AI News, Machine Learning and Combinatorial Optimization Problems artificial intelligence

Automated quantum programming via reinforcement learning for combinatorial optimization

By design, the agents were constrained to 25 uncompiled instructions.

Through training, for all problems, the expected length of the trained agent programs is decreased compared to those of the untrained agent.

If too much decoherence is experienced by the later stages of the program, one could expect a strong degradation in performance, as evidenced by the decreased episode score between the QVM and QPU for the QAOA.

Read e-book Paradigms of Combinatorial Optimization: Problems and New Approaches, Volume 2 (Iste)

International Journal of Control 87 :8, ETRI Journal 36 :4, Journal of the Franklin Institute :8, Journal of the Optical Society of America A 31 :8, ACM Transactions on Graphics 33 :4, Numerical Functional Analysis and Optimization 35 , Proceedings of the 33rd Chinese Control Conference , Theoretical Chemistry Accounts Knowledge-Based Systems 65 , IET Communications 8 :9, Journal of High Energy Physics Automatica 50 :6, Computational Optimization and Applications 58 :2, Asian-European Journal of Mathematics 07 , International Journal of Approximate Reasoning 55 :4, Journal of Functional Analysis , Journal of Industrial and Management Optimization 11 :1, Automatica 50 :5, Physical Review A 89 The International Journal of Robotics Research 33 :6, Machine Learning 94 :3, New Journal of Physics 16 :3, Nonlinear Dynamics 75 :4, International Journal of Robust and Nonlinear Control 24 :3, IET Communications 8 :2, Nonlinear Analysis: Hybrid Systems 11 , Procedia - Social and Behavioral Sciences , Abstract and Applied Analysis , Journal of Applied Research and Technology 12 :3, Journal of Applied Mathematics , American Journal of Operations Research 04 , Monthly Notices of the Royal Astronomical Society :3, Encyclopedia of Systems and Control, Detection in High Dimensions.

Optimization Letters 6 :8, Pattern Recognition 45 , Scientific Reports 2 Journal of Inequalities and Applications Journal of the Optical Society of America A 29 , Physical Review A 86 Journal of Global Optimization 54 :3, Operations Research Letters 40 :6, Signal Processing 92 , New Journal of Physics 14 , International Journal of Systems Science 43 , Applied Mathematical Modelling 36 , Distributed Sensor Networks, Second Edition, Electric Power Systems Research 90 , Mathematical Biosciences :1, Journal of Sound and Vibration , Cognitive Radio Communications and Networking, Electric Power Components and Systems 40 , Computational Management Science 9 :3, Journal of Computational Biology 19 :8, Metrika 75 :5, Nonlinear Dynamics 69 , Operations Research Letters 40 :4, Automatica 48 :6, Physical Review A 85 Computational Optimization and Applications 52 :2, Journal of Global Optimization 53 :2, Optimization Methods and Software 27 :3, Engineering Optimization 44 :6, Knowledge-Based Systems 30 , European Journal of Operational Research :3, Journal of Global Optimization 53 :1, Mathematical Methods of Operations Research 75 :2, Probabilistic Engineering Mechanics 28 , Matrix properties, examples and a clustered bibliography on copositive optimization.

Future Intelligent Information Systems, Journal of Process Control 20 , Mathematical Programming Computation 2 , Advances in Data Analysis and Classification 4 :4, Mathematics of Operations Research 35 :4, New Journal of Physics 12 :9, International Journal of Control 83 :9, Physical Review A 82 Journal of Industrial and Management Optimization 6 :4, Wiley Interdisciplinary Reviews: Computational Statistics 2 :5, Positivity 14 :3, Applied Mathematics Letters 23 :8, International Journal of Control, Automation and Systems 8 :4, Journal of Systems Science and Complexity 23 :4, The Journal of Chemical Physics :1, Linear Algebra and its Applications :1, Journal of Guidance, Control, and Dynamics 33 :4, Neurocomputing 73 , Computer Networks 54 :9, Physical Review A 81 Journal of Computational Physics , Machine Learning 79 , Structural and Multidisciplinary Optimization 41 :5, Magnetic Resonance in Medicine 63 :5, Acta Numerica 19 , Chemometrics and Intelligent Laboratory Systems :2, Applied Mathematics and Computation :4, Signal Processing 90 :4, Optics Communications :5, Applied Physics B 98 :4, IET Systems Biology 4 :2, Physica A: Statistical Mechanics and its Applications :3, SIAM Review 52 :3, Signal Processing 90 :1, Machine Learning 78 , Foundations of Set-Semidefinite Optimization.

