Dropping convexity for faster semi-definite optimization S Bhojanapalli, A Kyrillidis, S Sanghavi Conference on Learning Theory, 530-582, 2016 | 185 | 2016 |
Non-square matrix sensing without spurious local minima via the Burer-Monteiro approach D Park, A Kyrillidis, C Caramanis, S Sanghavi Artificial Intelligence and Statistics, pp. 65-74, 2016 | 184 | 2016 |
Current progress and open challenges for applying deep learning across the biosciences N Sapoval, A Aghazadeh, MG Nute, DA Antunes, A Balaji, R Baraniuk, ... Nature Communications 13 (1), 1728, 2022 | 170 | 2022 |
Multi-way compressed sensing for sparse low-rank tensors ND Sidiropoulos, A Kyrillidis IEEE Signal Processing Letters, 1-1, 2012 | 162 | 2012 |
Finding low-rank solutions via non-convex matrix factorization, efficiently and provably D Park, A Kyrillidis, C Caramanis, S Sanghavi SIAM Journal on Imaging Sciences 11 (4), 2165–2204, 2018 | 156* | 2018 |
Sparse projections onto the simplex A Kyrillidis, S Becker, V Cevher, C Koch Proceedings of The 30th International Conference on Machine Learning 28, 235–243, 2012 | 110 | 2012 |
Composite self-concordant minimization. Q Tran-Dinh, A Kyrillidis, V Cevher J. Mach. Learn. Res. 16 (1), 371-416, 2015 | 102 | 2015 |
Provable deterministic leverage score sampling D Papailiopoulos, A Kyrillidis, C Boutsidis Proceedings of the 20th ACM SIGKDD international conference on Knowledge …, 2014 | 97 | 2014 |
Matrix recipes for hard thresholding methods A Kyrillidis, V Cevher Journal of Mathematical Imaging and Vision, 2012 | 85 | 2012 |
Provable compressed sensing quantum state tomography via non-convex methods A Kyrillidis, A Kalev, D Park, S Bhojanapalli, C Caramanis, S Sanghavi npj Quantum Information 4 (1), 36, 2018 | 74* | 2018 |
PipeGCN: Efficient full-graph training of graph convolutional networks with pipelined feature communication C Wan, Y Li, CR Wolfe, A Kyrillidis, NS Kim, Y Lin arXiv preprint arXiv:2203.10428, 2022 | 57 | 2022 |
Recipes on hard thresholding methods A Kyrillidis, V Cevher 2011 4th IEEE International Workshop on Computational Advances in Multi …, 2011 | 54 | 2011 |
Statistical inference using SGD T Li, L Liu, A Kyrillidis, C Caramanis Thirty-Second AAAI Conference on Artificial Intelligence, 3571-3578, 2017 | 52 | 2017 |
Combinatorial selection and least absolute shrinkage via the CLASH algorithm A Kyrillidis, V Cevher 2012 IEEE International Symposium on Information Theory Proceedings, 2216-2220, 2012 | 49* | 2012 |
Distributed learning of fully connected neural networks using independent subnet training B Yuan, CR Wolfe, C Dun, Y Tang, A Kyrillidis, C Jermaine Proceedings of the VLDB Endowment 15 (8), 2022 | 47* | 2022 |
Mlsys: The new frontier of machine learning systems A Ratner, D Alistarh, G Alonso, DG Andersen, P Bailis, S Bird, N Carlini, ... arXiv preprint arXiv:1904.03257, 2019 | 46 | 2019 |
Scissorhands: Exploiting the persistence of importance hypothesis for llm kv cache compression at test time Z Liu, A Desai, F Liao, W Wang, V Xie, Z Xu, A Kyrillidis, A Shrivastava Advances in Neural Information Processing Systems 36, 2024 | 42 | 2024 |
Group-sparse model selection: Hardness and relaxations L Baldassarre, N Bhan, V Cevher, A Kyrillidis, S Satpathi IEEE Transactions on Information Theory 62 (11), 6508-6534, 2016 | 38 | 2016 |
Demon: Momentum Decay for Improved Neural Network Training J Chen, C Wolfe, Z Li, A Kyrillidis ICASSP 2022 - 2022 IEEE International Conference on Acoustics, Speech and …, 2020 | 37* | 2020 |
IHT dies hard: Provable accelerated iterative hard thresholding R Khanna, A Kyrillidis Proceedings of the Twenty-First International Conference on Artificial …, 2017 | 37 | 2017 |