Anastasios Kyrillidis

A Catalyst Framework for the Quantum Linear System Problem via the Proximal Point Algorithm AAAI 2026 Sweeping Heterogeneity with Smart MoPs: Mixture of Prompts for LLM Task Adaptation AAAI 2025 Adaptive Federated Learning with Auto-Tuned Clients ICLR 2024 On the Error-Propagation of Inexact Hotelling’s Deflation for Principal Component Analysis ICML 2024 Provable Accelerated Convergence of Nesterov’s Momentum for Deep ReLU Neural Networks ALT 2024 Efficient and Light-Weight Federated Learning via Asynchronous Distributed Dropout AISTATS 2023 Federated Learning Over Images: Vertical Decompositions and Pre-Trained Backbones Are Difficult to Beat ICCV 2023 LOFT: Finding Lottery Tickets through Filter-wise Training AISTATS 2023 Scissorhands: Exploiting the Persistence of Importance Hypothesis for LLM KV Cache Compression at Test Time NeurIPS 2023 Strong Lottery Ticket Hypothesis with ε–perturbation AISTATS 2023 Convergence and Stability of the Stochastic Proximal Point Algorithm with Momentum L4DC 2022 i-SpaSP: Structured Neural Pruning via Sparse Signal Recovery L4DC 2022 PipeGCN: Efficient Full-Graph Training of Graph Convolutional Networks with Pipelined Feature Communication ICLR 2022 ResIST: Layer-wise decomposition of ResNets for distributed training UAI 2022 Stackmix: a complementary mix algorithm UAI 2022 Bayesian Coresets: Revisiting the Nonconvex Optimization Perspective AISTATS 2021 On Continuous Local BDD-Based Search for Hybrid SAT Solving AAAI 2021 FourierSAT: A Fourier Expansion-Based Algebraic Framework for Solving Hybrid Boolean Constraints AAAI 2020 Low-rank regularization and solution uniqueness in over-parameterized matrix sensing AISTATS 2020 Negative Sampling in Semi-Supervised learning ICML 2020 Compressing Gradient Optimizers via Count-Sketches ICML 2019 Learning Sparse Distributions using Iterative Hard Thresholding NeurIPS 2019 IHT dies hard: Provable accelerated Iterative Hard Thresholding AISTATS 2018 Non-square matrix sensing without spurious local minima via the Burer-Monteiro approach AISTATS 2017 A Simple and Provable Algorithm for Sparse Diagonal CCA ICML 2016 Bipartite Correlation Clustering: Maximizing Agreements AISTATS 2016 Convex Block-sparse Linear Regression with Expanders – Provably AISTATS 2016 Dropping Convexity for Faster Semi-definite Optimization COLT 2016 Learning Sparse Additive Models with Interactions in High Dimensions AISTATS 2016 Composite Self-Concordant Minimization JMLR 2015 Sparse PCA via Bipartite Matchings NeurIPS 2015 Stay on path: PCA along graph paths ICML 2015 A proximal Newton framework for composite minimization: Graph learning without Cholesky decompositions and matrix inversions ICML 2013 Sparse projections onto the simplex ICML 2013