Ioannis Mitliagkas
34 papers · 2013–2025 · 5 conferences · across top CS/AI conferences
Achievements
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🏃 Academic Marathon (12) 🌍 Conference Polyglot (5) 🌉 Interdisciplinary Bridge 🧭 Keyword Pioneer 🐣 Hot Topic Early Bird
🌉
Interdisciplinary Bridge
🌍
Conference Polyglot
(5)
🏃
Academic Marathon
(12)
👑
Triple Crown
🏆
Keyword Champion
(2)
🌱
Topic Pioneer
🗃️
Keyword Collector
(114)
⚡
Prolific Year
(5)
🚀
Conference Pioneer
💎
Century Club
(34)
🔥
Unstoppable
(10)
📈
Trend Setter
Conferences
ICML (11)
NIPS (10)
AISTATS (6)
ICLR (6)
CLEAR (1)
Top co-authors
Keywords
representation learning
(5)
gradient descent
(4)
stochastic optimization
(3)
generative adversarial network
(3)
bilinear game
(3)
convergence rate
(3)
gaussian mixture model
(2)
condition number
(2)
differentiable game
(2)
variance reduction
(2)
domain generalization
(2)
anomaly detection
(2)
gibbs sampling
(2)
distribution shift
(2)
adversarial robustness
(2)
markov chain monte carlo
(2)
principal component analysis
(2)
convergence analysis
(2)
independent component analysis
(2)
consensus optimization
(2)
Papers
Solving hidden monotone variational inequalities with surrogate losses
ICLR 2025
Compositional Risk Minimization
ICML 2025
Empirical Analysis of Model Selection for Heterogeneous Causal Effect Estimation
ICLR 2024
No Wrong Turns: The Simple Geometry Of Neural Networks Optimization Paths
ICML 2024
Expecting The Unexpected: Towards Broad Out-Of-Distribution Detection
NIPS 2024
CADet: Fully Self-Supervised Out-Of-Distribution Detection With Contrastive Learning
NIPS 2023
Additive Decoders for Latent Variables Identification and Cartesian-Product Extrapolation
NIPS 2023
Synergies between Disentanglement and Sparsity: Generalization and Identifiability in Multi-Task Learning
ICML 2023
A Unified Approach to Reinforcement Learning, Quantal Response Equilibria, and Two-Player Zero-Sum Games
ICLR 2023
Neural Networks Efficiently Learn Low-Dimensional Representations with SGD
ICLR 2023
Performative Prediction with Neural Networks
AISTATS 2023
Towards efficient representation identification in supervised learning
CLEAR 2022
Gradient Descent Is Optimal Under Lower Restricted Secant Inequality And Upper Error Bound
NIPS 2022
Adversarial score matching and improved sampling for image generation
ICLR 2021
Invariance Principle Meets Information Bottleneck for Out-of-Distribution Generalization
NIPS 2021
Stochastic Gradient Descent-Ascent and Consensus Optimization for Smooth Games: Convergence Analysis under Expected Co-coercivity
NIPS 2021
A Study of Condition Numbers for First-Order Optimization
AISTATS 2021
Stochastic Hamiltonian Gradient Methods for Smooth Games
ICML 2020
In search of robust measures of generalization
NIPS 2020
Accelerating Smooth Games by Manipulating Spectral Shapes
AISTATS 2020
A Tight and Unified Analysis of Gradient-Based Methods for a Whole Spectrum of Differentiable Games
AISTATS 2020
Linear Lower Bounds and Conditioning of Differentiable Games
ICML 2020
h-detach: Modifying the LSTM Gradient Towards Better Optimization
ICLR 2019
Reducing the variance in online optimization by transporting past gradients
NIPS 2019
Negative Momentum for Improved Game Dynamics
AISTATS 2019
Multi-objective training of Generative Adversarial Networks with multiple discriminators
ICML 2019
State-Reification Networks: Improving Generalization by Modeling the Distribution of Hidden Representations
ICML 2019
Manifold Mixup: Better Representations by Interpolating Hidden States
ICML 2019
Learning Representations and Generative Models for 3D Point Clouds
ICML 2018
Accelerated Stochastic Power Iteration
AISTATS 2018
Improving Gibbs Sampler Scan Quality with DoGS
ICML 2017
Scan Order in Gibbs Sampling: Models in Which it Matters and Bounds on How Much
NIPS 2016
Finding Dense Subgraphs via Low-Rank Bilinear Optimization
ICML 2014
Memory Limited, Streaming PCA
NIPS 2013