| Year |
Citation |
Score |
| 2017 |
Li H, Linderman GC, Szlam A, Stanton KP, Kluger Y, Tygert M. Algorithm 971: An Implementation of a Randomized Algorithm for Principal Component Analysis. Acm Transactions On Mathematical Software. Association For Computing Machinery. 43. PMID 28983138 DOI: 10.1145/3004053 |
0.36 |
|
| 2016 |
Tygert M, Bruna J, Chintala S, LeCun Y, Piantino S, Szlam A. A Mathematical Motivation for Complex-Valued Convolutional Networks. Neural Computation. 1-11. PMID 26890348 DOI: 10.1162/NECO_a_00824 |
1 |
|
| 2014 |
Guzzetta NA, Szlam F, Kiser AS, Fernandez JD, Szlam AD, Leong T, Tanaka KA. Augmentation of thrombin generation in neonates undergoing cardiopulmonary bypass. British Journal of Anaesthesia. 112: 319-27. PMID 24193321 DOI: 10.1093/bja/aet355 |
1 |
|
| 2014 |
He Y, Kavukcuoglu K, Wang Y, Szlam A, Qi Y. Unsupervised feature learning by Deep Sparse Coding Siam International Conference On Data Mining 2014, Sdm 2014. 2: 902-910. DOI: 10.1137/1.9781611973440.103 |
1 |
|
| 2014 |
Wang Y, Szlam A. K-mappings and Regression trees Icassp, Ieee International Conference On Acoustics, Speech and Signal Processing - Proceedings. 2937-2941. DOI: 10.1109/ICASSP.2014.6854138 |
1 |
|
| 2014 |
Poling B, Lerman G, Szlam A. Better feature tracking through subspace constraints Proceedings of the Ieee Computer Society Conference On Computer Vision and Pattern Recognition. 3454-3461. DOI: 10.1109/CVPR.2014.441 |
1 |
|
| 2014 |
Bresson X, Tai XC, Chan TF, Szlam A. Multi-class transductive learning based on ℓ1 Relaxations of Cheeger Cut and Mumford-Shah-Potts Model Journal of Mathematical Imaging and Vision. 49: 191-201. DOI: 10.1007/s10851-013-0452-5 |
1 |
|
| 2014 |
Bruna J, Szlam A, Lecun Y. Signal recovery from pooling representations 31st International Conference On Machine Learning, Icml 2014. 2: 1585-1598. |
1 |
|
| 2013 |
Wang Y, Szlam A, Lerman G. Robust locally linear analysis with applications to image denoising and blind inpainting Siam Journal On Imaging Sciences. 6: 526-562. DOI: 10.1137/110843642 |
1 |
|
| 2012 |
Balzano L, Szlam A, Recht B, Nowak R. K-subspaces with missing data 2012 Ieee Statistical Signal Processing Workshop, Ssp 2012. 612-615. DOI: 10.1109/SSP.2012.6319774 |
1 |
|
| 2012 |
He J, Balzano L, Szlam A. Incremental gradient on the Grassmannian for online foreground and background separation in subsampled video Proceedings of the Ieee Computer Society Conference On Computer Vision and Pattern Recognition. 1568-1575. DOI: 10.1109/CVPR.2012.6247848 |
1 |
|
| 2012 |
Zhang T, Szlam A, Wang Y, Lerman G. Hybrid linear modeling via local best-fit flats International Journal of Computer Vision. 100: 217-240. DOI: 10.1007/s11263-012-0535-6 |
1 |
|
| 2012 |
Szlam A, Gregor K, LeCun Y. Fast approximations to structured sparse coding and applications to object classification Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). 7576: 200-213. DOI: 10.1007/978-3-642-33715-4_15 |
1 |
|
| 2011 |
Gregor K, Szlam A, LeCun Y. Structured sparse coding via lateral inhibition Advances in Neural Information Processing Systems 24: 25th Annual Conference On Neural Information Processing Systems 2011, Nips 2011. |
1 |
|
| 2010 |
Szlam F, Luan D, Bolliger D, Szlam AD, Levy JH, Varner JD, Tanaka KA. Anti-factor IXa Aptamer reduces propagation of thrombin generation in plasma anticoagulated with warfarin. Thrombosis Research. 125: 432-7. PMID 20004955 DOI: 10.1016/j.thromres.2009.11.018 |
1 |
|
| 2010 |
Szlam A, Guo Z, Osher S. A split Bregman method for non-negative sparsity penalized least squares with applications to hyperspectral demixing Proceedings - International Conference On Image Processing, Icip. 1917-1920. DOI: 10.1109/ICIP.2010.5651881 |
1 |
|
| 2010 |
Zhang T, Szlam A, Wang Y, Lerman G. Randomized hybrid linear modeling by local best-fit flats Proceedings of the Ieee Computer Society Conference On Computer Vision and Pattern Recognition. 1927-1934. DOI: 10.1109/CVPR.2010.5539866 |
1 |
|
| 2010 |
