Emanuel Laude

7 papers · 2016–2025 · 4 venues · across top CS/AI venues

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Achievements

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🌍 Conference Polyglot · Bronze 🏃 Academic Marathon · Sprint 🌉 Interdisciplinary Bridge · Silver 🗺️ Taxonomy Completionist (11) 🐣 Hot Topic Early Bird

Venues

AISTATS (2) CVPR (2) ICML (2) ECCV (1)

Top co-authors

Daniel Cremers (4) Panagiotis Patrinos (3) Konstantinos Oikonomidis (2) Tao Wu (2) Csaba Domokos (1) Andreas Themelis (1) Jan Lellmann (1) Robin Kenis (1) Thomas Möllenhoff (1) Puya Latafat (1)

Research topics

Machine Learning (7) Optimization & Theory · Machine Learning (6) Mathematics & Optimization (5) Optimization (5) Computer Vision (2) Deep Learning (2) Optimization & Theory · Deep Learning (2) Processing (2) Core AI (1) Core Methods (1) Learning Types (1)

Keywords

convergence (2) markov random field (2) non-convex optimization (2) convex relaxation (2) primal-dual optimization (1) energy minimization (1) transductive inference (1) alternating minimization (1) primal-dual algorithm (1) distributed training (1) moreau-yosida regularization (1) proximal splitting (1) alternating direction method of multiplier (1) gradient clipping (1) generalized smoothness (1) approximation guarantee (1) moreau envelope (1) proximal mapping (1) semi-algebraic function (1) video object segmentation (1)

Papers

Nonlinearly Preconditioned Gradient Methods under Generalized Smoothness ICML 2025 Adaptive Proximal Gradient Methods Are Universal Without Approximation ICML 2024 Convex Relaxations for Manifold-Valued Markov Random Fields with Approximation Guarantees ECCV 2024 Optimization of Inf-Convolution Regularized Nonconvex Composite Problems AISTATS 2019 A Nonconvex Proximal Splitting Algorithm under Moreau-Yosida Regularization AISTATS 2018 Discrete-Continuous ADMM for Transductive Inference in Higher-Order MRFs CVPR 2018 Sublabel-Accurate Relaxation of Nonconvex Energies CVPR 2016