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Burak Bartan
Burak Bartan
Researcher, Qualcomm AI Research
Bestätigte E-Mail-Adresse bei stanford.edu - Startseite
Titel
Zitiert von
Zitiert von
Jahr
Repairing multiple failures for scalar MDS codes
J Mardia, B Bartan, M Wootters
IEEE Transactions on Information Theory 65 (5), 2661-2672, 2018
402018
Discrete linear canonical transform based on hyperdifferential operators
A Koç, B Bartan, HM Ozaktas
IEEE Transactions on Signal Processing 67 (9), 2237-2248, 2019
292019
Debiasing distributed second order optimization with surrogate sketching and scaled regularization
M Derezinski, B Bartan, M Pilanci, MW Mahoney
Advances in Neural Information Processing Systems 33, 2020
282020
Straggler Resilient Serverless Computing Based on Polar Codes
B Bartan, M Pilanci
2019 57th Annual Allerton Conference on Communication, Control, and …, 2019
28*2019
Sparse representation of two-and three-dimensional images with fractional Fourier, Hartley, linear canonical, and Haar wavelet transforms
A Koç, B Bartan, E Gundogdu, T Çukur, HM Ozaktas
Expert Systems with Applications 77, 247-255, 2017
262017
Hidden Convexity of Wasserstein GANs: Interpretable Generative Models with Closed-Form Solutions
A Sahiner, T Ergen, B Ozturkler, B Bartan, J Pauly, M Mardani, M Pilanci
International Conference on Learning Representations (ICLR) 10, 2022
202022
Neural Spectrahedra and Semidefinite Lifts: Global Convex Optimization of Polynomial Activation Neural Networks in Fully Polynomial-Time
B Bartan, M Pilanci
arXiv preprint arXiv:2101.02429, 2021
202021
Repairing multiple failures for scalar MDS codes
B Bartan, M Wootters
2017 55th Annual Allerton Conference on Communication, Control, and …, 2017
182017
Distributed Sketching for Randomized Optimization: Exact Characterization, Concentration and Lower Bounds
B Bartan, M Pilanci
IEEE Transactions on Information Theory, 2023, 2023
16*2023
Convex Neural Autoregressive Models: Towards Tractable, Expressive, and Theoretically-Backed Models for Sequential Forecasting and Generation
V Gupta, B Bartan, T Ergen, M Pilanci
ICASSP 2021-2021 IEEE International Conference on Acoustics, Speech and …, 2021
15*2021
Training Quantized Neural Networks to Global Optimality via Semidefinite Programming
B Bartan, M Pilanci
Proceedings of the 38th International Conference on Machine Learning, 2021
112021
Adaptive hashing for model counting
J Kuck, T Dao, S Zhao, B Bartan, A Sabharwal, S Ermon
Uncertainty in Artificial Intelligence, 271-280, 2020
112020
Convex Relaxations of Convolutional Neural Nets
B Bartan, M Pilanci
ICASSP 2019-2019 IEEE International Conference on Acoustics, Speech and …, 2019
52019
Discrete scaling based on operator theory
A Koç, B Bartan, HM Ozaktas
Digital Signal Processing, 102904, 2020
32020
Neural DAG Scheduling via One-Shot Priority Sampling
W Jeon, M Gagrani, B Bartan, WW Zeng, H Teague, P Zappi, C Lott
International Conference on Learning Representations (ICLR) 11, 2023
22023
Neural Fisher Discriminant Analysis: Optimal Neural Network Embeddings in Polynomial Time
B Bartan, M Pilanci
International Conference on Machine Learning, 1647-1663, 2022
22022
Digital computation of fractional Fourier and linear canonical transforms and sparse image representation
A Koc, HM Ozaktas, B Bartan, E Gundogdu, T Cukur
2017 Asia-Pacific Signal and Information Processing Association Annual …, 2017
22017
Randomized Polar Codes for Anytime Distributed Machine Learning
B Bartan, M Pilanci
IEEE Journal on Selected Areas in Information Theory, 2023
12023
Convex Optimization of Deep Polynomial and ReLU Activation Neural Networks
B Bartan, M Pilanci
ICASSP 2023-2023 IEEE International Conference on Acoustics, Speech and …, 2023
12023
Moccasin: Efficient Tensor Rematerialization for Neural Networks
B Bartan, H Li, H Teague, C Lott, B Dilkina
International Conference on Machine Learning (ICML) 2023, 2023
12023
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