Physical Review Letters 99 Physical Review A 76 Optimal Control Applications and Methods 28 :6, Optimization Letters 2 :1, Pattern Recognition 40 , Optimization Methods and Software 22 :5, Journal of Interdisciplinary Mathematics 10 :5, Precision Engineering 31 :4, Operations Research Letters 35 :5, Chemical Physics Letters , Journal of Guidance, Control, and Dynamics 30 :5, Knowledge and Information Systems 13 :1, Optimization and Engineering 8 :3, International Journal of Machine Tools and Manufacture 47 , Automatica 43 :8, International Journal of Theoretical Physics 46 :6, Econometric Theory 23 Physics Letters A :6, Physical Review A 75 Journal of Physics: Conference Series 67 , IIE Transactions 39 :7, Journal of Global Optimization 38 :1, Journal of Computational and Applied Mathematics :1, Journal of Pure and Applied Algebra :1, Mathematische Zeitschrift :1, Mathematical Methods of Operations Research 65 :1, International Journal of Control 80 :2, Journal of Interdisciplinary Mathematics 10 :1, Optimization Letters 1 :2, SIAM Review 49 :3, SIAM Review 49 :4, Genetics Selection Evolution 39 :1, 3.

Jain, Combinatorial network optimization with unknown variables: Multi-armed bandits with linear rewards and individual observations, IEEE/ACM Transactions on Networking, vol.20, issue.5, pp.1466-1478, 2012.

Burke, An iterated local search framework with adaptive operator selection for nurse rostering, LION 11, pp.93-108, 2017.

Talbi, On dominance-based multiobjective local search: design, implementation and experimental analysis on scheduling and traveling salesman problems, Journal of Heuristics, vol.18, issue.2, pp.317-352, 2012.URL :

Stützle, The irace package: Iterated racing for automatic algorithm configuration, Operations Research Perspectives, vol.3, pp.43-58, 2016.

Ham, A heuristic algorithm for the m-machine, n-job flow-shop sequencing problem, Omega, vol.11, issue.1, pp.91-95, 1983.

Stützle, Pareto local optimum sets in the biobjective traveling salesman problem: An experimental study, Metaheuristics for Multiobjective Optimisation, pp.177-199, 2004.

Pisinger, An adaptive large neighborhood search heuristic for the pickup and delivery problem with time windows, Transportation Science, vol.40, issue.4, pp.455-472, 2006.

Qu, A dynamic multiarmed bandit-gene expression programming hyper-heuristic for combinatorial optimization problems, IEEE Transactions on Cybernetics, vol.45, issue.2, pp.217-228, 2015.

14. Neural Combinatorial Optimization with Reinforcement Learning. Samy Bengio

Deep Learning: Theory, Algorithms, and Applications. Berlin, June 2017 The workshop aims at bringing together leading scientists in deep learning and related ...

NIPS 2017 Spotlight - Learning Combinatorial Optimization Algorithms over Graphs

Full paper: Code: Abstract: The design of good heuristics or approximation .

TutORial: Machine Learning and Data Mining with Combinatorial Optimization Algorithms

By Dorit Simona Hochbaum. The dominant algorithms for machine learning tasks fall most often in the realm of AI or continuous optimization of intractable ...

How optimization for machine learning works, part 1

Part of the End-to-End Machine Learning School course library at See these concepts used in an End to End Machine Learning project: ..

Machine Learning #25 Optimization: Problems & Algorithms

Machine Learning #25 Optimization: Problems & Algorithms Mathematical optimization is the selection of a best element (with regard to some criteria) from some ...

How the Ant Colony Optimization algorithm works

To watch the rest of the videos, click here: In this course, you will learn about ..

Microsoft Research AI: Machine Learning & Optimization

Designing Next Generation AI Systems. The Machine Learning and Optimization group focuses on designing new algorithms to enable the next generation of AI ...



Optimization for Machine Learning I

Elad Hazan, Princeton University Foundations of Machine Learning Boot Camp

Building AI Solutions with Google OR-Tools - Barry Stahl

We depend on Artificial Intelligences to solve many types of problems for us. Some of these problems have more than one possible solution. Handling those ...