Joëlle Pineau

Q: What Schools Are Affiliated With Joëlle Pineau

Joëlle Pineau is affiliated with the following schools: McGill University, University of Waterloo, Carnegie Mellon University

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Joëlle Pineau

Computer Science

#1146

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#1186

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Machine Learning

#102

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#103

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Artificial Intelligence

#222

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#227

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#2610

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#2732

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Computer Science

Joëlle Pineau's Degrees

Bachelors Computer Science McGill University

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Why Is Joëlle Pineau Influential?

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According to Wikipedia, Joëlle Pineau is a Canadian computer scientist and associate professor at McGill University. She is the lead of Facebook's Artificial Intelligence Research lab in Montreal, Quebec. Early life and education Pineau was born in 1974 in Ottawa, Ontario. She played the viola in the Ottawa Symphony Orchestra. She eventually studied engineering at the University of Waterloo. She completed her postgraduate education in robotics at Carnegie Mellon University in 2004. A chapter of Pineau's Masters thesis, Point-based value iteration: An anytime algorithm for POMDPs, has been published and cited almost 1,000 times. Her doctoral thesis, Tractable Planning Under Uncertainty: Exploiting Structure, was supervised by Sebastian Thrun and Geoff Gordon.

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Joëlle Pineau's Published Works

Number of citations in a given year to any of this author's works

Total number of citations to an author for the works they published in a given year. This highlights publication of the most important work(s) by the author

