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2017 | Journal Article | IST-REx-ID: 995 |
G. Bighin and M. Lemeshko, “Diagrammatic approach to orbital quantum impurities interacting with a many-particle environment,” Physical Review B - Condensed Matter and Materials Physics, vol. 96, no. 8. American Physical Society, 2017.View | DOI | Download Submitted Version (ext.)
2017 | Journal Article | IST-REx-ID: 996 |
B. Shepperson, A. Chatterley, A. Søndergaard, L. Christiansen, M. Lemeshko, and H. Stapelfeldt, “Strongly aligned molecules inside helium droplets in the near-adiabatic regime,” The Journal of Chemical Physics, vol. 147, no. 1. AIP, 2017.View | DOI | Download Submitted Version (ext.)
2017 | Journal Article | IST-REx-ID: 997 |
E. Yakaboylu, A. Deuchert, and M. Lemeshko, “Emergence of non-abelian magnetic monopoles in a quantum impurity problem,” APS Physics, Physical Review Letters, vol. 119, no. 23. American Physiological Society, 2017.View | DOI | Download Submitted Version (ext.)
2017 | Conference Paper | IST-REx-ID: 998 |
S. A. Rebuffi, A. Kolesnikov, G. Sperl, and C. Lampert, “iCaRL: Incremental classifier and representation learning,” presented at the CVPR: Computer Vision and Pattern Recognition, Honolulu, HA, United States, 2017, vol. 2017, pp. 5533–5542.View | DOI | Download Submitted Version (ext.)
2017 | Book Chapter | IST-REx-ID: 424 |
X. Goaoc, P. Paták, Z. Patakova, M. Tancer, and U. Wagner, “Bounding helly numbers via betti numbers,” in A Journey through Discrete Mathematics: A Tribute to Jiri Matousek, M. Loebl, J. Nešetřil, and R. Thomas, Eds. Springer, 2017, pp. 407–447.View | Files available | DOI | Download Published Version (ext.)
2017 | Conference Paper | IST-REx-ID: 431 |
D.-A. Alistarh, D. Grubic, J. Li, R. Tomioka, and M. Vojnović, “QSGD: Communication-efficient SGD via gradient quantization and encoding,” presented at the NIPS: Neural Information Processing System, Long Beach, CA, United States, 2017, vol. 2017, pp. 1710–1721.View | Download Submitted Version (ext.) | arXiv
2017 | Conference Paper | IST-REx-ID: 432 |
H. Zhang, J. Li, K. Kara, D.-A. Alistarh, J. Liu, and C. Zhang, “ZipML: Training linear models with end-to-end low precision, and a little bit of deep learning,” in Proceedings of Machine Learning Research, Sydney, Australia, 2017, vol. 70, pp. 4035–4043.View | Files available