Grzegorz Swirszcz
Grzegorz Swirszcz
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Zitiert von
Zitiert von
Sobolev training for neural networks
WM Czarnecki, S Osindero, M Jaderberg, G Swirszcz, R Pascanu
Advances in neural information processing systems 30, 2017
Grouped orthogonal matching pursuit for variable selection and prediction
G Swirszcz, N Abe, AC Lozano
Advances in Neural Information Processing Systems 22, 2009
Maximum weight independent sets and matchings in sparse random graphs. Exact results using the local weak convergence method
D Gamarnik, T Nowicki, G Swirszcz
Random Structures & Algorithms 28 (1), 76-106, 2006
Winning the KDD cup orange challenge with ensemble selection
A Niculescu-Mizil, C Perlich, G Swirszcz, V Sindhwani, Y Liu, P Melville, ...
KDD-Cup 2009 Competition, 23-34, 2009
Distilling policy distillation
WM Czarnecki, R Pascanu, S Osindero, S Jayakumar, G Swirszcz, ...
The 22nd international conference on artificial intelligence and statistics …, 2019
l1 Regularization in Infinite Dimensional Feature Spaces.
S Rosset, G Swirszcz, N Srebro, J Zhu
COLT, 544-558, 2007
Multi-level lasso for sparse multi-task regression
AC Lozano, G Swirszcz
Proceedings of the 29th International Coference on International Conference …, 2012
Understanding synthetic gradients and decoupled neural interfaces
WM Czarnecki, G Świrszcz, M Jaderberg, S Osindero, O Vinyals, ...
International Conference on Machine Learning, 904-912, 2017
Group orthogonal matching pursuit for logistic regression
A Lozano, G Swirszcz, N Abe
Proceedings of the fourteenth international conference on artificial …, 2011
Local minima in training of neural networks
G Swirszcz, WM Czarnecki, R Pascanu
arXiv preprint arXiv:1611.06310, 2016
On the limit cycles of polynomial vector fields
J Llibre, G Swirszcz
Dyn. Contin. Discrete Impuls. Syst. Ser. A Math. Anal 18 (2), 203-214, 2011
Methods and systems for variable group selection and temporal causal modeling
N Abe, Y Liu, AC Lozano, S Rosset, G Swirszcz
US Patent 8,255,346, 2012
Medical data mining: insights from winning two competitions
S Rosset, C Perlich, G Świrszcz, P Melville, Y Liu
Data Mining and Knowledge Discovery 20, 439-468, 2010
Discovering faster matrix multiplication algorithms with reinforcement learning
A Fawzi, M Balog, A Huang, T Hubert, B Romera-Paredes, M Barekatain, ...
Nature 610 (7930), 47-53, 2022
Multi-level lasso for sparse multi-task regression
G Swirszcz, AC Lozano
Proceedings of the 29th International Conference on Machine Learning (ICML …, 2012
Method and system for scheduling delivery of at least one of goods and services
F Barahona, SJ Buckley, PR Chowdhary, JJ Forrest, TJ Kimbrel, ...
US Patent App. 11/443,068, 2007
Verification of non-linear specifications for neural networks
C Qin, B O'Donoghue, R Bunel, R Stanforth, S Gowal, J Uesato, ...
arXiv preprint arXiv:1902.09592, 2019
Local minima in training of deep networks
G Swirszcz, WM Czarnecki, R Pascanu
Invariant algebraic curves of large degree for quadratic system
C Christopher, J Llibre, G Świrszcz
Journal of mathematical analysis and applications 303 (2), 450-461, 2005
On cross-validation and stacking: Building seemingly predictive models on random data
C Perlich, G Świrszcz
ACM SIGKDD Explorations Newsletter 12 (2), 11-15, 2011
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