Joelle Pineau
79 papers · 2000–2024 · 16 conferences · across top CS/AI conferences
Achievements
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πΊοΈ Taxonomy Completionist (39) π§ Keyword Pioneer π Interdisciplinary Bridge π Renaissance Researcher (8) π£ Hot Topic Early Bird
πΊοΈ
Taxonomy Completionist
(39)
π
Interdisciplinary Bridge
π
Academic Marathon
(24)
π
Keyword Trendsetter Combo
(5)
π±
Topic Pioneer
π
Triple Crown
π¬
Deep Specialist
(11)
π§¬
Topic Evolution
π
Keyword Champion
π
Grand Slam
π₯
Mega-Team
(25)
π€
Dynamic Duo
(10)
π
Trend Setter
π₯
Unstoppable
(16)
β‘
Prolific Year
(16)
π
Century Club
(79)
π
Conference Pioneer
ποΈ
Keyword Collector
(130)
Conferences
NIPS (16)
ICML (14)
EMNLP (9)
AAAI (7)
ICLR (6)
JMLR (6)
ACL (4)
IJCAI (4)
CORL (2)
IJCNLP (2)
L4DC (2)
MLHC (2)
UAI (2)
AISTATS (1)
EACL (1)
RSS (1)
Top co-authors
Research topics
Keywords
reinforcement learning
(15)
representation learning
(7)
value function
(7)
policy learning
(6)
policy optimization
(5)
value function approximation
(4)
deep reinforcement learning
(4)
partial observability
(4)
multi-agent system
(4)
temporal difference learning
(3)
zero-shot learning
(3)
spatial invariance
(3)
model-based reinforcement learning
(3)
off-policy learning
(3)
imitation learning
(3)
markov decision process
(3)
partially observable markov decision process
(3)
sample efficiency
(2)
inductive reasoning
(2)
policy gradient
(2)
Papers
Position: On the Societal Impact of Open Foundation Models
ICML 2024
Piecewise Linear Parametrization of Policies: Towards Interpretable Deep Reinforcement Learning
ICLR 2024
New Insights on Reducing Abrupt Representation Change in Online Continual Learning
ICLR 2022
The Curious Case of Absolute Position Embeddings
EMNLP 2022
Improving Passage Retrieval with Zero-Shot Question Generation
EMNLP 2022
Block Contextual MDPs for Continual Learning
L4DC 2022
Robust Policy Learning over Multiple Uncertainty Sets
ICML 2022
A Generalized Bootstrap Target for Value-Learning, Efficiently Combining Value and Feature Predictions
AAAI 2022
Masked Language Modeling and the Distributional Hypothesis: Order Word Matters Pre-training for Little
EMNLP 2021
UnNatural Language Inference
IJCNLP 2021
Multi-Objective SPIBB: Seldonian Offline Policy Improvement with Safety Constraints in Finite MDPs
NIPS 2021
Improving Sample Efficiency in Model-Free Reinforcement Learning from Images
AAAI 2021
UnNatural Language Inference
ACL 2021
Exploring the Limits of Few-Shot Link Prediction in Knowledge Graphs
EACL 2021
Multi-Task Reinforcement Learning with Context-based Representations
ICML 2021
Improving Reproducibility in Machine Learning Research(A Report from the NeurIPS 2019 Reproducibility Program)
JMLR 2021
Sometimes We Want Ungrammatical Translations
EMNLP 2021
Learning Robust State Abstractions for Hidden-Parameter Block MDPs
ICLR 2021
Regularized Inverse Reinforcement Learning
ICLR 2021
OptiDICE: Offline Policy Optimization via Stationary Distribution Correction Estimation
ICML 2021
Handling Black Swan Events in Deep Learning with Diversely Extrapolated Neural Networks
IJCAI 2020
Exploiting Spatial Invariance for Scalable Unsupervised Object Tracking
AAAI 2020
Online Learned Continual Compression with Adaptive Quantization Modules
ICML 2020
Stable Policy Optimization via Off-Policy Divergence Regularization
UAI 2020
Learning an Unreferenced Metric for Online Dialogue Evaluation
ACL 2020
Language GANs Falling Short
ICLR 2020
Novelty Search in Representational Space for Sample Efficient Exploration
NIPS 2020
Adversarial Soft Advantage Fitting: Imitation Learning without Policy Optimization
NIPS 2020
Interference and Generalization in Temporal Difference Learning
ICML 2020
Literature Mining for Incorporating Inductive Bias in Biomedical Prediction Tasks (Student Abstract)
