Numerical Optimization

AutoDock Vina: Improving the speed and accuracy of docking with a new scoring function, efficient optimization, and multithreading

Trott, O., & Olson, A. J. (2010) · Journal of Computational Chemistry · doi:10.1002/jcc.21334 · Cited by 38,412

Distributed Optimization and Statistical Learning via the Alternating Direction Method of Multipliers

Boyd, S., Parikh, N., Chu, E., Peleato, B., & Eckstein, J. (2011) · Foundations and Trends® in Machine Learning · doi:10.1561/2200000016 · Cited by 17,075

Robust uncertainty principles: exact signal reconstruction from highly incomplete frequency information

Candes, E. J., Romberg, J., & Tao, T. (2006) · IEEE Transactions on Information Theory · doi:10.1109/tit.2005.862083 · Cited by 15,639

cryoSPARC: algorithms for rapid unsupervised cryo-EM structure determination

Punjani, A., Rubinstein, J. L., Fleet, D. J., & Brubaker, M. A. (2017) · Nature Methods · doi:10.1038/nmeth.4169 · Cited by 11,626

Fast model-based estimation of ancestry in unrelated individuals

Alexander, D. H., Novembre, J., & Lange, K. (2009) · Genome Research · doi:10.1101/gr.094052.109 · Cited by 9,898

On the implementation of an interior-point filter line-search algorithm for large-scale nonlinear programming

Wächter, A., & Biegler, L. T. (2006) · Mathematical Programming · doi:10.1007/s10107-004-0559-y · Cited by 9,483

Bundle Adjustment — A Modern Synthesis

Triggs, B., McLauchlan, P. F., Hartley, R. I., & Fitzgibbon, A. W. (2000) · Lecture Notes in Computer Science · doi:10.1007/3-540-44480-7_21 · Cited by 3,988

Markov logic networks

Richardson, M., & Domingos, P. (2006) · Machine Learning · doi:10.1007/s10994-006-5833-1 · Cited by 2,676

An Interior-Point Method for Large-Scale -Regularized Least Squares

Kim, S.-J., Koh, K., Lustig, M., Boyd, S., & Gorinevsky, D. (2007) · IEEE Journal of Selected Topics in Signal Processing · doi:10.1109/jstsp.2007.910971 · Cited by 2,083

A New Alternating Minimization Algorithm for Total Variation Image Reconstruction

Wang, Y., Yang, J., Yin, W., & Zhang, Y. (2008) · SIAM Journal on Imaging Sciences · doi:10.1137/080724265 · Cited by 1,975

Structural Relaxation Made Simple

Bitzek, E., Koskinen, P., Gähler, F., Moseler, M., & Gumbsch, P. (2006) · Physical Review Letters · doi:10.1103/physrevlett.97.170201 · Cited by 1,755

Fast Model Predictive Control Using Online Optimization

Wang, Y., & Boyd, S. (2010) · IEEE Transactions on Control Systems Technology · doi:10.1109/tcst.2009.2017934 · Cited by 1,372

Shallow parsing with conditional random fields

Sha, F., & Pereira, F. (2003) · Proceedings of the 2003 Conference of the North American Chapter of the Association for Computational Linguistics on Human Language Technology - NAACL '03 · doi:10.3115/1073445.1073473 · Cited by 1,246

Relational learning via collective matrix factorization

Singh, A. P., & Gordon, G. J. (2008) · Proceedings of the 14th ACM SIGKDD international conference on Knowledge discovery and data mining · doi:10.1145/1401890.1401969 · Cited by 1,204

Predicting clicks: estimating the click-through rate for new ads

Richardson, M., Dominowska, E., & Ragno, R. (2007) · Proceedings of the 16th international conference on World Wide Web · doi:10.1145/1242572.1242643 · Cited by 1,049

Untitled work

Romero (2017) · doi:10.1145/3130800.3130883 · Cited by 1,056

Disciplined Convex Programming

Grant, M., Boyd, S., & Ye, Y. (2006) · Nonconvex Optimization and Its Applications · doi:10.1007/0-387-30528-9_7 · Cited by 1,026

