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Guy Blanc

13 papers · 2018–2025 · 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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+6 more ↓ πŸ—ΊοΈ Taxonomy Completionist (21) πŸƒ Academic Marathon Β· Sprint 🌍 Conference Polyglot Β· Bronze πŸŒ‰ Interdisciplinary Bridge Β· Bronze 🐣 Hot Topic Early Bird
🧭 Keyword Pioneer 🀝 Dynamic Duo (11) πŸ—ƒοΈ Keyword Collector (64) πŸ“ˆ Trend Setter πŸ’Ž Century Club Β· Bronze ❓ The Questioner

Venues

COLT (5) ICML (4) NeurIPS (4)

Top co-authors

Li-Yang Tan (11) Jane Lange (10) Neha Gupta (3) Ali Malik (2) Paul Valiant (1) Mo Tiwari (1) Caleb Koch (1) Lydia Zakynthinou (1) Konstantina Bairaktari (1) Gregory Valiant (1)

Research topics

Machine Learning (12) Optimization & Theory Β· Machine Learning (11) Core Methods (8) Artificial Intelligence (4) Core AI (3) Learning Types (3) Computer Science (1) Deep Learning (1) Architectures (1) Foundations (1) Learning Paradigms (1) Optimization & Theory Β· Deep Learning (1)

Keywords

decision tree (4) decision tree learning (3) sample complexity (3) noise tolerance (2) pac learning (1) computational complexity (1) stochastic gradient descent (1) boosting algorithm (1) attribute-efficient learning (1) agnostic learning (1) multi-class classification (1) statistical query (1) halfspace learning (1) additive noise (1) query complexity (1) sampling distribution (1) polynomial time (1) greedy algorithm (1) multi-task learning (1) learning theory (1)

Papers

A Distributional-Lifting Theorem for PAC Learning COLT 2025 Harnessing the power of choices in decision tree learning NeurIPS 2023 Multitask Learning via Shared Features: Algorithms and Hardness COLT 2023 A query-optimal algorithm for finding counterfactuals ICML 2022 On the power of adaptivity in statistical adversaries COLT 2022 Open Problem: Properly learning decision trees in polynomial time? COLT 2022 Popular decision tree algorithms are provably noise tolerant ICML 2022 Provably efficient, succinct, and precise explanations NeurIPS 2021 Estimating decision tree learnability with polylogarithmic sample complexity NeurIPS 2020 Implicit regularization for deep neural networks driven by an Ornstein-Uhlenbeck like process COLT 2020 Provable guarantees for decision tree induction: the agnostic setting ICML 2020 Universal guarantees for decision tree induction via a higher-order splitting criterion NeurIPS 2020 Adaptive Sampled Softmax with Kernel Based Sampling ICML 2018