Oluwasanmi Oluseye Koyejo

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Research Output

A constrained matrix-variate Gaussian process for transposable data

Koyejo, O., Lee, C. & Ghosh, J., Oct 2014, In : Machine Learning. 97, 1-2, p. 103-127 25 p.

Research output: Contribution to journalArticle

A deflation method for structured probabilistic PCA

Khanna, R., Ghosh, J., Poldrack, R. & Koyejo, O., Jan 1 2017, Proceedings of the 17th SIAM International Conference on Data Mining, SDM 2017. Chawla, N. & Wang, W. (eds.). Society for Industrial and Applied Mathematics Publications, p. 534-542 9 p. (Proceedings of the 17th SIAM International Conference on Data Mining, SDM 2017).

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Aggregation for Sensitive Data

Bhowmik, A., Ghosh, J. & Koyejo, O., Jul 2019, 2019 13th International Conference on Sampling Theory and Applications, SampTA 2019. Institute of Electrical and Electronics Engineers Inc., 9030955. (2019 13th International Conference on Sampling Theory and Applications, SampTA 2019).

Research output: Chapter in Book/Report/Conference proceedingConference contribution

A kernel-based approach to exploiting interaction-networks in heterogeneous information sources for improved recommender systems

Koyejo, O. & Ghosh, J., Nov 23 2011, Proceedings of the 2nd International Workshop on Information Heterogeneity and Fusion in Recommender Systems, HetRec 2011 - Held at the 5th ACM Conference on Recommender Systems, RecSys 2011. p. 9-16 8 p. (Proceedings of the 2nd International Workshop on Information Heterogeneity and Fusion in Recommender Systems, HetRec 2011 - Held at the 5th ACM Conference on Recommender Systems, RecSys 2011).

Research output: Chapter in Book/Report/Conference proceedingConference contribution

A simple and provable algorithm for sparse diagonal CCA

Asteris, M., Kyrillidis, A., Koyejo, O. & Poldrack, R., Jan 1 2016, 33rd International Conference on Machine Learning, ICML 2016. Weinberger, K. Q. & Balcan, M. F. (eds.). International Machine Learning Society (IMLS), p. 1774-1783 10 p. (33rd International Conference on Machine Learning, ICML 2016; vol. 3).

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Bayesian structure learning for dynamic brain connectivity

Andersen, M. R., Winther, O., Hansen, L. K., Poldrack, R. & Koyejo, O., Jan 1 2018, p. 1436-1446. 11 p.

Research output: Contribution to conferencePaper

Bayesian structure learning for functional neuroimaging

Park, M., Koyejo, O. O., Ghosh, J., Poldrack, R. A. & Pillow, J. W., 2013, In : Journal of Machine Learning Research. 31, p. 489-497 9 p.

Research output: Contribution to journalArticle

Binary classification with karmic, threshold-quasi-concave metrics

Yan, B., Koyejo, O., Zhong, K. & Ravikumar, P., Jan 1 2018, 35th International Conference on Machine Learning, ICML 2018. Dy, J. & Krause, A. (eds.). International Machine Learning Society (IMLS), p. 8792-8804 13 p. (35th International Conference on Machine Learning, ICML 2018; vol. 12).

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Clustered fused graphical Lasso

Zhu, Y. & Koyejo, O., Jan 1 2018, 34th Conference on Uncertainty in Artificial Intelligence 2018, UAI 2018. Globerson, A., Globerson, A. & Silva, R. (eds.). Association For Uncertainty in Artificial Intelligence (AUAI), p. 487-496 10 p. (34th Conference on Uncertainty in Artificial Intelligence 2018, UAI 2018; vol. 1).

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Clustered monotone transforms for rating factorization

Hiranandani, G., Koyejo, O., Somani, R. & Acharyya, S., Jan 30 2019, WSDM 2019 - Proceedings of the 12th ACM International Conference on Web Search and Data Mining. Association for Computing Machinery, Inc, p. 132-140 9 p. (WSDM 2019 - Proceedings of the 12th ACM International Conference on Web Search and Data Mining).