Computational recipes for electromagnetic inverse problems: Computational recipes for EM inverse problems

Egbert, G. D., & Kelbert, A. (2012) · Geophysical Journal International · doi:10.1111/j.1365-246x.2011.05347.x · Cited by 849

Real-Time Detection of False Data Injection Attacks in Smart Grid: A Deep Learning-Based Intelligent Mechanism

He, Y., Mendis, G. J., & Wei, J. (2017) · IEEE Transactions on Smart Grid · doi:10.1109/tsg.2017.2703842 · Cited by 834

SBA: A software package for generic sparse bundle adjustment

Lourakis, M. I. A., & Argyros, A. A. (2009) · ACM Transactions on Mathematical Software · doi:10.1145/1486525.1486527 · Cited by 788

Quantitative spectroscopic photoacoustic imaging: a review

Cox, B., Laufer, J. G., Arridge, S. R., & Beard, P. C. (2012) · Journal of Biomedical Optics · doi:10.1117/1.jbo.17.6.061202 · Cited by 720

Interior Methods for Nonlinear Optimization

Forsgren, A., Gill, P. E., & Wright, M. H. (2002) · SIAM Review · doi:10.1137/s0036144502414942 · Cited by 699

The immersed boundary method: A projection approach

Taira, K., & Colonius, T. (2007) · Journal of Computational Physics · doi:10.1016/j.jcp.2007.03.005 · Cited by 667

Amorphous systems in athermal, quasistatic shear

Maloney, C. E., & Lemaître, A. (2006) · Physical Review E · doi:10.1103/physreve.74.016118 · Cited by 666

Transition-Path Theory and Path-Finding Algorithms for the Study of Rare Events

E, W., & Vanden-Eijnden, E. (2010) · Annual Review of Physical Chemistry · doi:10.1146/annurev.physchem.040808.090412 · Cited by 640

Evaluation of Optimization Methods for Control Allocation

Bodson, M. (2002) · Journal of Guidance, Control, and Dynamics · doi:10.2514/2.4937 · Cited by 631

Retrospective on optimization

Biegler, L. T., & Grossmann, I. E. (2004) · Computers & Chemical Engineering · doi:10.1016/j.compchemeng.2003.11.003 · Cited by 593

False rumors detection on Sina Weibo by propagation structures

Wu, K., Yang, S., & Zhu, K. Q. (2015) · 2015 IEEE 31st International Conference on Data Engineering · doi:10.1109/icde.2015.7113322 · Cited by 585

Dealing with uncertainty in model updating for damage assessment: a review

Simoen, E., De Roeck, G., & Lombaert, G. (2015) · Mechanical Systems and Signal Processing · doi:10.1016/j.ymssp.2014.11.001 · Cited by 540

Scalable Collaborative Filtering with Jointly Derived Neighborhood Interpolation Weights

Bell, R. M., & Koren, Y. (2007) · Seventh IEEE International Conference on Data Mining (ICDM 2007) · doi:10.1109/icdm.2007.90 · Cited by 499

Rotation Averaging

Hartley, R., Trumpf, J., Dai, Y., & Li, H. (2013) · International Journal of Computer Vision · doi:10.1007/s11263-012-0601-0 · Cited by 486

B80Fullerene: An Ab Initio Prediction of Geometry, Stability, and Electronic Structure

Gonzalez Szwacki, N., Sadrzadeh, A., & Yakobson, B. I. (2007) · Physical Review Letters · doi:10.1103/physrevlett.98.166804 · Cited by 478

Evolutionary optimization as applied to inverse scattering problems

Rocca, P., Benedetti, M., Donelli, M., Franceschini, D., & Massa, A. (2009) · Inverse Problems · doi:10.1088/0266-5611/25/12/123003 · Cited by 441

SimPEG: An open source framework for simulation and gradient based parameter estimation in geophysical applications

