William G. Macready

17.5k total citations · 1 hit paper
35 papers, 10.6k citations indexed

About

William G. Macready is a scholar working on Artificial Intelligence, Computer Networks and Communications and Management Science and Operations Research. According to data from OpenAlex, William G. Macready has authored 35 papers receiving a total of 10.6k indexed citations (citations by other indexed papers that have themselves been cited), including 22 papers in Artificial Intelligence, 7 papers in Computer Networks and Communications and 7 papers in Management Science and Operations Research. Recurrent topics in William G. Macready's work include Quantum Computing Algorithms and Architecture (8 papers), Metaheuristic Optimization Algorithms Research (5 papers) and Gaussian Processes and Bayesian Inference (4 papers). William G. Macready is often cited by papers focused on Quantum Computing Algorithms and Architecture (8 papers), Metaheuristic Optimization Algorithms Research (5 papers) and Gaussian Processes and Bayesian Inference (4 papers). William G. Macready collaborates with scholars based in United States, Canada and Italy. William G. Macready's co-authors include David H. Wolpert, Stuart Kauffman, José Lobo, Fabián A. Chudak, Zhengbing Bian, Aidan Roy, Robert B. Israel, Brad Lackey, Mario Köppen and Arash Vahdat and has published in prestigious journals such as Science, Physical Review Letters and Physical review. B, Condensed matter.

In The Last Decade

William G. Macready

35 papers receiving 10.1k citations

Hit Papers

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What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

No free lunch theorems for optimization

1997 9.4k citations David H. Wolpert, William G. Macready IEEE Transactions on Evolutionary Computation profile →

Peers

Countries citing papers authored by William G. Macready

Since Specialization

Citations

This map shows the geographic impact of William G. Macready's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by William G. Macready with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites William G. Macready more than expected).

Fields of papers citing papers by William G. Macready

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by William G. Macready. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by William G. Macready. The network helps show where William G. Macready may publish in the future.

Co-authorship network of co-authors of William G. Macready

This figure shows the co-authorship network connecting the top 25 collaborators of William G. Macready. A scholar is included among the top collaborators of William G. Macready based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with William G. Macready. William G. Macready is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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20 of 20 papers shown

#	Work	Indexed citations
1	Neural-Guided Runtime Prediction of Planners for Improved Motion and Task Planning with Graph Neural Networks 2022 ·2022 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) ·(unknown), Kamal Gupta, William G. Macready	3
2	Undirected Graphical Models as Approximate Posteriors 2020 ·International Conference on Machine Learning ·Arash Vahdat, Evgeny Andriyash, William G. Macready	1
3	Solving SAT (and MaxSAT) with a quantum annealer: Foundations, encodings, and preliminary results 2020 ·Information and Computation ·Zhengbing Bian, Fabián A. Chudak, William G. Macready, Aidan Roy, Roberto Sebastiani, (unknown)	18
4	DVAE++: Discrete Variational Autoencoders with Overlapping Transformations 2018 ·International Conference on Machine Learning ·Arash Vahdat, William G. Macready, Zhengbing Bian, (unknown), Evgeny Andriyash	2
5	DVAE#: Discrete Variational Autoencoders with Relaxed Boltzmann Priors 2018 ·arXiv (Cornell University) ·Arash Vahdat, Evgeny Andriyash, William G. Macready	3
6	Generalized Ramsey numbers through adiabatic quantum optimization 2016 ·Quantum Information Processing ·Mani Ranjbar, William G. Macready, Lane Clark, Frank Gaitan	3
7	Discrete optimization using quantum annealing on sparse Ising models 2014 ·Frontiers in Physics ·Zhengbing Bian, Fabián A. Chudak, Robert B. Israel, Brad Lackey, William G. Macready, Aidan Roy	79
8	Experimental Determination of Ramsey Numbers 2013 ·Physical Review Letters ·Zhengbing Bian, Fabián A. Chudak, William G. Macready, Lane Clark, Frank Gaitan	61
9	QBoost: Large Scale Classifier Training with Adiabatic Quantum Optimization. 2012 ·Asian Conference on Machine Learning ·Hartmut Neven, Vasil S. Denchev, Geordie Rose, William G. Macready	20
10	Experimental determination of Ramsey numbers with quantum annealing 2012 ·arXiv (Cornell University) ·Zhengbing Bian, Fabián A. Chudak, William G. Macready, Lane Clark, Frank Gaitan	7
11	Construction of Energy Functions for Lattice Heteropolymer Models: Efficient Encodings for Constraint Satisfaction Programming and Quantum Annealing 2012 ·arXiv (Cornell University) ·Ryan Babbush, Alejandro Perdomo‐Ortiz, Bryan O’Gorman, William G. Macready, Alán Aspuru‐Guzik	2
12	Investigating the performance of an adiabatic quantum optimization processor 2011 ·Quantum Information Processing ·Kamran Karimi, Neil G. Dickson, Firas Hamze, (unknown), Marshall Drew-Brook, Fabián A. Chudak, P. Bunyk, William G. Macready, Geordie Rose	20
13	Using self‐dissimilarity to quantify complexity 2007 ·Complexity ·David H. Wolpert, William G. Macready	21
14	Coevolutionary Free Lunches 2005 ·IEEE Transactions on Evolutionary Computation ·David H. Wolpert, William G. Macready	139
15	Remarks on a recent paper on the "no free lunch" theorems 2001 ·IEEE Transactions on Evolutionary Computation ·Mario Köppen, David H. Wolpert, William G. Macready	58
16	Self-dissimilarity: an empirically observable complexity measure 2000 ·David H. Wolpert, William G. Macready	15
17	What makes an optimization problem hand? 1996 ·Complexity ·William G. Macready, David H. Wolpert	37
18	Criticality and Parallelism in Combinatorial Optimization 1996 ·Science ·William G. Macready, Athanassios G. Siapas, Stuart Kauffman	39
19	Search strategies for applied molecular evolution 1995 ·Journal of Theoretical Biology ·Stuart Kauffman, William G. Macready	34
20	Thermal instability of thetrans-polyacetylene polaron 1990 ·Physical review. B, Condensed matter ·A. E. Jacobs, William G. Macready, Kwok Yip Szeto, Kazumi Maki	5

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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