David Balduzzi
19 papers · 2012–2021 · 6 venues · across top CS/AI venues
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Achievements
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🗺️ Taxonomy Completionist (37) 🏃 Academic Marathon · Sprint 🌍 Conference Polyglot · Silver 🌉 Interdisciplinary Bridge · Silver 🐣 Hot Topic Early Bird
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Keyword Champion
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Keyword Pioneer
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Topic Evolution
👑
Triple Crown
💎
Century Club · Bronze
🔥
Unstoppable · Bronze
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The Questioner
🚀
Conference Pioneer
🗃️
Keyword Collector
(92)
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Trend Setter
Top co-authors
Research topics
Machine Learning
(15)
Optimization & Theory
(12)
Artificial Intelligence
(11)
Core AI
(10)
Deep Learning
(6)
Learning Types · Machine Learning
(6)
Mathematics & Optimization
(3)
Reinforcement Learning
(3)
Architectures
(3)
Core Methods
(3)
Learning Types · Deep Learning
(3)
Optimization
(3)
Application Areas
(2)
Methods
(2)
Interdisciplinary
(1)
Keywords
game theory
(5)
nash equilibrium
(5)
gradient descent
(4)
zero-sum game
(4)
multi-agent system
(3)
differentiable game
(3)
feature learning
(2)
symplectic gradient adjustment
(2)
kernel methods
(2)
hamiltonian game
(2)
domain generalization
(2)
generative adversarial network
(2)
multi-agent learning
(2)
batch normalization
(1)
uncertainty quantification
(1)
nonparametric bayesian
(1)
gradient-based optimization
(1)
object recognition
(1)
benchmark evaluation
(1)
bayesian inference
(1)
Papers
A Limited-Capacity Minimax Theorem for Non-Convex Games or: How I Learned to Stop Worrying about Mixed-Nash and Love Neural Nets
AISTATS 2021
From Poincaré Recurrence to Convergence in Imperfect Information Games: Finding Equilibrium via Regularization
ICML 2021
From Chaos to Order: Symmetry and Conservation Laws in Game Dynamics
ICML 2020
Real World Games Look Like Spinning Tops
NeurIPS 2020
Smooth markets: A basic mechanism for organizing gradient-based learners
ICLR 2020
Differentiable Game Mechanics
JMLR 2019
Open-ended learning in symmetric zero-sum games
ICML 2019
Stable Opponent Shaping in Differentiable Games
ICLR 2019
Re-evaluating evaluation
NeurIPS 2018
The Mechanics of n-Player Differentiable Games
ICML 2018
Neural Taylor Approximations: Convergence and Exploration in Rectifier Networks
ICML 2017
Strongly-Typed Agents are Guaranteed to Interact Safely
ICML 2017
The Shattered Gradients Problem: If resnets are the answer, then what is the question?
ICML 2017
Strongly-Typed Recurrent Neural Networks
ICML 2016
Domain Generalization for Object Recognition With Multi-Task Autoencoders
ICCV 2015
Correlated random features for fast semi-supervised learning
NeurIPS 2013
Domain Generalization via Invariant Feature Representation
ICML 2013
A Nonparametric Conjugate Prior Distribution for the Maximizing Argument of a Noisy Function
NeurIPS 2012
Towards a learning-theoretic analysis of spike-timing dependent plasticity
NeurIPS 2012