Cockett, R., Kang, S., Heagy, L. J., Pidlisecky, A., & Oldenburg, D. W. (2015) · Computers & Geosciences · doi:10.1016/j.cageo.2015.09.015 · Cited by 431

Bayesian emulation of complex multi-output and dynamic computer models

Conti, S., & O’Hagan, A. (2010) · Journal of Statistical Planning and Inference · doi:10.1016/j.jspi.2009.08.006 · Cited by 417

The advanced-step NMPC controller: Optimality, stability and robustness

Zavala, V. M., & Biegler, L. T. (2009) · Automatica · doi:10.1016/j.automatica.2008.06.011 · Cited by 417

Non-convex Optimization for Machine Learning

Jain, P., & Kar, P. (2017) · Foundations and Trends® in Machine Learning · doi:10.1561/2200000058 · Cited by 364

Entity Resolution with Markov Logic

Singla, P., & Domingos, P. (2006) · Sixth International Conference on Data Mining (ICDM'06) · doi:10.1109/icdm.2006.65 · Cited by 359

Understanding adversarial training: Increasing local stability of supervised models through robust optimization

Shaham, U., Yamada, Y., & Negahban, S. (2018) · Neurocomputing · doi:10.1016/j.neucom.2018.04.027 · Cited by 355

Reassembling fractured objects by geometric matching

Huang, Q.-X., Flöry, S., Gelfand, N., Hofer, M., & Pottmann, H. (2006) · ACM Transactions on Graphics · doi:10.1145/1141911.1141925 · Cited by 329

QAOA for Max-Cut requires hundreds of qubits for quantum speed-up

Guerreschi, G. G., & Matsuura, A. Y. (2019) · Scientific Reports · doi:10.1038/s41598-019-43176-9 · Cited by 337

Systems biology: parameter estimation for biochemical models

Ashyraliyev, M., Fomekong‐Nanfack, Y., Kaandorp, J. A., & Blom, J. G. (2009) · The FEBS Journal · doi:10.1111/j.1742-4658.2008.06844.x · Cited by 323

FitDock: protein–ligand docking by template fitting

Yang, X., Liu, Y., Gan, J., Xiao, Z.-X., & Cao, Y. (2022) · Briefings in Bioinformatics · doi:10.1093/bib/bbac087 · Cited by 319

Spatial multiomics map of trophoblast development in early pregnancy

Arutyunyan, A., Roberts, K., Troulé, K., Wong, F. C. K., Sheridan, M. A., Kats, I., Garcia-Alonso, L., Velten, B., Hoo, R., Ruiz-Morales, E. R., et al. (2023) · Nature · doi:10.1038/s41586-023-05869-0 · Cited by 303

Random critical point separates brittle and ductile yielding transitions in amorphous materials

Ozawa, M., Berthier, L., Biroli, G., Rosso, A., & Tarjus, G. (2018) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1806156115 · Cited by 298

Tracing Fake-News Footprints: Characterizing Social Media Messages by How They Propagate

Wu, L., & Liu, H. (2018) · Proceedings of the Eleventh ACM International Conference on Web Search and Data Mining · doi:10.1145/3159652.3159677 · Cited by 292

Hybrid approaches to optimization and machine learning methods: a systematic literature review

Azevedo, B. F., Rocha, A. M. A. C., & Pereira, A. I. (2024) · Machine Learning · doi:10.1007/s10994-023-06467-x · Cited by 291

Coordinated Beamforming for MISO Interference Channel: Complexity Analysis and Efficient Algorithms

Liu, Y.-F., Dai, Y.-H., & Luo, Z.-Q. (2011) · IEEE Transactions on Signal Processing · doi:10.1109/tsp.2010.2092772 · Cited by 286

Three-Dimensional Electromagnetic Modelling and Inversion from Theory to Application

Avdeev, D. B. (2005) · Surveys in Geophysics · doi:10.1007/s10712-005-1836-x · Cited by 276

Convex Optimization for Trajectory Generation: A Tutorial on Generating Dynamically Feasible Trajectories Reliably and Efficiently