Published Works

Building End-To-End Dialogue Systems Using Generative Hierarchical Neural Network Models (2015) (1590)
Deep Reinforcement Learning that Matters (2017) (1423)
Point-based value iteration: An anytime algorithm for POMDPs (2003) (1120)
How NOT To Evaluate Your Dialogue System: An Empirical Study of Unsupervised Evaluation Metrics for Dialogue Response Generation (2016) (1055)
A Hierarchical Latent Variable Encoder-Decoder Model for Generating Dialogues (2016) (991)
The Ubuntu Dialogue Corpus: A Large Dataset for Research in Unstructured Multi-Turn Dialogue Systems (2015) (820)
An Introduction to Deep Reinforcement Learning (2018) (721)
Towards robotic assistants in nursing homes: Challenges and results (2003) (703)
Online Planning Algorithms for POMDPs (2008) (542)
An Actor-Critic Algorithm for Sequence Prediction (2016) (534)
A survey of point-based POMDP solvers (2013) (392)
Anytime Point-Based Approximations for Large POMDPs (2006) (388)
Pearl: A Mobile Robotic Assistant for the Elderly (2002) (378)
Experiences with a mobile robotic guide for the elderly (2002) (351)
Bayesian Reinforcement Learning: A Survey (2015) (338)
Spoken Dialogue Management Using Probabilistic Reasoning (2000) (333)
Towards an Automatic Turing Test: Learning to Evaluate Dialogue Responses (2017) (308)
A Survey of Available Corpora for Building Data-Driven Dialogue Systems (2015) (307)
Towards Personal Service Robots for the Elderly (1999) (304)
The Second Conversational Intelligence Challenge (ConvAI2) (2019) (250)
Conditional Computation in Neural Networks for faster models (2015) (244)
Learning Robust Features using Deep Learning for Automatic Seizure Detection (2016) (243)
Improving Sample Efficiency in Model-Free Reinforcement Learning from Images (2019) (237)
TarMAC: Targeted Multi-Agent Communication (2018) (208)
A Deep Reinforcement Learning Chatbot (2017) (200)
Towards the Systematic Reporting of the Energy and Carbon Footprints of Machine Learning (2020) (198)
Socially Adaptive Path Planning in Human Environments Using Inverse Reinforcement Learning (2016) (191)
Hierarchical Neural Network Generative Models for Movie Dialogues (2015) (177)
Informing sequential clinical decision-making through reinforcement learning: an empirical study (2010) (175)
Transparency and reproducibility in artificial intelligence (2020) (167)
Language GANs Falling Short (2018) (164)
Improving Reproducibility in Machine Learning Research (A Report from the NeurIPS 2019 Reproducibility Program) (2020) (162)
Bayes-Adaptive POMDPs (2007) (153)
Training End-to-End Dialogue Systems with the Ubuntu Dialogue Corpus (2017) (147)
Person tracking and following with 2D laser scanners (2015) (144)
A Dissection of Overfitting and Generalization in Continuous Reinforcement Learning (2018) (136)
Implementation of donor screening for infectious agents transmitted by blood by nucleic acid technology: update to 2003 (2005) (134)
A Bayesian Approach for Learning and Planning in Partially Observable Markov Decision Processes (2011) (131)
Bootstrapping Dialog Systems with Word Embeddings (2014) (127)
Benchmarking Batch Deep Reinforcement Learning Algorithms (2019) (126)
Masked Language Modeling and the Distributional Hypothesis: Order Word Matters Pre-training for Little (2021) (126)
Spatially Invariant Unsupervised Object Detection with Convolutional Neural Networks (2019) (125)
End-to-End Text Recognition with Hybrid HMM Maxout Models (2013) (119)
Wikispeedia: An Online Game for Inferring Semantic Distances between Concepts (2009) (116)
Bayesian posterior sampling via stochastic gradient Fisher scoring Bayesian Posterior Sampling via Stochastic Gradient Fisher Scoring (2012) (108)
Reinforcement learning with limited reinforcement: using Bayes risk for active learning in POMDPs (2008) (106)
Online Bagging and Boosting for Imbalanced Data Streams (2013) (105)
On the Pitfalls of Measuring Emergent Communication (2019) (101)
CLUTRR: A Diagnostic Benchmark for Inductive Reasoning from Text (2019) (101)
Learning from Limited Demonstrations (2013) (100)
Ethical Challenges in Data-Driven Dialogue Systems (2017) (98)
Adaptive Treatment of Epilepsy via Batch-mode Reinforcement Learning (2008) (97)
A Hierarchical Approach to POMDP Planning and Execution (2004) (90)
Generative Deep Neural Networks for Dialogue: A Short Review (2016) (86)
Active Learning in Partially Observable Markov Decision Processes (2005) (82)
Combined Reinforcement Learning via Abstract Representations (2018) (75)
Tractable planning under uncertainty: exploiting structure (2004) (75)
Policy-contingent abstraction for robust robot control (2002) (74)
