Mikael Johansson
17 papers · 2018–2025 · 5 conferences · across top CS/AI conferences
Achievements
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π Conference Polyglot (5) π£ Hot Topic Early Bird π§ Keyword Pioneer π Interdisciplinary Bridge π Academic Marathon (7)
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Conference Polyglot
(5)
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Academic Marathon
(7)
π£
Hot Topic Early Bird
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Keyword Champion
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Grand Slam
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Keyword Collector
(80)
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Century Club
(17)
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Trend Setter
Conferences
ICML (7)
NIPS (5)
ICLR (3)
AAAI (1)
JMLR (1)
Top co-authors
Keywords
stochastic gradient descent
(5)
convergence rate
(3)
non-convex optimization
(3)
convergence analysis
(3)
non-smooth optimization
(2)
asynchronous optimization
(2)
distributed learning
(2)
momentum method
(2)
domain adaptation
(1)
numerical optimization
(1)
reinforcement learning
(1)
incremental gradient
(1)
gaussian process
(1)
lyapunov function
(1)
distributed optimization
(1)
machine learning
(1)
neural network training
(1)
variance reduction
(1)
value function approximation
(1)
model-based reinforcement learning
(1)
Papers
From Promise to Practice: Realizing High-performance Decentralized Training
ICLR 2025
An Asynchronous Bundle Method for Distributed Learning Problems
ICLR 2025
Nonconvex Federated Learning on Compact Smooth Submanifolds With Heterogeneous Data
NIPS 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
NIPS 2023
Generalized Polyak Step Size for First Order Optimization with Momentum
ICML 2023
Delay-agnostic Asynchronous Coordinate Update Algorithm
ICML 2023
Delay-Adaptive Step-sizes for Asynchronous Learning
ICML 2022
A fast and accurate splitting method for optimal transport: analysis and implementation
ICLR 2022
Stability and Convergence of Stochastic Gradient Clipping: Beyond Lipschitz Continuity and Smoothness
ICML 2021
On the Convergence of Step Decay Step-Size for Stochastic Optimization
NIPS 2021
A Flexible Framework for Communication-Efficient Machine Learning
AAAI 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
NIPS 2018
The Convergence of Sparsified Gradient Methods
NIPS 2018