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Consistency analysis for binary classification revisited

Dembczyriski, K., Kottowski, W., Koyejo, O. & Natarajan, N., Jan 1 2017, 34th International Conference on Machine Learning, ICML 2017. International Machine Learning Society (IMLS), p. 1597-1613 17 p. (34th International Conference on Machine Learning, ICML 2017; vol. 3).

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Consistent binary classification with generalized performance metrics

Koyejo, O., Natarajan, N., Ravikumar, P. & Dhillon, I. S., Jan 1 2014, In : Advances in Neural Information Processing Systems. 3, January, p. 2744-2752 9 p.

Research output: Contribution to journalConference article

Consistent multilabel classification

Koyejo, O., Natarajan, N., Ravikumar, P. & Dhillon, I. S., Jan 1 2015, In : Advances in Neural Information Processing Systems. 2015-January, p. 3321-3329 9 p.

Research output: Contribution to journalConference article

Constrained Bayesian inference for low rank multitask learning

Koyejo, O. O. & Ghosh, J., Nov 28 2013, p. 341-350. 10 p.

Research output: Contribution to conferencePaper

Constrained Gaussian process regression for gene-disease association

Koyejo, O., Lee, C. & Ghosh, J., Jan 1 2013, p. 72-79. 8 p.

Research output: Contribution to conferencePaper

Decoding brain activity using a large-scale probabilistic functional-anatomical atlas of human cognition

Rubin, T. N., Koyejo, O., Gorgolewski, K. J., Jones, M. N., Poldrack, R. A. & Yarkoni, T., Oct 2017, In : PLoS computational biology. 13, 10, e1005649.

Research output: Contribution to journalArticle

Dependent relevance determination for smooth and structured sparse regression

Wu, A., Koyejo, O. & Pillow, J., May 1 2019, In : Journal of Machine Learning Research. 20

Research output: Contribution to journalArticle

Effects of thresholding on correlation-based image similarity metrics

Sochat, V. V., Gorgolewski, K. J., Koyejo, O., Durnez, J. & Poldrack, R. A., 2015, In : Frontiers in Neuroscience. 9, OCT, 418.

Research output: Contribution to journalArticle

Estimation of dynamic functional connectivity using Multiplication of Temporal Derivatives

Shine, J. M., Koyejo, O., Bell, P. T., Gorgolewski, K. J., Gilat, M. & Poldrack, R. A., Nov 15 2015, In : NeuroImage. 122, p. 399-407 9 p.

Research output: Contribution to journalArticle

Examples are not enough, learn to criticize! Criticism for interpretability

Kim, B., Khanna, R. & Koyejo, O., Jan 1 2016, In : Advances in Neural Information Processing Systems. p. 2288-2296 9 p.

Research output: Contribution to journalConference article

Fall of empires: Breaking byzantine-tolerant SGD by inner product manipulation

Xie, C., Koyejo, O. & Gupta, I., 2019.

Research output: Contribution to conferencePaper

False Discovery Rate Smoothing

Tansey, W., Koyejo, O., Poldrack, R. A. & Scott, J. G., Jul 3 2018, In : Journal of the American Statistical Association. 113, 523, p. 1156-1171 16 p.

Research output: Contribution to journalArticle

FMRI data augmentation via synthesis

Zhuang, P., Schwing, A. G. & Koyejo, O., Apr 2019, ISBI 2019 - 2019 IEEE International Symposium on Biomedical Imaging. IEEE Computer Society, p. 1783-1787 5 p. 8759585. (Proceedings - International Symposium on Biomedical Imaging; vol. 2019-April).

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Frequency domain predictive modelling with aggregated data

Bhowmik, A., Ghosh, J. & Koyejo, O., 2017.

Research output: Contribution to conferencePaper

Generalized correspondence-LDA models (GC-LDA) for identifying functional regions in the brain

Rubin, T. N., Koyejo, O., Jones, M. N. & Yarkoni, T., Jan 1 2016, In : Advances in Neural Information Processing Systems. p. 1126-1134 9 p.

Research output: Contribution to journalConference article

Generalized linear models for aggregated data

Bhowmik, A., Ghosh, J. & Koyejo, O., Jan 1 2015, In : Journal of Machine Learning Research. 38, p. 93-101 9 p.

