Simulated annealing for VLSI design
Simulated annealing for VLSI design
Practical Issues in Temporal Difference Learning
Machine Learning
Numerical recipes in C (2nd ed.): the art of scientific computing
Numerical recipes in C (2nd ed.): the art of scientific computing
Learning in embedded systems
Modern heuristic techniques for combinatorial problems
Reinforcement learning for robots using neural networks
Reinforcement learning for robots using neural networks
Synthesis of high-performance analog cells in ASTRX/OBLX
Synthesis of high-performance analog cells in ASTRX/OBLX
Artificial intelligence: a modern approach
Artificial intelligence: a modern approach
An efficient lower bound algorithm for channel routing
Integration, the VLSI Journal
Approximation algorithms for bin packing: a survey
Approximation algorithms for NP-hard problems
Learning instance-independent value functions to enhance local search
Proceedings of the 1998 conference on Advances in neural information processing systems II
Markov Decision Processes: Discrete Stochastic Dynamic Programming
Markov Decision Processes: Discrete Stochastic Dynamic Programming
Genetic Algorithms in Search, Optimization and Machine Learning
Genetic Algorithms in Search, Optimization and Machine Learning
Learning to Predict by the Methods of Temporal Differences
Machine Learning
Q2: Memory-Based Active Learning for Optimizing Noisy Continuous Functions
ICML '98 Proceedings of the Fifteenth International Conference on Machine Learning
A Nonparametric Approach to Noisy and Costly Optimization
ICML '00 Proceedings of the Seventeenth International Conference on Machine Learning
Learning as Applied to Stochastic Optimization for Standard Cell Placement
ICCD '98 Proceedings of the International Conference on Computer Design
Dynamic Programming
Combining Simulated Annealing with Local Search Heuristics
Combining Simulated Annealing with Local Search Heuristics
Reinforcement learning for job shop scheduling
Reinforcement learning for job shop scheduling
Learning evaluation functions for global optimization
Learning evaluation functions for global optimization
Cached sufficient statistics for efficient machine learning with large datasets
Journal of Artificial Intelligence Research
A reinforcement learning approach to job-shop scheduling
IJCAI'95 Proceedings of the 14th international joint conference on Artificial intelligence - Volume 2
Evidence for invariants in local search
AAAI'97/IAAI'97 Proceedings of the fourteenth national conference on artificial intelligence and ninth conference on Innovative applications of artificial intelligence
On the sample complexity of learning Bayesian networks
UAI'96 Proceedings of the Twelfth international conference on Uncertainty in artificial intelligence
IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems
Automated discovery of composite SAT variable-selection heuristics
Eighteenth national conference on Artificial intelligence
A recursive random search algorithm for large-scale network parameter configuration
SIGMETRICS '03 Proceedings of the 2003 ACM SIGMETRICS international conference on Measurement and modeling of computer systems
Policy search using paired comparisons
The Journal of Machine Learning Research
Speedup learning for repair-based search by identifying redundant steps
The Journal of Machine Learning Research
A smart hill-climbing algorithm for application server configuration
Proceedings of the 13th international conference on World Wide Web
Large-scale network parameter configuration using an on-line simulation framework
IEEE/ACM Transactions on Networking (TON)
Discriminative learning of beam-search heuristics for planning
IJCAI'07 Proceedings of the 20th international joint conference on Artifical intelligence
IJCAI'01 Proceedings of the 17th international joint conference on Artificial intelligence - Volume 1
Generating SAT local-search heuristics using a GP hyper-heuristic framework
EA'07 Proceedings of the Evolution artificielle, 8th international conference on Artificial evolution
Incremental evolution of local search heuristics
Proceedings of the 12th annual conference on Genetic and evolutionary computation
Combining Constraint Programming and Local Search for Job-Shop Scheduling
INFORMS Journal on Computing
An optimal stopping strategy for online calibration in local search
LION'05 Proceedings of the 5th international conference on Learning and Intelligent Optimization
Transfer in reinforcement learning via shared features
The Journal of Machine Learning Research
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This paper describes algorithms that learn to improve search performance on large-scale optimization tasks. The main algorithm, STAGE, works by learning an evaluation function that predicts the outcome of a local search algorithm, such as hillclimbing or Walksat, from features of states visited during search. The learned evaluation function is then used to bias future search trajectories toward better optima on the same problem. Another algorithm, X-STAGE, transfers previously learned evaluation functions to new, similar optimization problems. Empirical results are provided on seven large-scale optimization domains: bin-packing, channel routing, Bayesian network structure-finding, radiotherapy treatment planning, cartogram design, Boolean satisfiability, and Boggle board setup.