Lunjia Hu

17 papers · 2017–2026 · 5 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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🐣 Hot Topic Early Bird 🌍 Conference Polyglot · Silver 🏃 Academic Marathon · Sprint 🌉 Interdisciplinary Bridge · Bronze 🗺️ Taxonomy Completionist (22)

💎 Century Club · Bronze ❓ The Questioner 🗃️ Keyword Collector (81)

Venues

COLT (7) NeurIPS (5) AISTATS (2) ICML (2) ALT (1)

Top co-authors

Omer Reingold (3) Chutong Yang (3) Liwei Wang (2) Yifan Wu (2) Moses Charikar (2) Charlotte Peale (2) Parikshit Gopalan (2) Kevin Tian (2) Zhiqiang Hu (1) Avrim Blum (1)

Research topics

Machine Learning (17) Optimization & Theory (15) Core Methods (6) Learning Types (5) Artificial Intelligence (4) Mathematics & Optimization (4) Application Areas (3) Core AI (3) Optimization (3) Learning Paradigms (1) Mathematics (1)

Keywords

sample complexity (3) calibration testing (2) approximation algorithm (2) calibration error (2) binary classification (1) robustness (1) learning theory (1) fairness (1) online learning (1) k-means clustering (1) pac learning (1) mean estimation (1) constrained optimization (1) outlier detection (1) distance estimation (1) dynamic programming (1) agnostic learning (1) label complexity (1) multi-class classification (1) principal component analysis (1)

Papers

A Perfectly Truthful Calibration Measure COLT 2026 Efficient Swap Multicalibration of Elicitable Properties COLT 2026 Near-optimal Swap Regret Minimization for Convex Losses COLT 2026 Simultaneous Blackwell Approachability and Applications to Multiclass Omniprediction COLT 2026 Multigroup Robustness ICML 2024 On Computationally Efficient Multi-Class Calibration COLT 2024 Testing Calibration in Nearly-Linear Time NeurIPS 2024 Omnipredictors for Constrained Optimization ICML 2023 Simple, Scalable and Effective Clustering via One-Dimensional Projections NeurIPS 2023 When Does Optimizing a Proper Loss Yield Calibration? NeurIPS 2023 Metric Entropy Duality and the Sample Complexity of Outcome Indistinguishability ALT 2022 Subspace Recovery from Heterogeneous Data with Non-isotropic Noise NeurIPS 2022 Approximation Algorithms for Orthogonal Non-negative Matrix Factorization AISTATS 2021 Robust Mean Estimation on Highly Incomplete Data with Arbitrary Outliers AISTATS 2021 Active Tolerant Testing COLT 2018 Towards Understanding Learning Representations: To What Extent Do Different Neural Networks Learn the Same Representation NeurIPS 2018 Quadratic Upper Bound for Recursive Teaching Dimension of Finite VC Classes COLT 2017