Research output: Contribution to journalConference article

Human cognition involves the dynamic integration of neural activity and neuromodulatory systems

Shine, J. M., Breakspear, M., Bell, P. T., Ehgoetz Martens, K., Shine, R., Koyejo, O., Sporns, O. & Poldrack, R. A., Feb 1 2019, In : Nature Neuroscience. 22, 2, p. 289-296 8 p.

Research output: Contribution to journalArticle

Identifying candidate disease genes using a trace norm constrained bipartite raking model

Lee, C. H., Koyejo, O. & Ghosh, J., Oct 31 2013, 2013 35th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2013. p. 3459-3462 4 p. 6610286. (Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS).

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Information projection and approximate inference for structured sparse variables

Khanna, R., Ghosh, J., Poldrack, R. & Koyejo, O., 2017.

Research output: Contribution to conferencePaper

Interpreting black box predictions using fisher kernels

Khanna, R., Kim, B., Ghosh, J. & Koyejo, O., 2020.

Research output: Contribution to conferencePaper

Joint nonparametric precision matrix estimation with confounding

Geng, S., Kolar, M. & Koyejo, O., 2019.

Research output: Contribution to conferencePaper

Learning predictive cognitive structure from fMRI using supervised topic models

Koyejo, O., Patel, P., Ghosh, J. & Poldrack, R. A., Oct 15 2013, Proceedings - 2013 3rd International Workshop on Pattern Recognition in Neuroimaging, PRNI 2013. p. 9-12 4 p. 6603544. (Proceedings - 2013 3rd International Workshop on Pattern Recognition in Neuroimaging, PRNI 2013).

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Learning to rankwith bregman divergences and monotone retargeting

Acharyya, S., Koyejo, O. & Ghosh, J., Dec 1 2012, Uncertainty in Artificial Intelligence - Proceedings of the 28th Conference, UAI 2012. p. 16-25 10 p. (Uncertainty in Artificial Intelligence - Proceedings of the 28th Conference, UAI 2012).

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Long-term neural and physiological phenotyping of a single human

Poldrack, R. A., Laumann, T. O., Koyejo, O., Gregory, B., Hover, A., Chen, M. Y., Gorgolewski, K. J., Luci, J., Joo, S. J., Boyd, R. L., Hunicke-Smith, S., Simpson, Z. B., Caven, T., Sochat, V., Shine, J. M., Gordon, E., Snyder, A. Z., Adeyemo, B., Petersen, S. E., Glahn, D. C. & 11 others, Mckay, D. R., Curran, J. E., Göring, H. H. H., Carless, M. A., Blangero, J., Dougherty, R., Leemans, A., Handwerker, D. A., Frick, L., Marcotte, E. M. & Mumford, J. A., Dec 9 2015, In : Nature communications. 6, 8885.

Research output: Contribution to journalArticle

Message from the Program Chairs

Ryali, S., Chen, T., Ng, B. & Koyejo, S., Sep 16 2015, In : Proceedings - 2015 International Workshop on Pattern Recognition in NeuroImaging, PRNI 2015. p. ix 7270829.

Research output: Contribution to journalEditorial

MiPPS: A generative model for multi-manifold clustering

Koyejo, O. & Ghosh, J., Dec 1 2009, Manifold Learning and Its Applications - Papers from the AAAI Fall Symposium, Technical Report. p. 18-25 8 p. (AAAI Fall Symposium - Technical Report; vol. FS-09-04).

Research output: Chapter in Book/Report/Conference proceedingConference contribution

MRIQC: Advancing the automatic prediction of image quality in MRI from unseen sites

Esteban, O., Birman, D., Schaer, M., Koyejo, O. O., Poldrack, R. A. & Gorgolewski, K. J., Sep 2017, In : PloS one. 12, 9, e0184661.

Research output: Contribution to journalArticle

On prior distributions and approximate inference for structured variables

Koyejo, O., Khanna, R., Ghosh, J. & Poldrack, R. A., Jan 1 2014, In : Advances in Neural Information Processing Systems. 1, January, p. 676-684 9 p.

Research output: Contribution to journalConference article

Optimal classification with multivariate losses

Natarajan, N., Koyejo, O., Ravikumar, P. & Dhillon, I. S., Jan 1 2016, 33rd International Conference on Machine Learning, ICML 2016. Weinberger, K. Q. & Balcan, M. F. (eds.). International Machine Learning Society (IMLS), p. 2283-2295 13 p. (33rd International Conference on Machine Learning, ICML 2016; vol. 4).

