Anastasios Kyrillidis

Publication Activity (10 Years)

Years Active: 2011-2024
Publications (10 Years): 110

Top Venues

CoRR

AISTATS

AAAI

ICML

Publications

Junhyung Lyle Kim, Mohammad Taha Toghani, César A. Uribe, Anastasios Kyrillidis
Adaptive Federated Learning with Auto-Tuned Clients. ICLR (2024)
Junhyung Lyle Kim, Nai-Hui Chia, Anastasios Kyrillidis
A Catalyst Framework for the Quantum Linear System Problem via the Proximal Point Algorithm. CoRR (2024)
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)
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)
Junhyung Lyle Kim, Gauthier Gidel, Anastasios Kyrillidis, Fabian Pedregosa
When is Momentum Extragradient Optimal? A Polynomial-Based Analysis. Trans. Mach. Learn. Res. 2024 (2024)
Cameron R. Wolfe, Anastasios Kyrillidis
Better Schedules for Low Precision Training of Deep Neural Networks. CoRR (2024)
Fangshuo Liao, Anastasios Kyrillidis
Provable Accelerated Convergence of Nesterov's Momentum for Deep ReLU Neural Networks. ALT (2024)
Cameron R. Wolfe, Anastasios Kyrillidis
Better schedules for low precision training of deep neural networks. Mach. Learn. 113 (6) (2024)
Fangshuo Liao, Anastasios Kyrillidis
Accelerated Convergence of Nesterov's Momentum for Deep Neural Networks under Partial Strong Convexity. CoRR (2023)
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 (2023)
Erdong Hu, Yuxin Tang, Anastasios Kyrillidis, Chris Jermaine
Federated Learning Over Images: Vertical Decompositions and Pre-Trained Backbones Are Difficult to Beat. CoRR (2023)
Junhyung Lyle Kim, Mohammad Taha Toghani, César A. Uribe, Anastasios Kyrillidis
Adaptive Federated Learning with Auto-Tuned Clients. CoRR (2023)
Qihan Wang, Chen Dun, Fangshuo Liao, Chris Jermaine, Anastasios Kyrillidis
LOFT: Finding Lottery Tickets through Filter-wise Training. AISTATS (2023)
Erdong Hu, Yuxin Tang, Anastasios Kyrillidis, Chris Jermaine
Federated Learning Over Images: Vertical Decompositions and Pre-Trained Backbones Are Difficult to Beat. ICCV (2023)
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 (2023)
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 (2023)
John Chen, Chen Dun, Anastasios Kyrillidis
Fast FixMatch: Faster Semi-Supervised Learning with Curriculum Batch Size. CoRR (2023)
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 (2023)
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 (2023)
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 (2023)
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)
Zheyang Xiong, Fangshuo Liao, Anastasios Kyrillidis
Strong Lottery Ticket Hypothesis with ε-perturbation. AISTATS (2023)
Chen Dun, Mirian Hipolito Garcia, Chris Jermaine, Dimitrios Dimitriadis, Anastasios Kyrillidis
Efficient and Light-Weight Federated Learning via Asynchronous Distributed Dropout. AISTATS (2023)
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)
Fangshuo Liao, Junhyung Lyle Kim, Cruz Barnum, Anastasios Kyrillidis
On the Error-Propagation of Inexact Deflation for Principal Component Analysis. CoRR (2023)
David A. Quiroga, Anastasios Kyrillidis
Using non-convex optimization in quantum process tomography: Factored gradient descent is tough to beat. ICRC (2023)
Fangshuo Liao, Anastasios Kyrillidis
On the Convergence of Shallow Neural Network Training with Randomly Masked Neurons. Trans. Mach. Learn. Res. 2022 (2022)