Szlam A, Bresson X. Total variation and Cheeger cuts Icml 2010 - Proceedings, 27th International Conference On Machine Learning. 1039-1046. |
1 |
|
| 2009 |
Szlam A, Sapiro G. Discriminative k-metrics Proceedings of the 26th International Conference On Machine Learning, Icml 2009. 1009-1016. DOI: 10.1145/1553374.1553503 |
1 |
|
| 2009 |
Rokhlin V, Szlam A, Tygert M. A randomized algorithm for principal component analysis Siam Journal On Matrix Analysis and Applications. 31: 1100-1124. DOI: 10.1137/080736417 |
1 |
|
| 2009 |
Szlam A, Sapiro G. Discriminative k metrics and the Chan-Vese model for object detection and segmentation Proceedings of Spie - the International Society For Optical Engineering. 7446. DOI: 10.1117/12.825800 |
1 |
|
| 2009 |
Zhang T, Szlam A, Lerman G. Median K-flats for hybrid linear modeling with many outliers 2009 Ieee 12th International Conference On Computer Vision Workshops, Iccv Workshops 2009. 234-241. DOI: 10.1109/ICCVW.2009.5457695 |
1 |
|
| 2009 |
Szlam A. Asymptotic regularity of subdivisions of Euclidean domains by iterated PCA and iterated 2-means Applied and Computational Harmonic Analysis. 27: 342-350. DOI: 10.1016/j.acha.2009.02.006 |
1 |
|
| 2009 |
Houhou N, Bresson X, Szlam A, Chan TF, Thiran JP. Semi-supervised segmentation based on non-local continuous min-cut Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). 5567: 112-123. DOI: 10.1007/978-3-642-02256-2_10 |
1 |
|
| 2008 |
Szlam AD, Maggioni M, Coifman RR. Regularization on graphs with function-adapted diffusion processes Journal of Machine Learning Research. 9: 1711-1739. |
1 |
|
| 2006 |
Coifman RR, Lafon S, Maggioni M, Keller Y, Szlam AD, Warner FJ, Zucker SW. Geometries of sensor outputs, inference and information processing Proceedings of Spie - the International Society For Optical Engineering. 6232. DOI: 10.1117/12.669723 |
1 |
|
| 2006 |
Bremer JC, Coifman RR, Maggioni M, Szlam AD. Diffusion wavelet packets Applied and Computational Harmonic Analysis. 21: 95-112. DOI: 10.1016/j.acha.2006.04.005 |
1 |
|
| 2005 |
Szlam AD, Maggioni M, Coifman RR, Bremer JC. Diffusion-driven multiscale analysis on manifolds and graphs: Top-down and bottom-up constructions Proceedings of Spie - the International Society For Optical Engineering. 5914: 1-11. DOI: 10.1117/12.616931 |
1 |
|
| 2005 |
Maggioni M, Bremer JC, Coifman RR, Szlam AD. Biorthogonal diffusion wavelets for multiscale representations on manifolds and graphs Proceedings of Spie - the International Society For Optical Engineering. 5914: 1-13. DOI: 10.1117/12.616909 |
1 |
|
| 2001 |
Szlam AD. Monochromatic Translates of Configurations in the Plane Journal of Combinatorial Theory. Series A. 93: 173-176. DOI: 10.1006/jcta.2000.3065 |
1 |
|
| Low-probability matches |
| 2020 |
Fan A, Urbanek J, Ringshia P, Dinan E, Qian E, Karamcheti S, Prabhumoye S, Kiela D, Rocktaschel T, Szlam A, Weston J. Generating Interactive Worlds with Text Proceedings of the Aaai Conference On Artificial Intelligence. 34: 1693-1700. DOI: 10.1609/aaai.v34i02.5532 |
0.01 |
|
| 2017 |
Szlam A, Tulloch A, Tygert M. Accurate Low-Rank Approximations Via a Few Iterations of Alternating Least Squares Siam Journal On Matrix Analysis and Applications. 38: 425-433. DOI: 10.1137/16M1064556 |
0.01 |
|
| 2017 |
Bronstein MM, Bruna J, LeCun Y, Szlam A, Vandergheynst P. Geometric Deep Learning: Going beyond Euclidean data Ieee Signal Processing Magazine. 34: 18-42. DOI: 10.1109/MSP.2017.2693418 |
0.01 |
|
| 2017 |
Chintala S, Ranzato M, Szlam A, Tian Y, Tygert M, Zaremba W. Scale-invariant learning and convolutional networks Applied and Computational Harmonic Analysis. 42: 154-166. DOI: 10.1016/J.ACHA.2016.06.005 |
0.01 |
|
| 2016 |
Rice NT, Szlam F, Varner JD, Bernstein PS, Szlam AD, Tanaka KA. Differential Contributions of Intrinsic and Extrinsic Pathways to Thrombin Generation in Adult, Maternal and Cord Plasma Samples. Plos One. 11: e0154127. PMID 27196067 DOI: 10.1371/journal.pone.0154127 |
0.01 |
|
| Hide low-probability matches. |