Mikael Johansson
17 papers · 2018–2025 · 5 venues · across top CS/AI venues
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Achievements
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🗺️ Taxonomy Completionist (29) 🌉 Interdisciplinary Bridge · Silver 🌍 Conference Polyglot · Silver 🏃 Academic Marathon · Sprint 🐣 Hot Topic Early Bird
🔬
Deep Specialist
(11)
🏆
Grand Slam
💎
Century Club · Bronze
🗃️
Keyword Collector
(89)
🔥
Unstoppable · Bronze
Venues
Top co-authors
Research topics
Machine Learning
(17)
Optimization & Theory · Machine Learning
(16)
Mathematics & Optimization
(12)
Optimization
(12)
Deep Learning
(6)
Optimization & Theory · Deep Learning
(4)
Application Areas
(2)
Core Methods
(2)
Learning Types · Machine Learning
(2)
Artificial Intelligence
(1)
Reinforcement Learning
(1)
Applications
(1)
Learning Paradigms · Artificial Intelligence
(1)
Learning Paradigms · Machine Learning
(1)
Learning Types · Deep Learning
(1)
Keywords
stochastic gradient descent
(5)
distributed learning
(4)
convergence analysis
(4)
non-convex optimization
(3)
asynchronous optimization
(3)
convergence rate
(3)
douglas-rachford splitting
(2)
nonsmooth optimization
(2)
momentum method
(2)
stochastic optimization
(2)
optimal transport
(2)
block coordinate descent
(2)
lyapunov function
(1)
gaussian process
(1)
domain adaptation
(1)
incremental gradient
(1)
numerical optimization
(1)
reinforcement learning
(1)
machine learning
(1)
distributed optimization
(1)
Papers
An Asynchronous Bundle Method for Distributed Learning Problems
ICLR 2025
From Promise to Practice: Realizing High-performance Decentralized Training
ICLR 2025
Nonconvex Federated Learning on Compact Smooth Submanifolds With Heterogeneous Data
NeurIPS 2024
Asynchronous Iterations in Optimization: New Sequence Results and Sharper Algorithmic Guarantees
JMLR 2023
Bringing regularized optimal transport to lightspeed: a splitting method adapted for GPUs
NeurIPS 2023
Delay-agnostic Asynchronous Coordinate Update Algorithm
ICML 2023
Generalized Polyak Step Size for First Order Optimization with Momentum
ICML 2023
A fast and accurate splitting method for optimal transport: analysis and implementation
ICLR 2022
Delay-Adaptive Step-sizes for Asynchronous Learning
ICML 2022
A Flexible Framework for Communication-Efficient Machine Learning
AAAI 2021
On the Convergence of Step Decay Step-Size for Stochastic Optimization
NeurIPS 2021
Stability and Convergence of Stochastic Gradient Clipping: Beyond Lipschitz Continuity and Smoothness
ICML 2021
Anderson Acceleration of Proximal Gradient Methods
ICML 2020
Convergence of a Stochastic Gradient Method with Momentum for Non-Smooth Non-Convex Optimization
ICML 2020
Curvature-Exploiting Acceleration of Elastic Net Computations
ICML 2019
Continuous-time Value Function Approximation in Reproducing Kernel Hilbert Spaces
NeurIPS 2018
The Convergence of Sparsified Gradient Methods
NeurIPS 2018