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ORCIDAnastasios Kyrillidis
Tasos Kyrillidis – Αναστάσιος Κυριλλίδης
Person information
- unicode name: Αναστάσιος Κυριλλίδης
- affiliation: University of Texas at Austin, Department of Electrical and Computer Engineering, USA
- affiliation: Swiss Federal Institute of Technology in Lausanne, Switzerland
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2020 – today
- 2024
[j19]Cameron R. Wolfe
, Jingkang Yang, Fangshuo Liao, Arindam Chowdhury, Chen Dun, Artun Bayer, Santiago Segarra, Anastasios Kyrillidis:
GIST: distributed training for large-scale graph convolutional networks. J. Appl. Comput. Topol. 8(5): 1363-1415 (2024)- [j18]Cameron R. Wolfe, Anastasios Kyrillidis:
Better schedules for low precision training of deep neural networks. Mach. Learn. 113(6): 3569-3587 (2024) - [j17]Junhyung Lyle Kim, Gauthier Gidel, Anastasios Kyrillidis, Fabian Pedregosa:
When is Momentum Extragradient Optimal? A Polynomial-Based Analysis. Trans. Mach. Learn. Res. 2024 (2024) - [j16]Cameron R. Wolfe, Fangshuo Liao, Qihan Wang, Junhyung Lyle Kim, Anastasios Kyrillidis:
How Much Pre-training Is Enough to Discover a Good Subnetwork? Trans. Mach. Learn. Res. 2024 (2024) - [c56]Fangshuo Liao, Anastasios Kyrillidis:
Provable Accelerated Convergence of Nesterov's Momentum for Deep ReLU Neural Networks. ALT 2024: 732-784 - [c55]Junhyung Lyle Kim, Mohammad Taha Toghani, César A. Uribe, Anastasios Kyrillidis:
Adaptive Federated Learning with Auto-Tuned Clients. ICLR 2024 - [c54]Fangshuo Liao, Junhyung Lyle Kim, Cruz Barnum, Anastasios Kyrillidis:
On the Error-Propagation of Inexact Hotelling's Deflation for Principal Component Analysis. ICML 2024 - [c53]Carlos Quintero-Peña, Wil Thomason, Zachary K. Kingston, Anastasios Kyrillidis, Lydia E. Kavraki:
Stochastic Implicit Neural Signed Distance Functions for Safe Motion Planning under Sensing Uncertainty. ICRA 2024: 2360-2367 - [c52]John Chen, Chen Dun, Anastasios Kyrillidis:
Fast FixMatch: Faster Semi-Supervised Learning with Curriculum Batch Size. ISIT 2024: 1836-1841 - [i82]Cameron R. Wolfe, Anastasios Kyrillidis:
Better Schedules for Low Precision Training of Deep Neural Networks. CoRR abs/2403.02243 (2024) - [i81]Junhyung Lyle Kim, Nai-Hui Chia, Anastasios Kyrillidis:
A Catalyst Framework for the Quantum Linear System Problem via the Proximal Point Algorithm. CoRR abs/2406.13879 (2024) - 2023
- [j15]Junhyung Lyle Kim, Mohammad Taha Toghani, César A. Uribe, Anastasios Kyrillidis:
Local Stochastic Factored Gradient Descent for Distributed Quantum State Tomography. IEEE Control. Syst. Lett. 7: 199-204 (2023) - [c51]Qihan Wang, Chen Dun, Fangshuo Liao, Chris Jermaine, Anastasios Kyrillidis:
LOFT: Finding Lottery Tickets through Filter-wise Training. AISTATS 2023: 6498-6526 - [c50]Chen Dun, Mirian Hipolito Garcia, Chris Jermaine, Dimitrios Dimitriadis, Anastasios Kyrillidis:
Efficient and Light-Weight Federated Learning via Asynchronous Distributed Dropout. AISTATS 2023: 6630-6660 - [c49]Zheyang Xiong, Fangshuo Liao, Anastasios Kyrillidis:
Strong Lottery Ticket Hypothesis with ε-perturbation. AISTATS 2023: 6879-6902 - [c48]Erdong Hu, Yuxin Tang, Anastasios Kyrillidis, Chris Jermaine:
