Filip Hanzely
11 papers · 2018–2021 · 5 venues · across top CS/AI venues
Authors are matched by name, so researchers who share a name ("Yang Liu", "Wei Wang") appear as a single profile and their paper counts, venues and achievements are combined. How identity is handled.
Achievements
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🌉 Interdisciplinary Bridge · Silver 🗺️ Taxonomy Completionist (17) 🌍 Conference Polyglot · Silver 🧭 Keyword Pioneer 🤝 Dynamic Duo (11)
🚀
Conference Pioneer
⚡
Prolific Year · Productive
💎
Century Club · Bronze
Top co-authors
Research topics
Machine Learning
(10)
Optimization & Theory · Machine Learning
(10)
Mathematics & Optimization
(7)
Optimization
(7)
Artificial Intelligence
(3)
Learning Paradigms · Artificial Intelligence
(3)
Computer Vision
(1)
Deep Learning
(1)
Core Methods
(1)
Learning Paradigms · Machine Learning
(1)
Mathematics
(1)
Optimization & Theory · Deep Learning
(1)
Processing
(1)
Keywords
variance reduction
(5)
coordinate descent
(4)
distributed optimization
(3)
federated learning
(2)
convex optimization
(2)
empirical risk minimization
(2)
local sgd
(2)
communication sparsification
(2)
second-order optimization
(2)
stochastic optimization
(2)
stochastic gradient descent
(2)
importance sampling
(1)
low-rank decomposition
(1)
non-convex optimization
(1)
shadow removal
(1)
low-rank recovery
(1)
distributed learning
(1)
strongly convex
(1)
communication complexity
(1)
gradient descent
(1)
Papers
Local SGD: Unified Theory and New Efficient Methods
AISTATS 2021
Smoothness Matrices Beat Smoothness Constants: Better Communication Compression Techniques for Distributed Optimization
NeurIPS 2021
99% of Worker-Master Communication in Distributed Optimization Is Not Needed
UAI 2020
A Unified Theory of SGD: Variance Reduction, Sampling, Quantization and Coordinate Descent
AISTATS 2020
Lower Bounds and Optimal Algorithms for Personalized Federated Learning
NeurIPS 2020
Stochastic Subspace Cubic Newton Method
ICML 2020
Variance Reduced Coordinate Descent with Acceleration: New Method With a Surprising Application to Finite-Sum Problems
ICML 2020
Accelerated Coordinate Descent with Arbitrary Sampling and Best Rates for Minibatches
AISTATS 2019
A Nonconvex Projection Method for Robust PCA
AAAI 2019
Accelerated Stochastic Matrix Inversion: General Theory and Speeding up BFGS Rules for Faster Second-Order Optimization
NeurIPS 2018
SEGA: Variance Reduction via Gradient Sketching
NeurIPS 2018