Technological evolution and adaptive organizations: Ideas from biology may find applications in economics. - Stuart A. Kauffman; William G. Macready (Complex., 1995)

What makes an optimization problem hard? - William G. Macready; David H. Wolpert (Complex., 1996)

No free lunch theorems for optimization. - David H. Wolpert; William G. Macready (IEEE Trans. Evol. Comput., 1997)

Tailoring Mutation to Landscape Properties. - William G. Macready (Evolutionary Programming, 1998)

Bandit problems and the exploration/exploitation tradeoff. - William G. Macready; David H. Wolpert (IEEE Trans. Evol. Comput., 1998)

Learning landscapes: regression on discrete spaces. - William G. Macready; Bennett S. Levitan (CEC, 1999)

An Efficient Method To Estimate Bagging's Generalization Error. - David H. Wolpert; William G. Macready (Mach. Learn., 1999)

Remarks on a recent paper on the "no free lunch" theorems. - Mario Köppen; David H. Wolpert; William G. Macready (IEEE Trans. Evol. Comput., 2001)

Parameter space exploration with Gaussian process trees. - Robert B. Gramacy; Herbert K. H. Lee; William G. Macready (ICML, 2004)

Coevolutionary free lunches. - David H. Wolpert; William G. Macready (IEEE Trans. Evol. Comput., 2005)

Using self-dissimilarity to quantify complexity. - David H. Wolpert; William G. Macready (Complex., 2007)

Distributed Constrained Optimization with Semicoordinate Transformations - William G. Macready; David H. Wolpert (CoRR, 2008)

Training a Large Scale Classifier with the Quantum Adiabatic Algorithm - Hartmut Neven; Vasil S. Denchev; Geordie Rose; William G. Macready (CoRR, 2009)

QBoost: Large Scale Classifier Training with Adiabatic Quantum Optimization. - Hartmut Neven; Vasil S. Denchev; Geordie Rose; William G. Macready (ACML, 2012)

Investigating the performance of an adiabatic quantum optimization processor. - Kamran Karimi; Neil G. Dickson; Firas Hamze; Mohammad H. S. Amin; Marshall Drew-Brook; Fabián A. Chudak; Paul I. Bunyk; William G. Macready; Geordie Rose (Quantum Inf. Process., 2012)

A practical heuristic for finding graph minors. - Jun Cai; William G. Macready; Aidan Roy (CoRR, 2014)

Benchmarking Quantum Hardware for Training of Fully Visible Boltzmann Machines. - Dmytro Korenkevych; Yanbo Xue; Zhengbing Bian; Fabián A. Chudak; William G. Macready; Jason Rolfe; Evgeny Andriyash (CoRR, 2016)

Mapping Constrained Optimization Problems to Quantum Annealing with Application to Fault Diagnosis. - Zhengbing Bian; Fabián A. Chudak; Robert B. Israel; Brad Lackey; William G. Macready; Aidan Roy (Frontiers ICT, 2016)

Generalized Ramsey numbers through adiabatic quantum optimization. - Mani Ranjbar; William G. Macready; Lane H. Clark; Frank Gaitan (Quantum Inf. Process., 2016)

Solving SAT and MaxSAT with a Quantum Annealer: Foundations and a Preliminary Report. - Zhengbing Bian; Fabián A. Chudak; William G. Macready; Aidan Roy; Roberto Sebastiani; Stefano Varotti (FroCoS, 2017)

DVAE++: Discrete Variational Autoencoders with Overlapping Transformations. - Arash Vahdat; William G. Macready; Zhengbing Bian; Amir Khoshaman; Evgeny Andriyash (ICML, 2018)

DVAE#: Discrete Variational Autoencoders with Relaxed Boltzmann Priors. - Arash Vahdat; Evgeny Andriyash; William G. Macready (NeurIPS, 2018)

DVAE++: Discrete Variational Autoencoders with Overlapping Transformations. - Arash Vahdat; William G. Macready; Zhengbing Bian; Amir Khoshaman (CoRR, 2018)

Improved Gradient-Based Optimization Over Discrete Distributions. - Evgeny Andriyash; Arash Vahdat; William G. Macready (CoRR, 2018)

Weakly Supervised Semantic Image Segmentation with Self-correcting Networks. - Mostafa S. Ibrahim; Arash Vahdat; William G. Macready (CoRR, 2018)

A Robust Learning Approach to Domain Adaptive Object Detection. - Mehran Khodabandeh; Arash Vahdat; Mani Ranjbar; William G. Macready (ICCV, 2019)

Learning Undirected Posteriors by Backpropagation through MCMC Updates. - Arash Vahdat; Evgeny Andriyash; William G. Macready (CoRR, 2019)

Semi-Supervised Semantic Image Segmentation With Self-Correcting Networks. - Mostafa S. Ibrahim; Arash Vahdat; Mani Ranjbar; William G. Macready (CVPR, 2020)

Undirected Graphical Models as Approximate Posteriors. - Arash Vahdat; Evgeny Andriyash; William G. Macready (ICML, 2020)

Solving SAT (and MaxSAT) with a quantum annealer: Foundations, encodings, and preliminary results. - Zhengbing Bian; Fabián A. Chudak; William G. Macready; Aidan Roy; Roberto Sebastiani; Stefano Varotti (Inf. Comput., 2020)

Neural-Guided Runtime Prediction of Planners for Improved Motion and Task Planning with Graph Neural Networks. - Simon Odense; Kamal Gupta 001; William G. Macready (IROS, 2022)

Neural-Guided RuntimePrediction of Planners for Improved Motion and Task Planning with Graph Neural Networks. - Simon Odense; Kamal Gupta 001; William G. Macready (CoRR, 2022)