James Martens
16 papers · 2010–2024 · 5 conferences · across top CS/AI conferences
Achievements
Jump to papers ↓+7 more ↓ Show less ↑
๐ Conference Polyglot (5) ๐ Interdisciplinary Bridge ๐บ๏ธ Taxonomy Completionist (10) ๐งญ Keyword Pioneer ๐ Academic Marathon (14)
๐
Cross-Pollinator
(14)
๐
Conference Polyglot
(5)
๐
Academic Marathon
(14)
๐
Keyword Champion
(2)
๐
Century Club
(16)
๐
Conference Pioneer
โ
The Questioner
Conferences
NIPS (5)
ICLR (4)
ICML (4)
JMLR (2)
AISTATS (1)
Top co-authors
Keywords
natural gradient
(4)
second-order optimization
(3)
convergence analysis
(2)
neural network
(2)
stochastic gradient descent
(2)
gradient descent
(2)
generative adversarial network
(2)
fisher information matrix
(2)
symplectic gradient adjustment
(2)
hamiltonian game
(2)
differentiable game
(2)
restricted boltzmann machine
(2)
kronecker factorization
(2)
nash equilibrium
(1)
probabilistic inference
(1)
markov chain monte carlo
(1)
neural network theory
(1)
adversarial robustness
(1)
representation learning
(1)
neural network optimization
(1)
Papers
Normalization and effective learning rates in reinforcement learning
NIPS 2024
Pre-training via Denoising for Molecular Property Prediction
ICLR 2023
Deep Transformers without Shortcuts: Modifying Self-attention for Faithful Signal Propagation
ICLR 2023
Deep Learning without Shortcuts: Shaping the Kernel with Tailored Rectifiers
ICLR 2022
New Insights and Perspectives on the Natural Gradient Method
JMLR 2020
Adversarial Robustness through Local Linearization
NIPS 2019
Differentiable Game Mechanics
JMLR 2019
Which Algorithmic Choices Matter at Which Batch Sizes? Insights From a Noisy Quadratic Model
NIPS 2019
Fast Convergence of Natural Gradient Descent for Over-Parameterized Neural Networks
NIPS 2019
The Mechanics of n-Player Differentiable Games
ICML 2018
Kronecker-factored Curvature Approximations for Recurrent Neural Networks
ICLR 2018
A Kronecker-factored approximate Fisher matrix for convolution layers
ICML 2016
Optimizing Neural Networks with Kronecker-factored Approximate Curvature
ICML 2015
On the Representational Efficiency of Restricted Boltzmann Machines
NIPS 2013
On the importance of initialization and momentum in deep learning
ICML 2013
Parallelizable Sampling of Markov Random Fields
AISTATS 2010