Audrey Durand
16 papers · 2018–2026 · 10 venues · across top CS/AI venues
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Achievements
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πΊοΈ Taxonomy Completionist (46) π Academic Marathon Β· Sprint π Conference Polyglot Β· Gold π Interdisciplinary Bridge Β· Silver π£ Hot Topic Early Bird
ποΈ
Keyword Collector
(92)
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Renaissance Researcher
(7)
π₯
Unstoppable Β· Bronze
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Conference Pioneer
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Century Club Β· Bronze
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Trend Setter
Venues
Top co-authors
Research topics
Machine Learning
(16)
Learning Types Β· Machine Learning
(12)
Optimization & Theory
(8)
Deep Learning
(7)
Artificial Intelligence
(5)
Learning Types Β· Deep Learning
(5)
Mathematics & Optimization
(4)
Optimization
(4)
Architectures
(3)
Core AI
(3)
Core Methods
(3)
Healthcare & Medicine
(2)
Reinforcement Learning
(2)
Application Areas
(2)
Applications
(2)
Keywords
reinforcement learning
(3)
active learning
(2)
partial monitoring
(2)
upper confidence bound
(2)
markov decision process
(2)
cost-sensitive learning
(2)
multi-armed bandit
(2)
regret bound
(2)
confidence bound
(2)
imitation learning
(1)
knowledge transfer
(1)
uncertainty quantification
(1)
data augmentation
(1)
incremental learning
(1)
online learning
(1)
regret analysis
(1)
curriculum learning
(1)
discount factor
(1)
classification
(1)
exploration-exploitation tradeoff
(1)
Papers
Active Learning with Non-Uniform Costs for African Natural Language Processing
EACL 2026
On Shallow Planning Under Partial Observability
AAAI 2025
Neural Active Learning Meets the Partial Monitoring Framework
UAI 2024
Randomized Confidence Bounds for Stochastic Partial Monitoring
ICML 2024
Erratum: Risk Bounds for the Majority Vote: From a PAC-Bayesian Analysis to a Learning Algorithm
JMLR 2023
Latent Space Evolution under Incremental Learning with Concept Drift (Student Abstract)
AAAI 2023
Annotation Cost-Sensitive Deep Active Learning with Limited Data (Student Abstract)
AAAI 2022
Handling Black Swan Events in Deep Learning with Diversely Extrapolated Neural Networks
IJCAI 2020
Literature Mining for Incorporating Inductive Bias in Biomedical Prediction Tasks (Student Abstract)
AAAI 2020
Old Dog Learns New Tricks: Randomized UCB for Bandit Problems
AISTATS 2020
Leveraging exploration in off-policy algorithms via normalizing flows
CoRL 2019
Leveraging Observations in Bandits: Between Risks and Benefits
AAAI 2019
On-Line Adaptative Curriculum Learning for GANs
AAAI 2019
Contextual Bandits for Adapting Treatment in a Mouse Model of de Novo Carcinogenesis
MLHC 2018
Streaming kernel regression with provably adaptive mean, variance, and regularization
JMLR 2018
Temporal Regularization for Markov Decision Process
NeurIPS 2018