Konstantinos Stavropoulos

16 papers · 2021–2026 · 4 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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🗺️ Taxonomy Completionist (16) 🏃 Academic Marathon · Sprint 🌍 Conference Polyglot · Bronze 🌉 Interdisciplinary Bridge · Bronze 🐣 Hot Topic Early Bird

🔬 Deep Specialist (13) 🤝 Dynamic Duo (11) 🏆 Keyword Champion (6) ⚡ Prolific Year · Productive 🔥 Unstoppable · Bronze 🗃️ Keyword Collector (73) 💎 Century Club · Bronze

Venues

COLT (7) NeurIPS (6) ICLR (2) AISTATS (1)

Top co-authors

Adam Klivans (11) Arsen Vasilyan (10) Gautam Chandrasekaran (4) Aravind Gollakota (3) Vasilis Kontonis (3) Alkis Kalavasis (2) Surbhi Goel (2) Dimitris Fotakis (1) Raghu Meka (1) Lin Lin Lee (1)

Research topics

Machine Learning (16) Optimization & Theory (16) Core Methods (5) Learning Types (4) Artificial Intelligence (3) Application Areas (3) Learning Paradigms (3) Deep Learning (1) Mathematics & Optimization (1) Architectures (1) Mathematics (1) Probability (1)

Keywords

testable learning (6) distribution shift (6) sample complexity (4) agnostic learning (3) massart noise (3) learning theory (3) domain adaptation (3) intersection of halfspace (3) label noise (2) halfspace learning (2) moment matching (2) ranking aggregation (1) exponential family (1) classification noise (1) pac learning (1) bregman divergence (1) logistic regression (1) mallows model (1) outlier removal (1) statistical query (1)

Papers

Equivalence of Coarse and Fine-Grained Models for Learning with Distribution Shift COLT 2026 Sandwiching Polynomials for Geometric Concepts with Low Intrinsic Dimension COLT 2026 Testing Noise Assumptions of Learning Algorithms COLT 2026 Learning Constant-Depth Circuits in Malicious Noise Models COLT 2025 Learning Neural Networks with Distribution Shift: Efficiently Certifiable Guarantees ICLR 2025 An Efficient Tester-Learner for Halfspaces ICLR 2024 Efficient Discrepancy Testing for Learning with Distribution Shift NeurIPS 2024 Learning Intersections of Halfspaces with Distribution Shift: Improved Algorithms and SQ Lower Bounds COLT 2024 Learning Noisy Halfspaces with a Margin: Massart is No Harder than Random NeurIPS 2024 Smoothed Analysis for Learning Concepts with Low Intrinsic Dimension COLT 2024 Testable Learning with Distribution Shift COLT 2024 Tolerant Algorithms for Learning with Arbitrary Covariate Shift NeurIPS 2024 Agnostically Learning Single-Index Models using Omnipredictors NeurIPS 2023 Tester-Learners for Halfspaces: Universal Algorithms NeurIPS 2023 Learning and Covering Sums of Independent Random Variables with Unbounded Support NeurIPS 2022 Aggregating Incomplete and Noisy Rankings AISTATS 2021