Andrea Zanette
18 papers · 2018–2025 · 4 venues · across top CS/AI venues
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Achievements
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πΊοΈ Taxonomy Completionist (26) π Academic Marathon Β· Sprint π Conference Polyglot Β· Bronze π Interdisciplinary Bridge Β· Silver π£ Hot Topic Early Bird
π¬
Deep Specialist
(10)
π
Keyword Champion
(3)
β
The Questioner
π₯
Unstoppable Β· Bronze
ποΈ
Keyword Collector
(78)
π
Century Club Β· Bronze
Venues
Top co-authors
Research topics
Machine Learning
(16)
Reinforcement Learning
(14)
Methods
(14)
Optimization & Theory
(13)
Learning Types Β· Machine Learning
(9)
Artificial Intelligence
(7)
Core AI
(6)
Natural Language Processing
(3)
Resources & Methods
(2)
Deep Learning
(1)
Application Areas
(1)
Applications
(1)
Generation
(1)
Learning Paradigms
(1)
Learning Types Β· Deep Learning
(1)
Keywords
regret bound
(5)
function approximation
(5)
reinforcement learning
(5)
sample complexity
(5)
linear function approximation
(4)
markov decision process
(4)
bellman operator
(3)
value iteration
(3)
batch learning
(2)
offline reinforcement learning
(2)
contextual bandit
(2)
reward model
(2)
online learning
(2)
bellman error
(2)
policy optimization
(2)
linear methods
(1)
value function
(1)
model misspecification
(1)
bellman residual
(1)
policy learning
(1)
Papers
Accelerating Unbiased LLM Evaluation via Synthetic Feedback
ICML 2025
ArCHer: Training Language Model Agents via Hierarchical Multi-Turn RL
ICML 2024
Fast Best-of-N Decoding via Speculative Rejection
NeurIPS 2024
Policy Finetuning in Reinforcement Learning via Design of Experiments using Offline Data
NeurIPS 2023
When is Realizability Sufficient for Off-Policy Reinforcement Learning?
ICML 2023
Bellman Residual Orthogonalization for Offline Reinforcement Learning
NeurIPS 2022
Stabilizing Q-learning with Linear Architectures for Provable Efficient Learning
ICML 2022
Cautiously Optimistic Policy Optimization and Exploration with Linear Function Approximation
COLT 2021
Design of Experiments for Stochastic Contextual Linear Bandits
NeurIPS 2021
Exponential Lower Bounds for Batch Reinforcement Learning: Batch RL can be Exponentially Harder than Online RL
ICML 2021
Provable Benefits of Actor-Critic Methods for Offline Reinforcement Learning
NeurIPS 2021
Frequentist Regret Bounds for Randomized Least-Squares Value Iteration
AISTATS 2020
Learning Near Optimal Policies with Low Inherent Bellman Error
ICML 2020
Provably Efficient Reward-Agnostic Navigation with Linear Value Iteration
NeurIPS 2020
Almost Horizon-Free Structure-Aware Best Policy Identification with a Generative Model
NeurIPS 2019
Limiting Extrapolation in Linear Approximate Value Iteration
NeurIPS 2019
Tighter Problem-Dependent Regret Bounds in Reinforcement Learning without Domain Knowledge using Value Function Bounds
ICML 2019
Problem Dependent Reinforcement Learning Bounds Which Can Identify Bandit Structure in MDPs
ICML 2018