Anastasios Kyrillidis

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	总计	2020 年至今
引用	3054	1974
h 指数	28	22
i10 指数	60	44

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Volkan CevherAssociate Professor, LIONS, EPFL. Amazon Scholar (AGI Foundations).在 epfl.ch 的电子邮件经过验证
Sujay SanghaviAssociate Professor, Electrical and Computer Engineering, University of Texas, Austin在 mail.utexas.edu 的电子邮件经过验证
Cameron WolfePhD Student, Rice University在 rice.edu 的电子邮件经过验证
Chen DunPh.D, Rice University在 rice.edu 的电子邮件经过验证
Constantine CaramanisProfessor of Electrical and Computer Engineering, UT Austin在 utexas.edu 的电子邮件经过验证
Fangshuo LiaoPh.D. Student, Rice University在 rice.edu 的电子邮件经过验证
Dohyung ParkThe University of Texas at Austin在 utexas.edu 的电子邮件经过验证
Quoc Tran-DinhDepartment of Statistics and Operations Research, UNC在 email.unc.edu 的电子邮件经过验证
John ChenRice University在 rice.edu 的电子邮件经过验证
Junhyung Lyle KimQuantum Computing--Global Technology Applied Research, JPMorganChase在 jpmorgan.com 的电子邮件经过验证
Srinadh BhojanapalliResearch Scientist, Google Research在 google.com 的电子邮件经过验证
Chris JermaineAssociate Professor of Computer Science, Rice University在 cs.rice.edu 的电子邮件经过验证
Amir KalevInformation Sciences Institute, University of Southern California在 isi.edu 的电子邮件经过验证
Richard BaraniukC. Sidney Burrus Professor, Electrical & Computer Engineering, Rice University在 rice.edu 的电子邮件经过验证
Stephen BeckerAssociate Professor at University of Colorado在 colorado.edu 的电子邮件经过验证
Anshumali ShrivastavaRice University, ThirdAI Corp.在 rice.edu 的电子邮件经过验证
Megasthenis AsterisUniversity of Texas at Austin在 utexas.edu 的电子邮件经过验证
Yuxin TangRice University在 rice.edu 的电子邮件经过验证
Vatsal ShahDoordash在 utexas.edu 的电子邮件经过验证
Dimitris PapailiopoulosResearcher at Microsoft Research & Assoc. Professor at University of Wisconsin在 papail.io 的电子邮件经过验证

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Anastasios Kyrillidis

Noah Harding CS Associate Professor, Ken Kennedy Institute Fellow, Dean Fellow, Rice University

在 rice.edu 的电子邮件经过验证 - 首页

Optimization Nonconvex optimization AI Agents Continual Learning Mixture of experts


标题按引用次数排序按年份排序按标题排序	引用次数引用次数	年份
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	258	2022
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	197	2016
Dropping convexity for faster semi-definite optimization S Bhojanapalli, A Kyrillidis, S Sanghavi Conference on Learning Theory, 530-582, 2016	189	2016
Multi-way compressed sensing for sparse low-rank tensors ND Sidiropoulos, A Kyrillidis IEEE Signal Processing Letters, 1-1, 2012	168	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	166*	2018
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	143	2024
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	114	2012
Composite self-concordant minimization. Q Tran-Dinh, A Kyrillidis, V Cevher J. Mach. Learn. Res. 16 (1), 371-416, 2015	106	2015
Provable deterministic leverage score sampling D Papailiopoulos, A Kyrillidis, C Boutsidis Proceedings of the 20th ACM SIGKDD international conference on Knowledge …, 2014	105	2014
Matrix recipes for hard thresholding methods A Kyrillidis, V Cevher Journal of Mathematical Imaging and Vision, 2012	90	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	82*	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	81	2022
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, 2022	59*	2022
Statistical inference using SGD T Li, L Liu, A Kyrillidis, C Caramanis Thirty-Second AAAI Conference on Artificial Intelligence, 3571-3578, 2017	59	2017
Recipes on hard thresholding methods A Kyrillidis, V Cevher 2011 4th IEEE International Workshop on Computational Advances in Multi …, 2011	56	2011
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	50	2019
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	50*	2012
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	45*	2020
IHT dies hard: Provable accelerated iterative hard thresholding R Khanna, A Kyrillidis Proceedings of the Twenty-First International Conference on Artificial …, 2017	41	2017
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	41	2016

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