← Authors

Joelle Pineau

79 papers · 2000–2024 · 16 conferences · across top CS/AI conferences

Achievements

🐝 Cross-Pollinator (8) 🌈 Renaissance Researcher (8) 🧭 Keyword Pioneer 🌍 Conference Polyglot (16) 🐣 Hot Topic Early Bird πŸ—ΊοΈ Taxonomy Completionist (39) πŸŒ‰ Interdisciplinary Bridge πŸƒ Academic Marathon (24) 🌟 Keyword Trendsetter Combo (5) 🌱 Topic Pioneer πŸ‘‘ Triple Crown πŸ”¬ Deep Specialist (11) 🧬 Topic Evolution πŸ† Keyword Champion πŸ† Grand Slam πŸ‘₯ Mega-Team (25) 🀝 Dynamic Duo (10) πŸ“ˆ Trend Setter πŸ”₯ Unstoppable (16) ⚑ Prolific Year (16) πŸ’Ž Century Club (79) πŸš€ Conference Pioneer πŸ—ƒοΈ 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

Doina Precup (10) Koustuv Sinha (9) Amy Zhang (8) Shagun Sodhani (7) Audrey Durand (7) Joshua Romoff (6) Vincent Francois-Lavet (5) William L. Hamilton (5) Adina Williams (5) Prasanna Parthasarathi (5)

Research topics

Robotics (1)

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