quantum annealing is a heuristic quantum algorithm which exploits resources to minimize an objective function embedded as the energy levels of programmable physical system. To take advantage potential advantage, one needs be able map problem interest native hardware with reasonably low overhead. Because experimental considerations constrain our form degree PUBO (polynomial unconstrained binary optimization), we employ non-convex loss functions are polynomial margin. We show that these robust...
We propose a totally corrective boosting algorithm with explicit cardinality regularization. The resulting combinatorial optimization problems are not known to be efficiently solvable existing classical methods, but emerging quantum technology gives hope for achieving sparser models in practice. In order demonstrate the utility of our algorithm, we use distributed heuristic optimizer as stand-in hardware. Even though this evaluation methodology incurs large time and resource costs on...
The minimum weighted connected dominating set problem is a classical NP-hard with wide applications in practice. In this paper, an efficient local search algorithm proposed to solve problem. algorithm, firstly, initial solution construction method based on greedy randomized adaptive strategy adopted, which can balance the quality and diversity of solutions. Second, two new scoring functions, Ascore Cscore, are increase deleted vertices. Third, connectivity so that no longer relies shortest...
In the online base of CNKI, there are 4074 journal articles retrieved whose themes cultural consumption among all papers from 2003 to 2013, and keywords them exported arranged. Counting up words frequency with pivot tables EXCEL selecting high in order build a co-word matrix. Using Ucinet, tool social network analysis, transfer matrix into picture key word make an analysis it. Finally, results analyses discussed, summary is arrived at that current hotspots research Chinese mainly focused on...
Marginal probability distribution has been widely used as the probabilistic model in EDAs because of its simplicity and efficiency. However, obvious shortcoming kind lies incapability taking correlation between variables into account. This paper tries to solve problem from point view space transformation. As we know, it seems a default rule that is usually constructed directly selected samples defined by problem. In algorithm CM-MEDA, instead, first transform sampled data initial coordinate...
This paper is concerned with the optimization guaranteed cost fuzzy control for a quad-rotor UAV prescribed H <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">∞</sub> performance index, to achieve tracking of desired trajectory. Firstly, divided into altitude, position and attitude three subsystems. It adoptes interval matrix describe uncertainties in lift coefficient, drag coefficient moments inertia. Then sufficient condition designed guarantee...
The ageing population increases significantly in these years.How to care for the elderly people living alone becomes an important problem.This design is a wireless monitoring system based on ZigBee and LabVIEW because low power cost networking technology graphical programming platform.This performs daily activities of by setting variety different parameter sensors room data are sent center wirelessly.Then personnel can monitor elderly.When there some abnormal situations occurring elderly,...
Estimation of distribution algorithms(EDA) are a class recently-developed evolutionary algorithms in which the probabilistic model used to explicitly characterize population and generate new individuals. The polynomial is applied by discrete EDAs continuous based on discretization domain such as histogram-based EDA. We can unify those kinds EDA from their call them PolyEDA. In this paper, we theoretically analyze PolyEDA Bayesian analysis view. Our assumption that prior parameters satisfies...
As most of the community discovery methods are researched by static thought, some algorithms cannot represent whole dynamic network change process efficiently. This paper proposes a novel method (Phylogenetic Planted Partition Model, PPPM) for phylogenetic evolution. Firstly, time dimension is introduced into typical migration partition model, and all states treated as variables, observation equation constructed. Secondly, this takes social constraint between variables error function. Then,...