Bayesian reinforcement learning in continuous POMDPs with application to robot navigation (2008) (72)
Invariant Causal Prediction for Block MDPs (2020) (70)
Time Series Analysis Using Geometric Template Matching (2013) (70)
Independently Controllable Factors (2017) (67)
Contextual Bandits for Adapting Treatment in a Mouse Model of de Novo Carcinogenesis (2018) (64)
Extending Neural Generative Conversational Model using External Knowledge Sources (2018) (63)
On the Evaluation of Dialogue Systems with Next Utterance Classification (2016) (62)
OptionGAN: Learning Joint Reward-Policy Options using Generative Adversarial Inverse Reinforcement Learning (2017) (62)
Multi-Task Reinforcement Learning with Context-based Representations (2021) (62)
Independently Controllable Features (2017) (61)
Decoupling Dynamics and Reward for Transfer Learning (2018) (60)
Treating Epilepsy via Adaptive Neurostimulation: a Reinforcement Learning Approach (2009) (59)
Model-Based Bayesian Reinforcement Learning in Large Structured Domains (2008) (58)
Natural Environment Benchmarks for Reinforcement Learning (2018) (56)
Constructing evidence-based treatment strategies using methods from computer science. (2007) (55)
Disentangling the independently controllable factors of variation by interacting with the world (2018) (53)
Learning an Unreferenced Metric for Online Dialogue Evaluation (2020) (52)
SmartWheeler: A Robotic Wheelchair Test-Bed for Investigating New Models of Human-Robot Interaction (2007) (52)
Design and validation of an intelligent wheelchair towards a clinically-functional outcome (2013) (51)
Exploiting Spatial Invariance for Scalable Unsupervised Object Tracking (2019) (50)
An integrated approach to hierarchy and abstraction for pomdps (2002) (50)
POMDP Planning for Robust Robot Control (2005) (50)
Maximum Mean Discrepancy Imitation Learning (2013) (48)
Spoken Dialog Management for Robots (2000) (48)
Machine Learning for COVID-19 needs global collaboration and data-sharing (2020) (47)
Exploring Powered Wheelchair Users and Their Caregivers’ Perspectives on Potential Intelligent Power Wheelchair Use: A Qualitative Study (2014) (45)
UnNatural Language Inference (2020) (44)
Online Learned Continual Compression with Adaptive Quantization Modules (2019) (44)
On the interaction between supervision and self-play in emergent communication (2020) (42)
High-level robot behavior control using POMDPs (2002) (41)
Reinforcement Learning using Kernel-Based Stochastic Factorization (2011) (41)
Methods of Moments for Learning Stochastic Languages: Unified Presentation and Empirical Comparison (2014) (41)
COVID-19 Prognosis via Self-Supervised Representation Learning and Multi-Image Prediction (2021) (40)
Engagement and learning in simulation: recommendations of the Simnovate Engaged Learning Domain Group (2017) (40)
Modelling Sparse Dynamical Systems with Compressed Predictive State Representations (2013) (40)
Leveraging exploration in off-policy algorithms via normalizing flows (2019) (39)
Efficient learning and planning with compressed predictive states (2013) (39)
When AIs Outperform Doctors: Confronting the Challenges of a Tort-Induced Over-Reliance on Machine Learning (2019) (39)
Simultaneous Machine Translation using Deep Reinforcement Learning (2016) (39)
Development and Validation of a Robust Speech Interface for Improved Human-Robot Interaction (2009) (39)
Online Boosting Algorithms for Anytime Transfer and Multitask Learning (2015) (38)
Development of a polygenic risk score to improve screening for fracture risk: A genetic risk prediction study (2020) (36)
Learning Causal State Representations of Partially Observable Environments (2019) (35)
Practical Kernel-Based Reinforcement Learning (2014) (35)
Deep Generative Modeling of LiDAR Data (2018) (34)
Interference and Generalization in Temporal Difference Learning (2020) (34)
New Insights on Reducing Abrupt Representation Change in Online Continual Learning (2021) (34)
Online Adaptative Curriculum Learning for GANs (2018) (33)
Streaming kernel regression with provably adaptive mean, variance, and regularization (2017) (33)
OptiDICE: Offline Policy Optimization via Stationary Distribution Correction Estimation (2021) (33)
Incorporating Unstructured Textual Knowledge Sources into Neural Dialogue Systems (2015) (32)
Piecewise Latent Variables for Neural Variational Text Processing (2016) (32)
On the Feasibility of Using a Standardized Test for Evaluating a Speech-Controlled Smart Wheelchair (2011) (31)
Randomized Value Functions via Multiplicative Normalizing Flows (2018) (31)
Compressed Least-Squares Regression on Sparse Spaces (2012) (31)
