Tolga Ergen
16 papers · 2020–2025 · 6 conferences · across top CS/AI conferences
Achievements
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🏃 Academic Marathon (5) 🌉 Interdisciplinary Bridge 🧭 Keyword Pioneer 🌍 Conference Polyglot (6) 🐝 Cross-Pollinator (15)
🌉
Interdisciplinary Bridge
🧭
Keyword Pioneer
🤝
Dynamic Duo
(15)
⚡
Prolific Year
(5)
🔥
Unstoppable
(6)
💎
Century Club
(16)
Conferences
ICLR (7)
ICML (4)
NIPS (2)
AISTATS (1)
JMLR (1)
NAACL (1)
Top co-authors
Keywords
convex optimization
(8)
relu network
(4)
neural network
(3)
spline interpolation
(3)
representation learning
(2)
deep neural network
(2)
weight decay
(2)
convex duality
(2)
text summarization
(1)
neural network optimization
(1)
group lasso
(1)
semi-definite programming
(1)
multiple kernel learning
(1)
semi-definite program
(1)
relu activation
(1)
benchmark dataset
(1)
neural collapse
(1)
gradient flow
(1)
weight decay regularization
(1)
gated relu network
(1)
Papers
MASSW: A New Dataset and Benchmark Tasks for AI-Assisted Scientific Workflows
NAACL 2025
Scaling Convex Neural Networks with Burer-Monteiro Factorization
ICLR 2024
Parallel Deep Neural Networks Have Zero Duality Gap
ICLR 2023
Path Regularization: A Convexity and Sparsity Inducing Regularization for Parallel ReLU Networks
NIPS 2023
Globally Optimal Training of Neural Networks with Threshold Activation Functions
ICLR 2023
Fixing the NTK: From Neural Network Linearizations to Exact Convex Programs
NIPS 2023
Demystifying Batch Normalization in ReLU Networks: Equivalent Convex Optimization Models and Implicit Regularization
ICLR 2022
Unraveling Attention via Convex Duality: Analysis and Interpretations of Vision Transformers
ICML 2022
Hidden Convexity of Wasserstein GANs: Interpretable Generative Models with Closed-Form Solutions
ICLR 2022
Revealing the Structure of Deep Neural Networks via Convex Duality
ICML 2021
Implicit Convex Regularizers of CNN Architectures: Convex Optimization of Two- and Three-Layer Networks in Polynomial Time
ICLR 2021
Convex Geometry and Duality of Over-parameterized Neural Networks
JMLR 2021
Global Optimality Beyond Two Layers: Training Deep ReLU Networks via Convex Programs
ICML 2021
Vector-output ReLU Neural Network Problems are Copositive Programs: Convex Analysis of Two Layer Networks and Polynomial-time Algorithms
ICLR 2021
Neural Networks are Convex Regularizers: Exact Polynomial-time Convex Optimization Formulations for Two-layer Networks
ICML 2020
Convex Geometry of Two-Layer ReLU Networks: Implicit Autoencoding and Interpretable Models
AISTATS 2020