AAAI 2020
Plan2Vec: Unsupervised Representation Learning by Latent Plans
L4DC 2020
Towards the Systematic Reporting of the Energy and Carbon Footprints of Machine Learning
JMLR 2020
Invariant Causal Prediction for Block MDPs
ICML 2020
Constrained Markov Decision Processes via Backward Value Functions
ICML 2020
On the interaction between supervision and self-play in emergent communication
ICLR 2020
On Overfitting and Asymptotic Bias in Batch Reinforcement Learning with Partial Observability (Extended Abstract)
IJCAI 2020
On-Line Adaptative Curriculum Learning for GANs
AAAI 2019
CLUTRR: A Diagnostic Benchmark for Inductive Reasoning from Text
IJCNLP 2019
Multitask Metric Learning: Theory and Algorithm
AISTATS 2019
CLUTRR: A Diagnostic Benchmark for Inductive Reasoning from Text
EMNLP 2019
Seeded self-play for language learning
EMNLP 2019
Separating value functions across time-scales
ICML 2019
TarMAC: Targeted Multi-Agent Communication
ICML 2019
No-Press Diplomacy: Modeling Multi-Agent Gameplay
NIPS 2019
Gossip-based Actor-Learner Architectures for Deep Reinforcement Learning
NIPS 2019
Randomized Value Functions via Multiplicative Normalizing Flows
UAI 2019
Leveraging exploration in off-policy algorithms via normalizing flows
CORL 2019
Spatially Invariant Unsupervised Object Detection with Convolutional Neural Networks
AAAI 2019
Combined Reinforcement Learning via Abstract Representations
AAAI 2019
Streaming kernel regression with provably adaptive mean, variance, and regularization
JMLR 2018
Temporal Regularization for Markov Decision Process
NIPS 2018
Reward Estimation for Variance Reduction in Deep Reinforcement Learning
CORL 2018
Extending Neural Generative Conversational Model using External Knowledge Sources
EMNLP 2018
Focused Hierarchical RNNs for Conditional Sequence Processing
ICML 2018
An Inference-Based Policy Gradient Method for Learning Options
ICML 2018
Contextual Bandits for Adapting Treatment in a Mouse Model of de Novo Carcinogenesis
MLHC 2018
Multitask Spectral Learning of Weighted Automata
NIPS 2017
Piecewise Latent Variables for Neural Variational Text Processing
EMNLP 2017
Towards an Automatic Turing Test: Learning to Evaluate Dialogue Responses
ACL 2017
Learning Robust Features using Deep Learning for Automatic Seizure Detection
MLHC 2016
Practical Kernel-Based Reinforcement Learning
JMLR 2016
How NOT To Evaluate Your Dialogue System: An Empirical Study of Unsupervised Evaluation Metrics for Dialogue Response Generation
EMNLP 2016
Generalized Dictionary for Multitask Learning with Boosting
IJCAI 2016
An Expectation-Maximization Algorithm to Compute a Stochastic Factorization From Data
IJCAI 2015
Methods of Moments for Learning Stochastic Languages: Unified Presentation and Empirical Comparison
ICML 2014
Efficient Learning and Planning with Compressed Predictive States
JMLR 2014
Modelling Sparse Dynamical Systems with Compressed Predictive State Representations
ICML 2013
Maximum Mean Discrepancy Imitation Learning
RSS 2013
Learning from Limited Demonstrations
NIPS 2013
Bellman Error Based Feature Generation using Random Projections on Sparse Spaces
NIPS 2013
On-line Reinforcement Learning Using Incremental Kernel-Based Stochastic Factorization
NIPS 2012
A Bayesian Approach for Learning and Planning in Partially Observable Markov Decision Processes
JMLR 2011
Reinforcement Learning using Kernel-Based Stochastic Factorization
NIPS 2011
PAC-Bayesian Model Selection for Reinforcement Learning
NIPS 2010
Manifold Embeddings for Model-Based Reinforcement Learning under Partial Observability
NIPS 2009
MDPs with Non-Deterministic Policies
NIPS 2008
Bayes-Adaptive POMDPs
NIPS 2007
Theoretical Analysis of Heuristic Search Methods for Online POMDPs
NIPS 2007
Spoken Dialogue Management Using Probabilistic Reasoning
ACL 2000