Elliot Meyerson

7 papers · 2018–2025 · 3 venues · across top CS/AI venues

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Achievements

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🌍 Conference Polyglot · Bronze 🏃 Academic Marathon · Sprint 🗺️ Taxonomy Completionist (13) 🧬 Topic Evolution 🚀 Conference Pioneer

Venues

ICLR (3) ICML (2) NeurIPS (2)

Top co-authors

Risto Miikkulainen (6) Xin Qiu (2) Olivier Francon (1) Babak Hodjat (1) Darren Sargent (1)

Research topics

Machine Learning (5) Artificial Intelligence (4) Deep Learning (4) Learning Paradigms (3) Application Areas (2) Architectures (2) Core AI (2) Learning Types · Machine Learning (2) Core Methods (1) Learning Types · Deep Learning (1) Models (1) Optimization & Theory (1) Techniques (1)

Keywords

multi-task learning (4) neural network (2) transfer learning (2) uncertainty quantification (1) knowledge distillation (1) deep learning (1) asymptotic analysis (1) gaussian process (1) regression analysis (1) evolutionary algorithm (1) problem decomposition (1) spatial embedding (1) shared layer (1) kernel methods (1) variable embedding (1) pseudo-task augmentation (1) task sharing (1) modular reparameterization (1) model recombination (1) residual modeling (1)

Papers

Position: Scaling LLM Agents Requires Asymptotic Analysis with LLM Primitives ICML 2025 Unlocking the Potential of Global Human Expertise NeurIPS 2024 The Traveling Observer Model: Multi-task Learning Through Spatial Variable Embeddings ICLR 2021 Quantifying Point-Prediction Uncertainty in Neural Networks via Residual Estimation with an I/O Kernel ICLR 2020 Modular Universal Reparameterization: Deep Multi-task Learning Across Diverse Domains NeurIPS 2019 Beyond Shared Hierarchies: Deep Multitask Learning through Soft Layer Ordering ICLR 2018 Pseudo-task Augmentation: From Deep Multitask Learning to Intratask Sharing—and Back ICML 2018