Joshua Agterberg

4 papers · 2022–2025 · 3 venues · across top CS/AI venues

Authors are matched by name, so researchers who share a name ("Yang Liu", "Wei Wang") appear as a single profile and their paper counts, venues and achievements are combined. How identity is handled.

Achievements

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🌍 Conference Polyglot · Bronze 🌉 Interdisciplinary Bridge · Bronze 🗺️ Taxonomy Completionist (12)

Venues

AISTATS (2) ICLR (1) L4DC (1)

Top co-authors

René Vidal (3) Uday Kiran Reddy Tadipatri (2) Benjamin David Haeffele (1) Juan Elenter (1) Alejandro Ribeiro (1) Ingvar Ziemann (1) Liangzu Peng (1) Jeremias Sulam (1) Benjamin D. Haeffele (1)

Research topics

Machine Learning (4) Optimization & Theory · Machine Learning (3) Deep Learning (2) Mathematics & Optimization (2) Optimization (2) Core Methods (1) Learning Types (1) Optimization & Theory · Deep Learning (1) Techniques (1)

Keywords

singular value decomposition (2) sample complexity (2) empirical risk minimization (1) low-rank approximation (1) sparse principal component analysis (1) convex relaxation (1) support recovery (1) nuclear norm minimization (1) eigenvector estimation (1) generalization bound (1) pre-trained model (1) theoretical guarantee (1) burer-monteiro factorization (1) entrywise recovery (1) high-dimensional subgaussian design (1) subspace perturbation (1) linear system identification (1) minimal state representation (1) continual learning (1) positive homogeneity (1)

Papers

A Convex Relaxation Approach to Generalization Analysis for Parallel Positively Homogeneous Networks AISTATS 2025 LoRanPAC: Low-rank Random Features and Pre-trained Models for Bridging Theory and Practice in Continual Learning ICLR 2025 Nonconvex Linear System Identification with Minimal State Representation L4DC 2025 Entrywise Recovery Guarantees for Sparse PCA via Sparsistent Algorithms AISTATS 2022