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Partially linear additive Gaussian graphical models

Geng, S., Yan, M., Kolar, M. & Koyejo, O., Jan 1 2019, 36th International Conference on Machine Learning, ICML 2019. International Machine Learning Society (IMLS), p. 3827-3847 21 p. (36th International Conference on Machine Learning, ICML 2019; vol. 2019-June).

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Performance metric elicitation from pairwise classifier comparisons

Hiranandani, G., Boodaghians, S., Mehta, R. & Koyejo, O., 2020.

Research output: Contribution to conferencePaper

Preface: Manifold learning and its applications

Koyejo, O. & Souvenir, R., Dec 1 2010, In : AAAI Fall Symposium - Technical Report. FS-10-06

Research output: Contribution to journalEditorial

Preference completion from partial rankings

Gunasekar, S., Koyejo, O. & Ghosh, J., Jan 1 2016, In : Advances in Neural Information Processing Systems. p. 1378-1386 9 p.

Research output: Contribution to journalConference article

Rényi divergence minimization based co-regularized multiview clustering

Joshi, S., Ghosh, J., Reid, M. & Koyejo, O., Sep 1 2016, In : Machine Learning. 104, 2-3, p. 411-439 29 p.

Research output: Contribution to journalArticle

Reports of the AAAI 2010 fall symposia

Azevedo, R., Biswas, G., Bohus, D., Carmichael, T., Finlayson, M. A., Hadzikadic, M., Havasi, C., Horvitz, E., Kanda, T., Koyejo, O. O., Lawless, W. F., Lenat, D., Meneguzzi, F., Mutlu, B., Oh, J., Pirrone, R., Raux, A., Sofge, D. A., Sukthankar, G., Van Durme, B. & 1 others, Yorke-Smith, N., Mar 2011, In : AI Magazine. 32, 1, p. 93-100 8 p.

Research output: Contribution to journalArticle

Reports on the AAAI 2009 fall symposia

Azevedo, R., Bench-Capon, T., Biswas, G., Carmichael, T., Green, N., Hadzikadic, M., Koyejo, O., Kurup, U., Parsons, S., Pirrone, R., Prakken, H., Samsonovich, A., Scott, D. & Souvenir, R., Jan 1 2010, In : AI Magazine. 31, 1, p. 88-94 7 p.

Research output: Contribution to journalArticle

Retargeted matrix factorization for collaborative filtering

Koyejo, O. O., Acharyya, S. & Ghosh, J., Nov 20 2013, RecSys 2013 - Proceedings of the 7th ACM Conference on Recommender Systems. p. 49-56 8 p. (RecSys 2013 - Proceedings of the 7th ACM Conference on Recommender Systems).

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Simultaneous prognosis and exploratory analysis of multiple chronic conditions using clinical notes

Joshi, S., Koyejo, O., Resurreccion, K. & Ghosh, J., Dec 8 2015, Proceedings - 2015 IEEE International Conference on Healthcare Informatics, ICHI 2015. Fu, W-T., Balakrishnan, P., Harabagiu, S., Wang, F. & Srivatsava, J. (eds.). Institute of Electrical and Electronics Engineers Inc., p. 243-252 10 p. 7349697. (Proceedings - 2015 IEEE International Conference on Healthcare Informatics, ICHI 2015).

Research output: Chapter in Book/Report/Conference proceedingConference contribution

SLSGD: Secure and Efficient Distributed On-device Machine Learning

Xie, C., Koyejo, O. & Gupta, I., 2020, Machine Learning and Knowledge Discovery in Databases - European Conference, ECML PKDD 2019, Proceedings. Brefeld, U., Fromont, E., Hotho, A., Knobbe, A., Maathuis, M. & Robardet, C. (eds.). Springer, p. 213-228 16 p. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); vol. 11907 LNAI).

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Sparse Bayesian structure learning with dependent relevance determination prior

Wu, A., Park, M., Koyejo, O. & Pillow, J. W., 2014, In : Advances in Neural Information Processing Systems. 2, January, p. 1628-1636 9 p.

Research output: Contribution to journalConference article