Albert Gu
Albert Gu
Verified email at stanford.edu
Title
Cited by
Cited by
Year
Representation tradeoffs for hyperbolic embeddings
C De Sa, A Gu, C Ré, F Sala
Proceedings of machine learning research 80, 4460, 2018
982018
The power of deferral: maintaining a constant-competitive steiner tree online
A Gu, A Gupta, A Kumar
SIAM Journal on Computing 45 (1), 1-28, 2016
382016
Learning mixed-curvature representations in product spaces
A Gu, F Sala, B Gunel, C Ré
International Conference on Learning Representations, 2018
322018
A kernel theory of modern data augmentation
T Dao, A Gu, AJ Ratner, V Smith, C De Sa, C Ré
Proceedings of machine learning research 97, 1528, 2019
242019
Learning compressed transforms with low displacement rank
A Thomas, A Gu, T Dao, A Rudra, C Ré
Advances in neural information processing systems, 9052-9060, 2018
122018
Learning fast algorithms for linear transforms using butterfly factorizations
T Dao, A Gu, M Eichhorn, A Rudra, C Ré
Proceedings of machine learning research 97, 1517, 2019
92019
Christopher Ré. A kernel theory of modern data augmentation
T Dao, A Gu, AJ Ratner, V Smith, C De Sa
arXiv preprint arXiv:1803.06084, 2018
52018
A two-pronged progress in structured dense matrix vector multiplication
C De Sa, A Cu, R Puttagunta, C Ré, A Rudra
Proceedings of the Twenty-Ninth Annual ACM-SIAM Symposium on Discrete …, 2018
52018
Recurrence width for structured dense matrix vector multiplication
A Gu, R Puttagunta, C Ré, A Rudra
arXiv preprint arXiv:1611.01569, 2016
22016
HiPPO: Recurrent Memory with Optimal Polynomial Projections
A Gu, T Dao, S Ermon, A Rudra, C Re
arXiv preprint arXiv:2008.07669, 2020
12020
Sparse Recovery for Orthogonal Polynomial Transforms
A Gilbert, A Gu, C Re, A Rudra, M Wootters
arXiv preprint arXiv:1907.08362, 2019
12019
Learning invariance with compact transforms
AT Thomas, A Gu, T Dao, A Rudra, C Ré
12018
Model Patching: Closing the Subgroup Performance Gap with Data Augmentation
K Goel, A Gu, Y Li, C Ré
arXiv preprint arXiv:2008.06775, 2020
2020
Improving the Gating Mechanism of Recurrent Neural Networks
A Gu, C Gulcehre, TL Paine, M Hoffman, R Pascanu
arXiv preprint arXiv:1910.09890, 2019
2019
Kaleidoscope: An Efficient, Learnable Representation For All Structured Linear Maps
T Dao, N Sohoni, A Gu, M Eichhorn, A Blonder, M Leszczynski, A Rudra, ...
International Conference on Learning Representations, 2019
2019
Sprague-Grundy Values of the -Wythoff Game
A Gu
The Electronic Journal of Combinatorics 22 (2), P2. 13, 2015
2015
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Articles 1–16