Ahmed Imtiaz Humayun, Randall Balestriero, Anastasios Kyrillidis, Richard G. Baraniuk
No More Than 6ft Apart: Robust K-Means via Radius Upper Bounds. ICASSP (2022)
Anastasios Kyrillidis, Moshe Y. Vardi, Zhiwei Zhang
DPMS: An ADD-Based Symbolic Approach for Generalized MaxSAT Solving. CoRR (2022)
John Chen, Samarth Sinha, Anastasios Kyrillidis
Stackmix: a complementary mix algorithm. UAI (2022)
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 (2022)
Chen Dun, Mirian Hipolito Garcia, Chris Jermaine, Dimitrios Dimitriadis, Anastasios Kyrillidis
Efficient and Light-Weight Federated Learning via Asynchronous Distributed Dropout. CoRR (2022)
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) (2022)
Ahmed Imtiaz Humayun, Randall Balestriero, Anastasios Kyrillidis, Richard G. Baraniuk
No More Than 6ft Apart: Robust K-Means via Radius Upper Bounds. CoRR (2022)
Zheyang Xiong, Fangshuo Liao, Anastasios Kyrillidis
Strong Lottery Ticket Hypothesis with ε-perturbation. CoRR (2022)
Qihan Wang, Chen Dun, Fangshuo Liao, Chris Jermaine, Anastasios Kyrillidis
LOFT: Finding Lottery Tickets through Filter-wise Training. CoRR (2022)
Chen Dun, Cameron R. Wolfe, Christopher M. Jermaine, Anastasios Kyrillidis
ResIST: Layer-wise decomposition of ResNets for distributed training. UAI (2022)
Junhyung Lyle Kim, Gauthier Gidel, Anastasios Kyrillidis, Fabian Pedregosa
Extragradient with Positive Momentum is Optimal for Games with Cross-Shaped Jacobian Spectrum. CoRR (2022)
Cameron R. Wolfe, Anastasios Kyrillidis
i-SpaSP: Structured Neural Pruning via Sparse Signal Recovery. L4DC (2022)
Junhyung Lyle Kim, Panos Toulis, Anastasios Kyrillidis
Convergence and Stability of the Stochastic Proximal Point Algorithm with Momentum. L4DC (2022)
Cameron R. Wolfe, Anastasios Kyrillidis
Cold Start Streaming Learning for Deep Networks. CoRR (2022)
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)
Junhyung Lyle Kim, Mohammad Taha Toghani, César A. Uribe, Anastasios Kyrillidis
Local Stochastic Factored Gradient Descent for Distributed Quantum State Tomography. CoRR (2022)
John Chen, Cameron R. Wolfe, Zhao Li, Anastasios Kyrillidis
Demon: Improved Neural Network Training With Momentum Decay. ICASSP (2022)
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 (2021)
Cameron R. Wolfe, Qihan Wang, Junhyung Lyle Kim, Anastasios Kyrillidis
Provably Efficient Lottery Ticket Discovery. CoRR (2021)
Jacky Zhang, Rajiv Khanna, Anastasios Kyrillidis, Sanmi Koyejo
Bayesian Coresets: Revisiting the Nonconvex Optimization Perspective. AISTATS (2021)
John Chen, Qihan Wang, Anastasios Kyrillidis
Mitigating deep double descent by concatenating inputs. CoRR (2021)
Anastasios Kyrillidis, Anshumali Shrivastava, Moshe Y. Vardi, Zhiwei Zhang
Solving hybrid Boolean constraints in continuous space via multilinear Fourier expansions. Artif. Intell. 299 (2021)
Carlos Quintero-Peña, Anastasios Kyrillidis, Lydia E. Kavraki
Robust Optimization-based Motion Planning for high-DOF Robots under Sensing Uncertainty. ICRA (2021)
Zhenwei Dai, Chen Dun, Yuxin Tang, Anastasios Kyrillidis, Anshumali Shrivastava
Federated Multiple Label Hashing (FedMLH): Communication Efficient Federated Learning on Extreme Classification Tasks. CoRR (2021)
John Chen, Cameron R. Wolfe, Anastasios Kyrillidis
REX: Revisiting Budgeted Training with an Improved Schedule. CoRR (2021)
