Anastasios Kyrillidis
34 papers · 2013–2026 · 11 conferences · across top CS/AI conferences
Achievements
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๐งญ Keyword Pioneer ๐ Renaissance Researcher (5) ๐ Interdisciplinary Bridge ๐บ๏ธ Taxonomy Completionist (12) ๐ Conference Polyglot (11)
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Conference Polyglot
(11)
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Academic Marathon
(12)
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Cross-Pollinator
(5)
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Keyword Champion
(2)
๐งฌ
Topic Evolution
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Grand Slam
๐ฅ
Unstoppable
(11)
โก
Prolific Year
(5)
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Century Club
(33)
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Conference Pioneer
๐๏ธ
Keyword Collector
(153)
Conferences
AISTATS (10)
ICML (7)
AAAI (4)
NIPS (3)
ICLR (2)
L4DC (2)
UAI (2)
ALT (1)
COLT (1)
ICCV (1)
JMLR (1)
Top co-authors
Keywords
model compression
(5)
gradient descent
(5)
matrix factorization
(3)
convex optimization
(3)
sparse optimization
(3)
matrix sensing
(2)
federated learning
(2)
memory optimization
(2)
semi-supervised learning
(2)
dimensionality reduction
(2)
neural network pruning
(2)
non-convex optimization
(2)
lottery ticket hypothesis
(2)
distributed training
(2)
sparse pca
(2)
compressed sensing
(2)
boolean satisfiability
(2)
combinatorial optimization
(2)
sparse principal component analysis
(2)
momentum method
(2)
Papers
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
Provable Accelerated Convergence of Nesterovโs Momentum for Deep ReLU Neural Networks
ALT 2024
On the Error-Propagation of Inexact Hotellingโs Deflation for Principal Component Analysis
ICML 2024
Adaptive Federated Learning with Auto-Tuned Clients
ICLR 2024
Efficient and Light-Weight Federated Learning via Asynchronous Distributed Dropout
AISTATS 2023
Scissorhands: Exploiting the Persistence of Importance Hypothesis for LLM KV Cache Compression at Test Time
NIPS 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
Strong Lottery Ticket Hypothesis with $\varepsilon$โperturbation
AISTATS 2023
Convergence and Stability of the Stochastic Proximal Point Algorithm with Momentum
L4DC 2022
ResIST: Layer-wise decomposition of ResNets for distributed training
UAI 2022
Stackmix: a complementary mix algorithm
UAI 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
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
NIPS 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
Dropping Convexity for Faster Semi-definite Optimization
COLT 2016
Convex Block-sparse Linear Regression with Expanders โ Provably
AISTATS 2016
Learning Sparse Additive Models with Interactions in High Dimensions
AISTATS 2016
Bipartite Correlation Clustering: Maximizing Agreements
AISTATS 2016
A Simple and Provable Algorithm for Sparse Diagonal CCA
ICML 2016
Composite Self-Concordant Minimization
JMLR 2015
Stay on path: PCA along graph paths
ICML 2015
Sparse PCA via Bipartite Matchings
NIPS 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