Arthur Szlam, PhD

Mathematics City College of New York, New York, NY, United States 
learning, vision
"Arthur Szlam"
Mean distance: 16.81 (cluster 17)
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Bronstein MM, Bruna J, LeCun Y, et al. (2017) Geometric Deep Learning: Going beyond Euclidean data Ieee Signal Processing Magazine. 34: 18-42
Chintala S, Ranzato M, Szlam A, et al. (2017) Scale-invariant learning and convolutional networks Applied and Computational Harmonic Analysis. 42: 154-166
Tygert M, Bruna J, Chintala S, et al. (2016) A Mathematical Motivation for Complex-Valued Convolutional Networks. Neural Computation. 1-11
He Y, Kavukcuoglu K, Wang Y, et al. (2014) Unsupervised feature learning by Deep Sparse Coding Siam International Conference On Data Mining 2014, Sdm 2014. 2: 902-910
Bresson X, Tai XC, Chan TF, et al. (2014) 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
Bruna J, Szlam A, Lecun Y. (2014) Signal recovery from pooling representations 31st International Conference On Machine Learning, Icml 2014. 2: 1585-1598
Szlam A, Gregor K, LeCun Y. (2012) 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
Gregor K, Szlam A, LeCun Y. (2011) Structured sparse coding via lateral inhibition Advances in Neural Information Processing Systems 24: 25th Annual Conference On Neural Information Processing Systems 2011, Nips 2011
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