Federated Learning Over Images: Vertical Decompositions and Pre-Trained Backbones Are Difficult to Beat. ICCV 2023: 19328-19339 - [c47]Carlos Quintero-Peña, Zachary K. Kingston, Tianyang Pan, Rahul Shome, Anastasios Kyrillidis, Lydia E. Kavraki:
Optimal Grasps and Placements for Task and Motion Planning in Clutter. ICRA 2023: 3707-3713 - [c46]David A. Quiroga, Anastasios Kyrillidis:
Using non-convex optimization in quantum process tomography: Factored gradient descent is tough to beat. ICRC 2023: 1-10 - [c45]Zichang Liu, Aditya Desai, Fangshuo Liao, Weitao Wang, Victor Xie, Zhaozhuo Xu, Anastasios Kyrillidis, Anshumali Shrivastava:
Scissorhands: Exploiting the Persistence of Importance Hypothesis for LLM KV Cache Compression at Test Time. NeurIPS 2023 - [i80]Zichang Liu, Aditya Desai, Fangshuo Liao, Weitao Wang, Victor Xie, Zhaozhuo Xu, Anastasios Kyrillidis, Anshumali Shrivastava:
Scissorhands: Exploiting the Persistence of Importance Hypothesis for LLM KV Cache Compression at Test Time. CoRR abs/2305.17118 (2023) - [i79]Fangshuo Liao, Anastasios Kyrillidis:
Accelerated Convergence of Nesterov's Momentum for Deep Neural Networks under Partial Strong Convexity. CoRR abs/2306.08109 (2023) - [i78]Chen Dun, Mirian Hipolito Garcia, Guoqing Zheng, Ahmed Hassan Awadallah, Robert Sim, Anastasios Kyrillidis, Dimitrios Dimitriadis:
Fed-ZERO: Efficient Zero-shot Personalization with Federated Mixture of Experts. CoRR abs/2306.08586 (2023) - [i77]Junhyung Lyle Kim, Mohammad Taha Toghani, César A. Uribe, Anastasios Kyrillidis:
Adaptive Federated Learning with Auto-Tuned Clients. CoRR abs/2306.11201 (2023) - [i76]Erdong Hu, Yuxin Tang, Anastasios Kyrillidis, Chris Jermaine:
Federated Learning Over Images: Vertical Decompositions and Pre-Trained Backbones Are Difficult to Beat. CoRR abs/2309.03237 (2023) - [i75]John Chen, Chen Dun, Anastasios Kyrillidis:
Fast FixMatch: Faster Semi-Supervised Learning with Curriculum Batch Size. CoRR abs/2309.03469 (2023) - [i74]Carlos Quintero-Peña, Wil Thomason, Zachary K. Kingston, Anastasios Kyrillidis, Lydia E. Kavraki:
Stochastic Implicit Neural Signed Distance Functions for Safe Motion Planning under Sensing Uncertainty. CoRR abs/2309.16862 (2023) - [i73]Chen Dun, Mirian Hipolito Garcia, Guoqing Zheng, Ahmed Hassan Awadallah, Anastasios Kyrillidis, Robert Sim:
Sweeping Heterogeneity with Smart MoPs: Mixture of Prompts for LLM Task Adaptation. CoRR abs/2310.02842 (2023) - [i72]Chen Dun, Qiutai Pan, Shikai Jin, Ria Stevens, Mitchell D. Miller, George N. Phillips Jr., Anastasios Kyrillidis:
CrysFormer: Protein Structure Prediction via 3d Patterson Maps and Partial Structure Attention. CoRR abs/2310.03899 (2023) - [i71]Fangshuo Liao, Junhyung Lyle Kim, Cruz Barnum, Anastasios Kyrillidis:
On the Error-Propagation of Inexact Deflation for Principal Component Analysis. CoRR abs/2310.04283 (2023) - 2022
- [j14]Binhang Yuan, Cameron R. Wolfe, Chen Dun, Yuxin Tang, Anastasios Kyrillidis, Chris Jermaine:
Distributed Learning of Fully Connected Neural Networks using Independent Subnet Training. Proc. VLDB Endow. 15(8): 1581-1590 (2022) - [j13]Fangshuo Liao, Anastasios Kyrillidis:
On the Convergence of Shallow Neural Network Training with Randomly Masked Neurons. Trans. Mach. Learn. Res. 2022 (2022) - [c44]John Chen, Cameron R. Wolfe, Zhao Li, Anastasios Kyrillidis:
Demon: Improved Neural Network Training With Momentum Decay. ICASSP 2022: 3958-3962 - [c43]Ahmed Imtiaz Humayun, Randall Balestriero, Anastasios Kyrillidis, Richard G. Baraniuk:
No More Than 6ft Apart: Robust K-Means via Radius Upper Bounds. ICASSP 2022: 4433-4437 - [c42]Cheng Wan, Youjie Li, Cameron R. Wolfe, Anastasios Kyrillidis, Nam Sung Kim, Yingyan Lin:
PipeGCN: Efficient Full-Graph Training of Graph Convolutional Networks with Pipelined Feature Communication. ICLR 2022 - [c41]Cameron R. Wolfe, Anastasios Kyrillidis:
i-SpaSP: Structured Neural Pruning via Sparse Signal Recovery. L4DC 2022: 248-262 - [c40]Junhyung Lyle Kim, Panos Toulis, Anastasios Kyrillidis:
Convergence and Stability of the Stochastic Proximal Point Algorithm with Momentum. L4DC 2022: 1034-1047 - [c39]John Chen, Cameron R. Wolfe, Tasos Kyrillidis:
REX: Revisiting Budgeted Training with an Improved Schedule. MLSys 2022 - [c38]John Chen, Samarth Sinha, Anastasios Kyrillidis:
Stackmix: a complementary mix algorithm. UAI 2022: 326-335 - [c37]Chen Dun, Cameron R. Wolfe, Christopher M. Jermaine, Anastasios Kyrillidis:
ResIST: Layer-wise decomposition of ResNets for distributed training. UAI 2022: 610-620 - [i70]Ahmed Imtiaz Humayun, Randall Balestriero, Anastasios Kyrillidis, Richard G. Baraniuk:
No More Than 6ft Apart: Robust K-Means via Radius Upper Bounds. CoRR abs/2203.02502 (2022) - [i69]Cheng Wan, Youjie Li, Cameron R. Wolfe, Anastasios Kyrillidis, Nam Sung Kim, Yingyan Lin:
PipeGCN: Efficient Full-Graph Training of Graph Convolutional Networks with Pipelined Feature Communication. CoRR abs/2203.10428 (2022) - [i68]Junhyung Lyle Kim, Mohammad Taha Toghani, César A. Uribe, Anastasios Kyrillidis:
Local Stochastic Factored Gradient Descent for Distributed Quantum State Tomography. CoRR abs/2203.11579 (2022) - [i67]Anastasios Kyrillidis, Moshe Y. Vardi, Zhiwei Zhang:
DPMS: An ADD-Based Symbolic Approach for Generalized MaxSAT Solving. CoRR abs/2205.03747 (2022) - [i66]Chen Dun, Mirian Hipolito Garcia, Chris Jermaine, Dimitrios Dimitriadis, Anastasios Kyrillidis:
Efficient and Light-Weight Federated Learning via Asynchronous Distributed Dropout. CoRR abs/2210.16105 (2022) - [i65]Qihan Wang, Chen Dun, Fangshuo Liao, Chris Jermaine, Anastasios Kyrillidis:
LOFT: Finding Lottery Tickets through Filter-wise Training. CoRR abs/2210.16169 (2022) - [i64]Zheyang Xiong, Fangshuo Liao, Anastasios Kyrillidis:
Strong Lottery Ticket Hypothesis with ε-perturbation. CoRR abs/2210.16589 (2022) - [i63]Cameron R. Wolfe, Anastasios Kyrillidis:
Cold Start Streaming Learning for Deep Networks. CoRR abs/2211.04624 (2022) - [i62]Junhyung Lyle Kim, Gauthier Gidel, Anastasios Kyrillidis, Fabian Pedregosa:
Extragradient with Positive Momentum is Optimal for Games with Cross-Shaped Jacobian Spectrum. CoRR abs/2211.04659 (2022) - 2021
- [j12]Anastasios Kyrillidis, Anshumali Shrivastava, Moshe Y. Vardi, Zhiwei Zhang:
Solving hybrid Boolean constraints in continuous space via multilinear Fourier expansions. Artif. Intell. 299: 103559 (2021) - [c36]Anastasios Kyrillidis, Moshe Y. Vardi, Zhiwei Zhang:
On Continuous Local BDD-Based Search for Hybrid SAT Solving. AAAI 2021: 3841-3850 - [c35]Jacky Zhang, Rajiv Khanna, Anastasios Kyrillidis, Sanmi Koyejo:
Bayesian Coresets: Revisiting the Nonconvex Optimization Perspective. AISTATS 2021: 2782-2790 - [c34]John Chen, Qihan Wang, Anastasios Kyrillidis:
Mitigating Deep Double Descent by Concatenating Inputs. CIKM 2021: 2930-2934 - [c33]Carlos Quintero-Peña, Anastasios Kyrillidis, Lydia E. Kavraki:
Robust Optimization-based Motion Planning for high-DOF Robots under Sensing Uncertainty. ICRA 2021: 9724-9730 - [i61]Cameron R. Wolfe, Jingkang Yang, Arindam Chowdhury, Chen Dun, Artun Bayer, Santiago Segarra, Anastasios Kyrillidis:
GIST: Distributed Training for Large-Scale Graph Convolutional Networks. CoRR abs/2102.10424 (2021) - [i60]Junhyung Lyle Kim, George Kollias, Amir Kalev, Ken X. Wei, Anastasios Kyrillidis:
Fast quantum state reconstruction via accelerated non-convex programming. CoRR abs/2104.07006 (2021) - [i59]Junhyung Lyle Kim, Jose Antonio Lara Benitez, Mohammad Taha Toghani, Cameron R. Wolfe, Zhiwei Zhang, Anastasios Kyrillidis:
Momentum-inspired Low-Rank Coordinate Descent for Diagonally Constrained SDPs. CoRR abs/2106.08775 (2021) - [i58]John Chen, Qihan Wang, Anastasios Kyrillidis:
Mitigating deep double descent by concatenating inputs. CoRR abs/2107.00797 (2021) - [i57]Chen Dun, Cameron R. Wolfe, Christopher M. Jermaine, Anastasios Kyrillidis:
ResIST: Layer-Wise Decomposition of ResNets for Distributed Training. CoRR abs/2107.00961 (2021) - [i56]John Chen, Cameron R. Wolfe, Anastasios Kyrillidis:
REX: Revisiting Budgeted Training with an Improved Schedule. CoRR abs/2107.04197 (2021) - [i55]Cameron R. Wolfe, Qihan Wang, Junhyung Lyle Kim, Anastasios Kyrillidis:
Provably Efficient Lottery Ticket Discovery. CoRR abs/2108.00259 (2021) - [i54]Zhenwei Dai, Chen Dun, Yuxin Tang, Anastasios Kyrillidis, Anshumali Shrivastava:
Federated Multiple Label Hashing (FedMLH): Communication Efficient Federated Learning on Extreme Classification Tasks. CoRR abs/2110.12292 (2021) - [i53]Junhyung Lyle Kim, Panos Toulis, Anastasios Kyrillidis:
Convergence and Stability of the Stochastic Proximal Point Algorithm with Momentum. CoRR abs/2111.06171 (2021) - [i52]Fangshuo Liao, Anastasios Kyrillidis:
On the Convergence of Shallow Neural Network Training with Randomly Masked Neurons. CoRR abs/2112.02668 (2021) - [i51]Cameron R. Wolfe, Anastasios Kyrillidis:
i-SpaSP: Structured Neural Pruning via Sparse Signal Recovery. CoRR abs/2112.04905 (2021) - 2020
- [c32]Anastasios Kyrillidis, Anshumali Shrivastava, Moshe Y. Vardi, Zhiwei Zhang:
FourierSAT: A Fourier Expansion-Based Algebraic Framework for Solving Hybrid Boolean Constraints. AAAI 2020: 1552-1560 - [c31]Kelly Geyer, Anastasios Kyrillidis, Amir Kalev:
Low-rank regularization and solution uniqueness in over-parameterized matrix sensing. AISTATS 2020: 930-940 - [c30]John Chen, Vatsal Shah, Anastasios Kyrillidis:
Negative Sampling in Semi-Supervised learning. ICML 2020: 1704-1714 - [i50]Jacky Y. Zhang, Rajiv Khanna, Anastasios Kyrillidis, Oluwasanmi Koyejo:
Bayesian Coresets: An Optimization Perspective. CoRR abs/2007.00715 (2020) - [i49]John Chen, Samarth Sinha, Anastasios Kyrillidis:
ImCLR: Implicit Contrastive Learning for Image Classification. CoRR abs/2011.12618 (2020) - [i48]Vatsal Shah, Soumya Basu, Anastasios Kyrillidis, Sujay Sanghavi:
On Generalization of Adaptive Methods for Over-parameterized Linear Regression. CoRR abs/2011.14066 (2020) - [i47]Anastasios Kyrillidis, Moshe Y. Vardi, Zhiwei Zhang:
On Continuous Local BDD-Based Search for Hybrid SAT Solving. CoRR abs/2012.07983 (2020) - [i46]T. Mitchell Roddenberry, Santiago Segarra, Anastasios Kyrillidis:
Rank-One Measurements of Low-Rank PSD Matrices Have Small Feasible Sets. CoRR abs/2012.09768 (2020)
2010 – 2019
- 2019
- [c29]Ryan Spring, Anastasios Kyrillidis, Vijai Mohan, Anshumali Shrivastava:
Compressing Gradient Optimizers via Count-Sketches. ICML 2019: 5946-5955 - [c28]Jacky Y. Zhang, Rajiv Khanna, Anastasios Kyrillidis, Oluwasanmi Koyejo:
Learning Sparse Distributions using Iterative Hard Thresholding. NeurIPS 2019: 6757-6766 - [i45]Ryan Spring, Anastasios Kyrillidis, Vijai Mohan, Anshumali Shrivastava:
Compressing Gradient Optimizers via Count-Sketches. CoRR abs/1902.00179 (2019) - [i44]Alexander Ratner, Dan Alistarh, Gustavo Alonso, David G. Andersen, Peter Bailis, Sarah Bird, Nicholas Carlini, Bryan Catanzaro, Eric S. Chung, Bill Dally, Jeff Dean, Inderjit S. Dhillon, Alexandros G. Dimakis, Pradeep Dubey, Charles Elkan, Grigori Fursin, Gregory R. Ganger, Lise Getoor, Phillip B. Gibbons, Garth A. Gibson, Joseph E. Gonzalez, Justin Gottschlich, Song Han, Kim M. Hazelwood, Furong Huang, Martin Jaggi, Kevin G. Jamieson, Michael I. Jordan, Gauri Joshi, Rania Khalaf, Jason Knight, Jakub Konecný, Tim Kraska, Arun Kumar, Anastasios Kyrillidis, Jing Li, Samuel Madden, H. Brendan McMahan, Erik Meijer, Ioannis Mitliagkas, Rajat Monga, Derek Gordon Murray, Dimitris S. Papailiopoulos, Gennady Pekhimenko, Theodoros Rekatsinas, Afshin Rostamizadeh, Christopher Ré, Christopher De Sa, Hanie Sedghi, Siddhartha Sen, Virginia Smith, Alex Smola, Dawn Song, Evan Randall Sparks, Ion Stoica, Vivienne Sze, Madeleine Udell, Joaquin Vanschoren, Shivaram Venkataraman, Rashmi Vinayak, Markus Weimer, Andrew Gordon Wilson, Eric P. Xing, Matei Zaharia, Ce Zhang, Ameet Talwalkar:
SysML: The New Frontier of Machine Learning Systems. CoRR abs/1904.03257 (2019) - [i43]Binhang Yuan, Anastasios Kyrillidis, Christopher M. Jermaine:
Distributed Learning of Deep Neural Networks using Independent Subnet Training. CoRR abs/1910.02120 (2019) - [i42]John Chen, Anastasios Kyrillidis:
Decaying momentum helps neural network training. CoRR abs/1910.04952 (2019) - [i41]Jacky Y. Zhang, Rajiv Khanna, Anastasios Kyrillidis, Oluwasanmi Koyejo:
Learning Sparse Distributions using Iterative Hard Thresholding. CoRR abs/1910.13389 (2019) - [i40]John Chen, Vatsal Shah, Anastasios Kyrillidis:
Negative sampling in semi-supervised learning. CoRR abs/1911.05166 (2019) - [i39]Michael P. Perrone, Haidar Khan, Changhoan Kim, Anastasios Kyrillidis, Jerry Quinn, Valentina Salapura:
Optimal Mini-Batch Size Selection for Fast Gradient Descent. CoRR abs/1911.06459 (2019) - [i38]Anastasios Kyrillidis, Anshumali Shrivastava, Moshe Y. Vardi, Zhiwei Zhang:
FourierSAT: A Fourier Expansion-Based Algebraic Framework for Solving Hybrid Boolean Constraints. CoRR abs/1912.01032 (2019) - 2018
- [j11]Quoc Tran-Dinh, Anastasios Kyrillidis, Volkan Cevher:
A Single-Phase, Proximal Path-Following Framework. Math. Oper. Res. 43(4): 1326-1347 (2018) - [j10]Dohyung Park, Anastasios Kyrillidis, Constantine Caramanis, Sujay Sanghavi:
Finding Low-Rank Solutions via Nonconvex Matrix Factorization, Efficiently and Provably. SIAM J. Imaging Sci. 11(4): 2165-2204 (2018) - [j9]Ya-Ping Hsieh, Yu-Chun Kao, Rabeeh Karimi Mahabadi, Alp Yurtsever, Anastasios Kyrillidis, Volkan Cevher:
A Non-Euclidean Gradient Descent Framework for Non-Convex Matrix Factorization. IEEE Trans. Signal Process. 66(22): 5917-5926 (2018) - [c27]Tianyang Li, Liu Liu, Anastasios Kyrillidis, Constantine Caramanis:
Statistical Inference Using SGD. AAAI 2018: 3571-3578 - [c26]Rajiv Khanna, Anastasios Kyrillidis:
IHT dies hard: Provable accelerated Iterative Hard Thresholding. AISTATS 2018: 188-198 - [c25]Anastasios Kyrillidis:
Simple and practical algorithms for 𝓁p-norm low-rank approximation. UAI 2018: 414-424 - [i37]Tianyang Li, Anastasios Kyrillidis, Liu Liu, Constantine Caramanis:
Approximate Newton-based statistical inference using only stochastic gradients. CoRR abs/1805.08920 (2018) - [i36]Anastasios Kyrillidis:
Simple and practical algorithms for 𝓁p-norm low-rank approximation. CoRR abs/1805.09464 (2018) - [i35]Anastasios Kyrillidis, Shashanka Ubaru, Georgios Kollias, Kristofer E. Bouchard:
Run Procrustes, Run! On the convergence of accelerated Procrustes Flow. CoRR abs/1806.00534 (2018) - [i34]Anastasios Kyrillidis, Amir Kalev:
Implicit regularization and solution uniqueness in over-parameterized matrix sensing. CoRR abs/1806.02046 (2018) - 2017
- [c24]Dohyung Park, Anastasios Kyrillidis, Constantine Caramanis, Sujay Sanghavi:
Non-square matrix sensing without spurious local minima via the Burer-Monteiro approach. AISTATS 2017: 65-74 - [i33]Tianyang Li, Liu Liu, Anastasios Kyrillidis, Constantine Caramanis:
Statistical inference using SGD. CoRR abs/1705.07477 (2017) - [i32]Anastasios Kyrillidis, Amir Kalev, Dohyung Park, Srinadh Bhojanapalli, Constantine Caramanis, Sujay Sanghavi:
Provable quantum state tomography via non-convex methods. CoRR abs/1711.02524 (2017) - [i31]Rajiv Khanna, Anastasios Kyrillidis:
IHT dies hard: Provable accelerated Iterative Hard Thresholding. CoRR abs/1712.09379 (2017) - 2016
- [j8]Luca Baldassarre, Nirav Bhan, Volkan Cevher, Anastasios Kyrillidis, Siddhartha Satpathi:
Group-Sparse Model Selection: Hardness and Relaxations. IEEE Trans. Inf. Theory 62(11): 6508-6534 (2016) - [j7]Georgios Skoumas, Dieter Pfoser, Anastasios Kyrillidis, Timos Sellis:
Location Estimation Using Crowdsourced Spatial Relations. ACM Trans. Spatial Algorithms Syst. 2(2): 5:1-5:23 (2016) - [c23]Anastasios Kyrillidis, Bubacarr Bah, Rouzbeh Hasheminezhad, Quoc Tran-Dinh, Luca Baldassarre, Volkan Cevher:
Convex Block-sparse Linear Regression with Expanders - Provably. AISTATS 2016: 19-27 - [c22]Hemant Tyagi, Anastasios Kyrillidis, Bernd Gärtner, Andreas Krause:
Learning Sparse Additive Models with Interactions in High Dimensions. AISTATS 2016: 111-120 - [c21]Megasthenis Asteris, Anastasios Kyrillidis, Dimitris S. Papailiopoulos, Alexandros G. Dimakis:
Bipartite Correlation Clustering: Maximizing Agreements. AISTATS 2016: 121-129 - [c20]Dohyung Park, Anastasios Kyrillidis, Constantine Caramanis, Sujay Sanghavi:
Finding low-rank solutions to smooth convex problems via the Burer-Monteiro approach. Allerton 2016: 439-446 - [c19]Srinadh Bhojanapalli, Anastasios Kyrillidis, Sujay Sanghavi:
Dropping Convexity for Faster Semi-definite Optimization. COLT 2016: 530-582 - [c18]Megasthenis Asteris, Anastasios Kyrillidis, Oluwasanmi Koyejo, Russell A. Poldrack:
A Simple and Provable Algorithm for Sparse Diagonal CCA. ICML 2016: 1148-1157 - [i30]Quoc Tran-Dinh, Anastasios Kyrillidis, Volkan Cevher:
A single-phase, proximal path-following framework. CoRR abs/1603.01681 (2016) - [i29]Megasthenis Asteris, Anastasios Kyrillidis, Dimitris S. Papailiopoulos, Alexandros G. Dimakis:
Bipartite Correlation Clustering - Maximizing Agreements. CoRR abs/1603.02782 (2016) - [i28]Anastasios Kyrillidis, Bubacarr Bah, Rouzbeh Hasheminezhad, Quoc Tran-Dinh, Luca Baldassarre, Volkan Cevher:
Convex block-sparse linear regression with expanders - provably. CoRR abs/1603.06313 (2016) - [i27]Vatsal Shah, Megasthenis Asteris, Anastasios Kyrillidis, Sujay Sanghavi:
Trading-off variance and complexity in stochastic gradient descent. CoRR abs/1603.06861 (2016) - [i26]Hemant Tyagi, Anastasios Kyrillidis, Bernd Gärtner, Andreas Krause:
Learning Sparse Additive Models with Interactions in High Dimensions. CoRR abs/1604.05307 (2016) - [i25]Hemant Tyagi, Anastasios Kyrillidis, Bernd Gärtner, Andreas Krause:
Algorithms for Learning Sparse Additive Models with Interactions in High Dimensions. CoRR abs/1605.00609 (2016) - [i24]Megasthenis Asteris, Anastasios Kyrillidis, Oluwasanmi Koyejo, Russell A. Poldrack:
A simple and provable algorithm for sparse diagonal CCA. CoRR abs/1605.08961 (2016) - [i23]Dohyung Park, Anastasios Kyrillidis, Srinadh Bhojanapalli, Constantine Caramanis, Sujay Sanghavi:
Provable non-convex projected gradient descent for a class of constrained matrix optimization problems. CoRR abs/1606.01316 (2016) - [i22]Dohyung Park, Anastasios Kyrillidis, Constantine Caramanis, Sujay Sanghavi:
Finding Low-rank Solutions to Matrix Problems, Efficiently and Provably. CoRR abs/1606.03168 (2016) - [i21]Dohyung Park, Anastasios Kyrillidis, Constantine Caramanis, Sujay Sanghavi:
Non-square matrix sensing without spurious local minima via the Burer-Monteiro approach. CoRR abs/1609.03240 (2016) - 2015
- [j6]Quoc Tran-Dinh, Anastasios Kyrillidis, Volkan Cevher:
Composite self-concordant minimization. J. Mach. Learn. Res. 16: 371-416 (2015) - [j5]Michail Vlachos, Nikolaos M. Freris, Anastasios Kyrillidis:
Compressive mining: fast and optimal data mining in the compressed domain. VLDB J. 24(1): 1-24 (2015) - [c17]Megasthenis Asteris, Anastasios Kyrillidis, Alexandros G. Dimakis, Han-Gyol Yi, Bharath Chandrasekaran:
Stay on path: PCA along graph paths. ICML 2015: 1728-1736 - [c16]Megasthenis Asteris, Dimitris S. Papailiopoulos, Anastasios Kyrillidis, Alexandros G. Dimakis:
Sparse PCA via Bipartite Matchings. NIPS 2015: 766-774 - [i20]