Anastasios Kyrillidis, Moshe Y. Vardi, Zhiwei Zhang
On Continuous Local BDD-Based Search for Hybrid SAT Solving. AAAI (2021)
Chen Dun, Cameron R. Wolfe, Christopher M. Jermaine, Anastasios Kyrillidis
ResIST: Layer-Wise Decomposition of ResNets for Distributed Training. CoRR (2021)
John Chen, Qihan Wang, Anastasios Kyrillidis
Mitigating Deep Double Descent by Concatenating Inputs. CIKM (2021)
Junhyung Lyle Kim, George Kollias, Amir Kalev, Ken X. Wei, Anastasios Kyrillidis
Fast quantum state reconstruction via accelerated non-convex programming. CoRR (2021)
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 (2021)
Fangshuo Liao, Anastasios Kyrillidis
On the Convergence of Shallow Neural Network Training with Randomly Masked Neurons. CoRR (2021)
Cameron R. Wolfe, Anastasios Kyrillidis
i-SpaSP: Structured Neural Pruning via Sparse Signal Recovery. CoRR (2021)
Junhyung Lyle Kim, Panos Toulis, Anastasios Kyrillidis
Convergence and Stability of the Stochastic Proximal Point Algorithm with Momentum. CoRR (2021)
Anastasios Kyrillidis, Moshe Y. Vardi, Zhiwei Zhang
On Continuous Local BDD-Based Search for Hybrid SAT Solving. CoRR (2020)
Vatsal Shah, Soumya Basu, Anastasios Kyrillidis, Sujay Sanghavi
On Generalization of Adaptive Methods for Over-parameterized Linear Regression. CoRR (2020)
John Chen, Vatsal Shah, Anastasios Kyrillidis
Negative Sampling in Semi-Supervised learning. ICML (2020)
T. Mitchell Roddenberry, Santiago Segarra, Anastasios Kyrillidis
Rank-One Measurements of Low-Rank PSD Matrices Have Small Feasible Sets. CoRR (2020)
Kelly Geyer, Anastasios Kyrillidis, Amir Kalev
Low-rank regularization and solution uniqueness in over-parameterized matrix sensing. AISTATS (2020)
John Chen, Samarth Sinha, Anastasios Kyrillidis
ImCLR: Implicit Contrastive Learning for Image Classification. CoRR (2020)
Anastasios Kyrillidis, Anshumali Shrivastava, Moshe Y. Vardi, Zhiwei Zhang
FourierSAT: A Fourier Expansion-Based Algebraic Framework for Solving Hybrid Boolean Constraints. AAAI (2020)
Jacky Y. Zhang, Rajiv Khanna, Anastasios Kyrillidis, Oluwasanmi Koyejo
Bayesian Coresets: An Optimization Perspective. CoRR (2020)
Michael P. Perrone, Haidar Khan, Changhoan Kim, Anastasios Kyrillidis, Jerry Quinn, Valentina Salapura
Optimal Mini-Batch Size Selection for Fast Gradient Descent. CoRR (2019)
Ryan Spring, Anastasios Kyrillidis, Vijai Mohan, Anshumali Shrivastava
Compressing Gradient Optimizers via Count-Sketches. CoRR (2019)
John Chen, Anastasios Kyrillidis
Decaying momentum helps neural network training. CoRR (2019)
John Chen, Vatsal Shah, Anastasios Kyrillidis
Negative sampling in semi-supervised learning. CoRR (2019)
Jacky Y. Zhang, Rajiv Khanna, Anastasios Kyrillidis, Oluwasanmi Koyejo
Learning Sparse Distributions using Iterative Hard Thresholding. NeurIPS (2019)
Binhang Yuan, Anastasios Kyrillidis, Christopher M. Jermaine
Distributed Learning of Deep Neural Networks using Independent Subnet Training. CoRR (2019)
Anastasios Kyrillidis, Anshumali Shrivastava, Moshe Y. Vardi, Zhiwei Zhang
FourierSAT: A Fourier Expansion-Based Algebraic Framework for Solving Hybrid Boolean Constraints. CoRR (2019)
Ryan Spring, Anastasios Kyrillidis, Vijai Mohan, Anshumali Shrivastava
Compressing Gradient Optimizers via Count-Sketches. ICML (2019)