No Press Diplomacy: Modeling Multi-Agent Gameplay (2019) (31)
Constrained Markov Decision Processes via Backward Value Functions (2020) (30)
An Inference-Based Policy Gradient Method for Learning Options (2018) (30)
Fast reinforcement learning of dialog strategies (2000) (29)
PAC-Bayesian Model Selection for Reinforcement Learning (2010) (29)
Completing wikipedia's hyperlink structure through dimensionality reduction (2009) (28)
The potential impact of intelligent power wheelchair use on social participation: perspectives of users, caregivers and clinicians (2015) (27)
Theoretical Analysis of Heuristic Search Methods for Online POMDPs (2007) (27)
RRT-Plan: A Randomized Algorithm for STRIPS Planning (2006) (27)
PAC-Learning of Markov Models with Hidden State (2006) (27)
Reward Estimation for Variance Reduction in Deep Reinforcement Learning (2018) (27)
A formal framework for robot learning and control under model uncertainty (2007) (26)
Novelty Search in representational space for sample efficient exploration (2020) (26)
A multiple imputation strategy for sequential multiple assignment randomized trials. (2017) (26)
Differences in the Evacuation Behaviour of Office and Apartment Building Occupants (1996) (26)
MVFST-RL: An Asynchronous RL Framework for Congestion Control with Delayed Actions (2019) (26)
A bayesian reinforcement learning approach for customizing human-robot interfaces (2009) (25)
Bayesian reinforcement learning for POMDP-based dialogue systems (2011) (25)
Adaptive control of epileptiform excitability in an in vitro model of limbic seizures (2013) (24)
Focused Hierarchical RNNs for Conditional Sequence Processing (2018) (24)
Non-Deterministic Policies in Markovian Decision Processes (2014) (23)
Learning Robust State Abstractions for Hidden-Parameter Block MDPs (2021) (23)
RapidBrachyDL: Rapid Radiation Dose Calculations in Brachytherapy via Deep Learning. (2020) (23)
Separating value functions across time-scales (2019) (22)
Plan2Vec: Unsupervised Representation Learning by Latent Plans (2020) (22)
Where Did My Optimum Go?: An Empirical Analysis of Gradient Descent Optimization in Policy Gradient Methods (2018) (22)
The Bottleneck Simulator: A Model-based Deep Reinforcement Learning Approach (2018) (21)
Improving Passage Retrieval with Zero-Shot Question Generation (2022) (21)
Generalized Dictionary for Multitask Learning with Boosting (2016) (21)
The importance of transparency and reproducibility in artificial intelligence research (2020) (20)
Evaluating Logical Generalization in Graph Neural Networks (2020) (20)
Manifold Embeddings for Model-Based Reinforcement Learning under Partial Observability (2009) (19)
On-line Reinforcement Learning Using Incremental Kernel-Based Stochastic Factorization (2012) (19)
RE-EVALUATE: Reproducibility in Evaluating Reinforcement Learning Algorithms (2018) (19)
A Bayesian Method for Learning POMDP Observation Parameters for Robot Interaction Management Systems (2010) (19)
Gossip-based Actor-Learner Architectures for Deep Reinforcement Learning (2019) (19)
A multiple imputation strategy for sequential multiple assignment randomized trials (2014) (18)
Tensor Regression Networks with various Low-Rank Tensor Approximations (2017) (18)
Variable resolution decomposition for robotic navigation under a POMDP framework (2010) (18)
A Decision-Theoretic Approach for the Collaborative Control of a Smart Wheelchair (2018) (18)
Adversarial Soft Advantage Fitting: Imitation Learning without Policy Optimization (2020) (17)
Multitask Metric Learning: Theory and Algorithm (2019) (17)
Multi-modal Variational Encoder-Decoders (2017) (16)
Building Adaptive Dialogue Systems Via Bayes-Adaptive POMDPs (2012) (15)
Bellman Error Based Feature Generation using Random Projections on Sparse Spaces (2012) (15)
Policy Iteration Based on Stochastic Factorization (2014) (15)
Multi-tasking SLAM (2010) (15)
Proceedings of the 29th International Conference on Machine Learning (ICML-12) (2012) (15)
Model-Invariant State Abstractions for Model-Based Reinforcement Learning (2021) (14)
Domain Adversarial Reinforcement Learning (2021) (14)
Temporal Regularization in Markov Decision Process (2018) (14)
Representing Systems with Hidden State (2006) (14)
Automated Personalized Feedback Improves Learning Gains in An Intelligent Tutoring System (2020) (13)
Attraction-Repulsion Actor-Critic for Continuous Control Reinforcement Learning (2019) (13)
Active Learning for Developing Personalized Treatment (2011) (13)
A bistable computational model of recurring epileptiform activity as observed in rodent slice preparations (2011) (13)