Malyuta, D., Reynolds, T. P., Szmuk, M., Lew, T., Bonalli, R., Pavone, M., & Açıkmeşe, B. (2022) · IEEE Control Systems · doi:10.1109/mcs.2022.3187542 · Cited by 259

A review of optimization methodologies in support vector machines

Shawe-Taylor, J., & Sun, S. (2011) · Neurocomputing · doi:10.1016/j.neucom.2011.06.026 · Cited by 256

Efficient Search for Diverse Coherent Explanations

Russell, C. (2019) · Proceedings of the Conference on Fairness, Accountability, and Transparency · doi:10.1145/3287560.3287569 · Cited by 218

A comparative evaluation of genetic and gradient-based algorithms applied to aerodynamic optimization

Zingg, D. W., Nemec, M., & Pulliam, T. H. (2008) · European Journal of Computational Mechanics · doi:10.3166/remn.17.103-126 · Cited by 186

Systems biology: model based evaluation and comparison of potential explanations for given biological data

Cedersund, G., & Roll, J. (2009) · The FEBS Journal · doi:10.1111/j.1742-4658.2008.06845.x · Cited by 127

A flexible framework for simulating and fitting generalized drift-diffusion models

Shinn, M., Lam, N. H., & Murray, J. D. (2020) · eLife · doi:10.7554/elife.56938 · Cited by 133

Learning to Hash With Optimized Anchor Embedding for Scalable Retrieval

Guo, Y., Ding, G., Liu, L., Han, J., & Shao, L. (2017) · IEEE Transactions on Image Processing · doi:10.1109/tip.2017.2652730 · Cited by 108

Parameter estimation and determinability analysis applied to Drosophila gap gene circuits

Ashyraliyev, M., Jaeger, J., & Blom, J. G. (2008) · BMC Systems Biology · doi:10.1186/1752-0509-2-83 · Cited by 89

Human generation times across the past 250,000 years

Wang, R. J., Al-Saffar, S. I., Rogers, J., & Hahn, M. W. (2023) · Science Advances · doi:10.1126/sciadv.abm7047 · Cited by 93

Bringing the analysis of animal orientation data full circle: model-based approaches with maximum likelihood

Fitak, R. R., & Johnsen, S. (2017) · Journal of Experimental Biology · doi:10.1242/jeb.167056 · Cited by 92

Image Registration with Guaranteed Displacement Regularity

Haber, E., & Modersitzki, J. (2007) · International Journal of Computer Vision · doi:10.1007/s11263-006-8984-4 · Cited by 88

Scaling up Gaussian Belief Space Planning Through Covariance-Free Trajectory Optimization and Automatic Differentiation

Patil, S., Kahn, G., Laskey, M., Schulman, J., Goldberg, K., & Abbeel, P. (2015) · Springer Tracts in Advanced Robotics · doi:10.1007/978-3-319-16595-0_30 · Cited by 72

PETSc/TAO Users Manual (Rev. 3.19)

Argonne National Laboratory (ANL), A., Balay, S., USDOE Office of Science (SC), A. S. C. R. (., Abhyankar, S., Adams, M., Benson, S., Brown, J., Brune, P., Buschelman, K., Constantinescu, E., et al. (2023) · doi:10.2172/1968587 · Cited by 67

A ready-to-use machine learning tool for symmetric multi-modality registration of brain MRI

Iglesias, J. E. (2023) · Scientific Reports · doi:10.1038/s41598-023-33781-0 · Cited by 64

Passive control of bilinear hysteretic structures by tuned mass damper for narrow band seismic motions

Zhang, Z., & Balendra, T. (2013) · Engineering Structures · doi:10.1016/j.engstruct.2013.03.044 · Cited by 56

Damage Identification in a Truss Tower by Regularized Model Updating

Weber, B., & Paultre, P. (2010) · Journal of Structural Engineering · doi:10.1061/(asce)st.1943-541x.0000105 · Cited by 54