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Surbhi Goel
Surbhi Goel
Assistant Professor, University of Pennsylvania
Verified email at cis.upenn.edu - Homepage
Title
Cited by
Cited by
Year
Reliably learning the relu in polynomial time
S Goel, V Kanade, A Klivans, J Thaler
Conference on Learning Theory (COLT) 2017, 2016
1382016
Learning neural networks with two nonlinear layers in polynomial time
S Goel, A Klivans
Conference on Learning Theory (COLT) 2019, 2017
100*2017
Understanding contrastive learning requires incorporating inductive biases
N Saunshi, J Ash, S Goel, D Misra, C Zhang, S Arora, S Kakade, ...
International Conference on Machine Learning, 19250-19286, 2022
942022
Transformers learn shortcuts to automata
B Liu, JT Ash, S Goel, A Krishnamurthy, C Zhang
arXiv preprint arXiv:2210.10749, 2022
862022
Learning one convolutional layer with overlapping patches
S Goel, A Klivans, R Meka
International Conference on Machine Learning (ICML) 2018, 2018
842018
Hidden progress in deep learning: Sgd learns parities near the computational limit
B Barak, B Edelman, S Goel, S Kakade, E Malach, C Zhang
Advances in Neural Information Processing Systems 35, 21750-21764, 2022
832022
Inductive biases and variable creation in self-attention mechanisms
BL Edelman, S Goel, S Kakade, C Zhang
International Conference on Machine Learning, 5793-5831, 2022
822022
Superpolynomial lower bounds for learning one-layer neural networks using gradient descent
S Goel, A Gollakota, Z Jin, S Karmalkar, A Klivans
International Conference on Machine Learning, 3587-3596, 2020
682020
Time/accuracy tradeoffs for learning a relu with respect to gaussian marginals
S Goel, S Karmalkar, A Klivans
Advances in neural information processing systems 32, 2019
562019
Statistical-query lower bounds via functional gradients
S Goel, A Gollakota, A Klivans
Advances in Neural Information Processing Systems 33, 2147-2158, 2020
552020
Gone fishing: Neural active learning with fisher embeddings
J Ash, S Goel, A Krishnamurthy, S Kakade
Advances in Neural Information Processing Systems 34, 8927-8939, 2021
522021
Approximation schemes for relu regression
I Diakonikolas, S Goel, S Karmalkar, AR Klivans, M Soltanolkotabi
Conference on learning theory, 1452-1485, 2020
522020
Investigating the role of negatives in contrastive representation learning
JT Ash, S Goel, A Krishnamurthy, D Misra
arXiv preprint arXiv:2106.09943, 2021
442021
Tight hardness results for training depth-2 ReLU networks
S Goel, A Klivans, P Manurangsi, D Reichman
arXiv preprint arXiv:2011.13550, 2020
332020
Efficiently learning adversarially robust halfspaces with noise
O Montasser, S Goel, I Diakonikolas, N Srebro
International Conference on Machine Learning, 7010-7021, 2020
332020
Quantifying perceptual distortion of adversarial examples
M Jordan, N Manoj, S Goel, AG Dimakis
arXiv preprint arXiv:1902.08265, 2019
302019
Eigenvalue decay implies polynomial-time learnability for neural networks
S Goel, A Klivans
Advances in Neural Information Processing Systems 30, 2017
282017
Acceleration via fractal learning rate schedules
N Agarwal, S Goel, C Zhang
International Conference on Machine Learning, 87-99, 2021
202021
Improved learning of one-hidden-layer convolutional neural networks with overlaps
SS Du, S Goel
arXiv preprint arXiv:1805.07798, 2018
202018
Learning ising and potts models with latent variables
S Goel
International Conference on Artificial Intelligence and Statistics, 3557-3566, 2020
19*2020
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