A Variance Analysis for POMDP Policy Evaluation (2008) (13)
Efficient Planning and Tracking in POMDPs with Large Observation Spaces (2006) (13)
Reducing Representation Drift in Online Continual Learning (2021) (12)
SPeCiaL: Self-Supervised Pretraining for Continual Learning (2021) (12)
Mobility profile and wheelchair driving skills of powered wheelchair users: Sensor-based event recognition using a support vector machine classifier (2011) (12)
A Deep Reinforcement Learning Chatbot (Short Version) (2018) (12)
Quasi-Equivalence Discovery for Zero-Shot Emergent Communication (2021) (12)
Automatically suggesting topics for augmenting text documents (2010) (11)
Active learning for personalizing treatment (2011) (11)
Stable Policy Optimization via Off-Policy Divergence Regularization (2020) (11)
Point-based approximations for fast POMDP solving (2006) (11)
Proceedings of the Twenty-Ninth International Conference on Machine Learning (2012) (10)
Hierarchical POMDP Decomposition for A Conversational Robot (2001) (10)
PAC-Bayesian Policy Evaluation for Reinforcement Learning (2011) (10)
Online Ensemble Learning for Imbalanced Data Streams (2013) (10)
Questions Are All You Need to Train a Dense Passage Retriever (2022) (10)
Machine Learning to Predict Osteoporotic Fracture Risk from Genotypes (2018) (10)
Block Contextual MDPs for Continual Learning (2021) (10)
Multi-Objective SPIBB: Seldonian Offline Policy Improvement with Safety Constraints in Finite MDPs (2021) (9)
Knowledge Transfer in Markov Decision Processes (2006) (9)
COVID-19 Deterioration Prediction via Self-Supervised Representation Learning and Multi-Image Prediction. (2021) (9)
A Large-Scale, Open-Domain, Mixed-Interface Dialogue-Based ITS for STEM (2020) (9)
Seeded self-play for language learning (2019) (9)
Automatic Detection and Classification of Unsafe Events During Power Wheelchair Use (2014) (9)
Automated Data-Driven Generation of Personalized Pedagogical Interventions in Intelligent Tutoring Systems (2021) (9)
Exploring Zero-Shot Emergent Communication in Embodied Multi-Agent Populations (2020) (9)
NeurIPS 2019 Reproducibility Challenge (2020) (8)
Applying Metric-Trees to Belief-Point POMDPs (2003) (8)
Goal-Directed Online Learning of Predictive Models (2011) (8)
ACtuAL: Actor-Critic Under Adversarial Learning (2017) (8)
Mixed Observability Predictive State Representations (2013) (8)
Learning to learn to communicate (2019) (8)
Multitask Spectral Learning of Weighted Automata (2017) (8)
Information Gathering and Reward Exploitation of Subgoals for POMDPs (2015) (7)
MACA: A Modular Architecture for Conversational Agents (2017) (7)
Planning under uncertainty in robotics (2006) (7)
Modeling Glucagon Action in Patients With Type 1 Diabetes (2017) (7)
Probablistic Control of Human Robot Interaction : Experiments with A Robotic Assistant for Nursing Homes (2003) (7)
Incremental Stochastic Factorization for Online Reinforcement Learning (2016) (7)
Bayes-Adaptive POMDPs: A New Perspective on the Explore-Exploit Tradeoff in Partially Observable Domains (2008) (6)
An Empirical Analysis of Off-policy Learning in Discrete MDPs (2012) (6)
Intervention Design for Effective Sim2Real Transfer (2020) (6)
MDPs with Non-Deterministic Policies (2008) (6)
Multitask Generalized Eigenvalue Program (2016) (6)
Efficient Continual Learning Ensembles in Neural Network Subspaces (2022) (5)
Laser-based Person Tracking for Clinical Locomotion Analysis (2014) (5)
Automatically characterizing driving activities onboard smart wheelchairs from accelerometer data (2015) (5)
Predicting Success in Goal-Driven Human-Human Dialogues (2017) (5)
Circulating proteins to predict adverse COVID-19 outcomes (2021) (5)
On the Use of Modular Software and Hardware for Designing Wheelchair Robots (2016) (5)
Correcting Momentum in Temporal Difference Learning (2021) (5)
Learning time series models for pedestrian motion prediction (2016) (5)
Sometimes We Want Translationese (2021) (5)
Online Learned Continual Compression with Stacked Quantization Module (2019) (5)
When AIs Outperform Doctors : The dangers of a tort-induced over-reliance on machine learning and what ( not ) to do about it (2018) (5)
Scalable Multi-Agent Inverse Reinforcement Learning via Actor-Attention-Critic (2020) (5)
On the Design and Validation of an Intelligent Powered Wheelchair: Lessons from the SmartWheeler Project (2010) (4)
A Framework for Computing Bounds for the Return of a Policy (2011) (4)
Design and Evaluation of a Flexible Interface for Spatial Navigation (2012) (4)
Building reproducible, reusable, and robust machine learning software (2020) (4)
Towards a standardized test for intelligent wheelchairs (2010) (4)
