Kurtland Chua

4 papers · 2018–2023 · 2 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 🏃 Academic Marathon · Sprint 🌉 Interdisciplinary Bridge · Bronze 🗺️ Taxonomy Completionist (10) 🐣 Hot Topic Early Bird

Venues

AISTATS (2) NeurIPS (2)

Top co-authors

Jason Lee (2) Roberto Calandra (2) Qi Lei (2) Frank Hutter (1) André Biedenkapp (1) Baohe Zhang (1) Luis Pineda (1) Nathan Lambert (1) Raghu Rajan (1) Rowan McAllister (1)

Research topics

Machine Learning (3) Reinforcement Learning (3) Artificial Intelligence (2) Applications (2) Learning Paradigms (2) Learning Types (2) Methods (2) Bayesian & Probabilistic (1) Core AI (1) Core Methods (1) Optimization & Theory (1)

Keywords

model-based reinforcement learning (2) sample efficiency (2) representation learning (1) state abstraction (1) few-shot learning (1) hyperparameter optimization (1) neural network optimization (1) dynamics modeling (1) hierarchical reinforcement learning (1) gradient descent (1) temporal abstraction (1) regret bound (1) meta-reinforcement learning (1) planning algorithm (1) data efficiency (1) uncertainty propagation (1) trajectory sampling (1) neural network (1) automatic hyperparameter tuning (1) latent hierarchy (1)

Papers

Provable Hierarchy-Based Meta-Reinforcement Learning AISTATS 2023 How Fine-Tuning Allows for Effective Meta-Learning NeurIPS 2021 On the Importance of Hyperparameter Optimization for Model-based Reinforcement Learning AISTATS 2021 Deep Reinforcement Learning in a Handful of Trials using Probabilistic Dynamics Models NeurIPS 2018