Alexander Ratner, Dan Alistarh, Gustavo Alonso, David G. Andersen, Peter Bailis, Sarah Bird, Nicholas Carlini, Bryan Catanzaro, Eric 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 R. 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 (2019)
Jacky Y. Zhang, Rajiv Khanna, Anastasios Kyrillidis, Oluwasanmi Koyejo
Learning Sparse Distributions using Iterative Hard Thresholding. CoRR (2019)
Tianyang Li, Anastasios Kyrillidis, Liu Liu, Constantine Caramanis
Approximate Newton-based statistical inference using only stochastic gradients. CoRR (2018)
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) (2018)
Tianyang Li, Liu Liu, Anastasios Kyrillidis, Constantine Caramanis
Statistical Inference Using SGD. AAAI (2018)
Anastasios Kyrillidis, Shashanka Ubaru, Georgios Kollias, Kristofer E. Bouchard
Run Procrustes, Run! On the convergence of accelerated Procrustes Flow. CoRR (2018)
Anastasios Kyrillidis
-norm low-rank approximation. CoRR (2018)
Anastasios Kyrillidis
-norm low-rank approximation. UAI (2018)
Quoc Tran-Dinh, Anastasios Kyrillidis, Volkan Cevher
A Single-Phase, Proximal Path-Following Framework. Math. Oper. Res. 43 (4) (2018)
Anastasios Kyrillidis, Amir Kalev
Implicit regularization and solution uniqueness in over-parameterized matrix sensing. CoRR (2018)
Rajiv Khanna, Anastasios Kyrillidis
IHT dies hard: Provable accelerated Iterative Hard Thresholding. AISTATS (2018)
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) (2018)
Tianyang Li, Liu Liu, Anastasios Kyrillidis, Constantine Caramanis
Statistical inference using SGD. CoRR (2017)
Dohyung Park, Anastasios Kyrillidis, Constantine Caramanis, Sujay Sanghavi
Non-square matrix sensing without spurious local minima via the Burer-Monteiro approach. AISTATS (2017)
Anastasios Kyrillidis, Amir Kalev, Dohyung Park, Srinadh Bhojanapalli, Constantine Caramanis, Sujay Sanghavi
Provable quantum state tomography via non-convex methods. CoRR (2017)
Rajiv Khanna, Anastasios Kyrillidis
IHT dies hard: Provable accelerated Iterative Hard Thresholding. CoRR (2017)
Hemant Tyagi, Anastasios Kyrillidis, Bernd Gärtner, Andreas Krause
Learning Sparse Additive Models with Interactions in High Dimensions. AISTATS (2016)
Quoc Tran-Dinh, Anastasios Kyrillidis, Volkan Cevher
A single-phase, proximal path-following framework. CoRR (2016)
Megasthenis Asteris, Anastasios Kyrillidis, Oluwasanmi Koyejo, Russell A. Poldrack
A simple and provable algorithm for sparse diagonal CCA. CoRR (2016)
Vatsal Shah, Megasthenis Asteris, Anastasios Kyrillidis, Sujay Sanghavi
Trading-off variance and complexity in stochastic gradient descent. CoRR (2016)
Anastasios Kyrillidis, Bubacarr Bah, Rouzbeh Hasheminezhad, Quoc Tran-Dinh, Luca Baldassarre, Volkan Cevher
Convex block-sparse linear regression with expanders - provably. CoRR (2016)
Dohyung Park, Anastasios Kyrillidis, Constantine Caramanis, Sujay Sanghavi
Finding Low-rank Solutions to Matrix Problems, Efficiently and Provably. CoRR (2016)
Dohyung Park, Anastasios Kyrillidis, Constantine Caramanis, Sujay Sanghavi
Non-square matrix sensing without spurious local minima via the Burer-Monteiro approach. CoRR (2016)
Megasthenis Asteris, Anastasios Kyrillidis, Dimitris S. Papailiopoulos, Alexandros G. Dimakis
Bipartite Correlation Clustering: Maximizing Agreements. AISTATS (2016)

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Publication Activity (10 Years)

Top Topics

Top Venues

Anastasios Kyrillidis