| Year |
Citation |
Score |
| 2021 |
Fong J, Gardner JR, Andrews JM, Cashen AF, Payton JE, Weinberger KQ, Edwards JR. Determining subpopulation methylation profiles from bisulfite sequencing data of heterogeneous samples using DXM. Nucleic Acids Research. PMID 34157105 DOI: 10.1093/nar/gkab516 |
0.641 |
|
| 2015 |
Song XD, Wallace BM, Gardner JR, Ledbetter NM, Weinberger KQ, Barbour DL. Fast, Continuous Audiogram Estimation Using Machine Learning. Ear and Hearing. PMID 26258575 DOI: 10.1097/Aud.0000000000000186 |
0.671 |
|
| 2015 |
Zhou Q, Chen W, Song S, Gardner JR, Weinberger KQ, Chen Y. A reduction of the Elastic Net to Support Vector machines with an application to GPU computing Proceedings of the National Conference On Artificial Intelligence. 4: 3210-3216. |
0.329 |
|
| 2015 |
Kusner MJ, Gardner JR, Garnett R, Weinberger KQ. Differentially private Bayesian optimization 32nd International Conference On Machine Learning, Icml 2015. 2: 918-927. |
0.343 |
|
| 2015 |
Chen Z, Chen M, Weinberger KQ, Zhang W. Marginalized denoising for link prediction and multi-label learning Proceedings of the National Conference On Artificial Intelligence. 3: 1707-1713. |
0.364 |
|
| 2015 |
Chen M, Weinberger KQ, Xu Z, Sha F. Marginalizing Stacked linear denoising autoencoders Journal of Machine Learning Research. 16: 3849-3875. |
0.627 |
|
| 2014 |
Chen W, Chen Y, Weinberger KQ. Fast flux discriminant for large-scale sparse nonlinear classification Proceedings of the Acm Sigkdd International Conference On Knowledge Discovery and Data Mining. 621-630. DOI: 10.1145/2623330.2623627 |
0.325 |
|
| 2014 |
Kusner MJ, Chen W, Zhou Q, Xu Z, Weinberger KQ, Chen Y. Feature-cost sensitive learning with submodular trees of classifiers Proceedings of the National Conference On Artificial Intelligence. 3: 1939-1945. |
0.319 |
|
| 2013 |
Chen W, Chen Y, Weinberger KQ, Lu Q, Chen X. Goal-oriented euclidean heuristics with manifold learning Proceedings of the 27th Aaai Conference On Artificial Intelligence, Aaai 2013. 173-179. |
0.328 |
|
| 2013 |
Xu Z, Kusner MJ, Huang G, Weinberger KQ. Anytime representation learning 30th International Conference On Machine Learning, Icml 2013. 2113-2121. |
0.318 |
|
| 2013 |
Chen W, Weinberger KQ, Chen Y. Maximum Variance Correction with application to A*search 30th International Conference On Machine Learning, Icml 2013. 302-310. |
0.355 |
|
| 2012 |
Xu Z, Chen M, Weinberger KQ, Sha F. From sBoW to dCoT marginalized encoders for text representation Acm International Conference Proceeding Series. 1879-1884. DOI: 10.1145/2396761.2398536 |
0.597 |
|
| 2012 |
Chen M, Xu Z, Weinberger KQ, Sha F. Marginalized denoising autoencoders for domain adaptation Proceedings of the 29th International Conference On Machine Learning, Icml 2012. 1: 767-774. |
0.616 |
|
| 2012 |
Kedem D, Tyree S, Weinberger KQ, Sha F, Lanckriet G. Non-linear metric learning Advances in Neural Information Processing Systems. 4: 2573-2581. |
0.595 |
|
| 2011 |
Chapelle O, Shivaswamy P, Vadrevu S, Weinberger K, Zhang Y, Tseng B. Boosted multi-task learning Machine Learning. 85: 149-173. DOI: 10.1007/S10994-010-5231-6 |
0.444 |
|
| 2010 |
Weinberger K, Sha F, Saul L. Convex optimizations for distance metric learning and pattern classification Ieee Signal Processing Magazine. 27: 146-150+158. DOI: 10.1109/Msp.2010.936013 |
0.735 |
|
| 2010 |
Parameswaran S, Weinberger KQ. Large margin multi-task metric learning Advances in Neural Information Processing Systems 23: 24th Annual Conference On Neural Information Processing Systems 2010, Nips 2010. |
0.333 |
|
| 2009 |
Bai B, Weston J, Grangier D, Collobert R, Sadamasa K, Qi Y, Chapelle O, Weinberger K. Learning to rank with (a lot of) word features Information Retrieval. 13: 291-314. DOI: 10.1007/S10791-009-9117-9 |
0.341 |
|
| 2009 |
Weinberger KQ, Saul LK. Distance metric learning for large margin nearest neighbor classification Journal of Machine Learning Research. 10: 207-244. |
0.677 |
|
| 2009 |
Weinberger KQ, Saul LK. Distance metric learning for large margin nearest neighbor classification Journal of Machine Learning Research. 10: 207-244. |
0.408 |
|
| 2008 |
Lewis JM, Weinberger KQ, Hull PM, Saul LK. Mapping uncharted waters: Exploratory analysis, visualization, and clustering of oceanographic data Proceedings - 7th International Conference On Machine Learning and Applications, Icmla 2008. 388-395. DOI: 10.1109/ICMLA.2008.125 |
0.62 |
|
| 2008 |
Weinberger KQ, Saul LK. Fast solvers and efficient implementations for distance metric learning Proceedings of the 25th International Conference On Machine Learning. 1160-1167. |
0.682 |
|
| 2007 |
Weinberger KQ, Sha F, Zhu Q, Saul LK. Graph Laplacian regularization for large-scale semidefinite programming Advances in Neural Information Processing Systems. 1489-1496. |
0.562 |
|
| 2007 |
Weinberger KQ, Tesauro G. Metric learning for kernel regression Journal of Machine Learning Research. 2: 612-619. |
0.391 |
|
| 2006 |
Weinberger KQ, Saul LK. Unsupervised learning of image manifolds by semidefinite programming International Journal of Computer Vision. 70: 77-90. DOI: 10.1007/S11263-005-4939-Z |
0.631 |
|
| 2006 |
Weinberger KQ, Saul LK. An introduction to nonlinear dimensionality reduction by maximum variance unfolding Proceedings of the National Conference On Artificial Intelligence. 2: 1683-1686. |
0.672 |
|
| 2005 |
Weinberger KQ, Packer BD, Saul LK. Nonlinear dimensionality reduction by semidefinite programming and kernel matrix factorization Aistats 2005 - Proceedings of the 10th International Workshop On Artificial Intelligence and Statistics. 381-388. |
0.656 |
|
| 2005 |
Blitzer J, Weinberger KQ, Saul LK, Pereira FCN. Hierarchical distributed representations for statistical language modeling Advances in Neural Information Processing Systems. |
0.585 |
|
| 2004 |
Weinberger KQ, Sha F, Saul LK. Learning a kernel matrix for nonlinear dimensionality reduction Proceedings, Twenty-First International Conference On Machine Learning, Icml 2004. 839-846. |
0.633 |
|
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