Sometimes We Want Ungrammatical Translations (2021) (4)
Handling Black Swan Events in Deep Learning with Diversely Extrapolated Neural Networks (2020) (4)
Regularized Inverse Reinforcement Learning (2020) (4)
Designing Intelligent Wheelchairs: Reintegrating AI (2013) (4)
valuation des rgulateurs de dbit passifs utiliss pour la perfusion intraveineuse (2009) (4)
How To Evaluate Your Dialogue System: Probe Tasks as an Alternative for Token-level Evaluation Metrics (2020) (4)
The Curious Case of Absolute Position Embeddings (2022) (4)
Evidence-based modeling of network discharge dynamics during periodic pacing to control epileptiform activity (2012) (3)
Democratising the Digital Revolution: The Role of Data Governance (2021) (3)
Estimating People's Subjective Experiences of Robot Behavior (2014) (3)
Multi-Task Reinforcement Learning as a Hidden-Parameter Block MDP (2020) (3)
Chapter 16: Practical reinforcement learning in dynamic treatment regimes (2015) (3)
Probabilistic robot planning under model uncertainty : an active learning approach (2005) (3)
Recurrent Boosting for Classification of Natural and Synthetic Time-Series Data (2007) (3)
Lifelong Learning of Discriminative Representations (2014) (3)
Recurrent Value Functions (2019) (3)
Adaptive Treatment Allocation Using Sub-Sampled Gaussian Processes (2015) (3)
Exploring the Limits of Few-Shot Link Prediction in Knowledge Graphs (2021) (3)
The Duality of State and Observation in Probabilistic Transition Systems (2011) (3)
Rephrasing the Problem of Robotic Social Navigation (2014) (3)
An Actor-Critic Algorithm for Structured Prediction (2016) (3)
Robust Policy Learning over Multiple Uncertainty Sets (2022) (3)
Apprentissage actif dans les processus décisionnels de Markov partiellement observables L'algorithme MEDUSA (2007) (2)
Manifold Embeddings for Model-Based Reinforcement Learning of Neurostimulation Policies (2009) (2)
A Study of Off-policy Learning in Computational Sustainability (2012) (2)
An Expectation-Maximization Algorithm to Compute a Stochastic Factorization From Data (2015) (2)
TDprop: Does Jacobi Preconditioning Help Temporal Difference Learning? (2020) (2)
Estimating causal effects with optimization-based methods: A review and empirical comparison (2022) (2)
Reinforcement Learning Competition : Helicopter Hovering with Controllability and Kernel-Based Stochastic Factorization (2013) (2)
The Duality of State and Observations (2007) (2)
Design and validation of an intelligent wheelchair towards a clinically-functional outcome (2013) (1)
Representation of Reinforcement Learning Policies in Reproducing Kernel Hilbert Spaces. (2020) (1)
Overcoming missing data in a sequential , multiple assignment , randomized clinical trial of patients with schizophrenia (1)
Recurrent Boosting Method for Time-Dependent Classification of Epileptiform Signals (2006) (1)
A Decision-Theoretic Approach for the Collaborative Control of a Smart Wheelchair (2017) (1)
Least-Squares Regression on Sparse Spaces (2011) (1)
Biomedical Research and Informatics Living Laboratory for Innovative Advances of New Technologies in Community Mobility Rehabilitation: Protocol for Evaluation and Rehabilitation of Mobility Across Continuums of Care (2022) (1)
Missteps in Robot Social Navigation (2015) (1)
Provably efficient reconstruction of policy networks (2020) (1)
Treating Epilepsy by Reinforcement Learning Via Manifold-Based Simulation (2010) (1)
Compositional Language Understanding with Text-based Relational Reasoning (2018) (1)
LSTD on Sparse Spaces (2011) (1)
Deep interpretability for GWAS (2020) (1)
Representation as a Service (2014) (1)
Machine Learning for COVID-19 needs global collaboration and data-sharing (2020) (1)
Convex Optimization: Algorithms and Complexity (2015) (1)
Learning Algorithms for Automata with Observations (2007) (1)
Analyzing Open Data from the City of Montreal (2015) (1)
Approximate Policy Iteration with Demonstration Data (2013) (1)
Separable value functions across time-scales (2019) (0)
Towards Emerging Nonverbal Communication Protocols for Multi-Robot Populations (2010) (0)
Assessing Generalization in TD methods for Deep Reinforcement Learning (2019) (0)
Improvement in Large POMDPs via an Error Minimization Search (2007) (0)
Robotic Assistance During Ambulation by Older Adults (2002) (0)
MODEL-BASED REINFORCEMENT LEARNING (2021) (0)
Automatic Seizure Detection in an In-Vivo Model of Epilepsy (2011) (0)
Chapter 11: Imputing missing data from sequential multiple assignment randomized trials (2015) (0)
Model-based Bayesian Reinforcement Learning with Tree-based State Aggregation (2008) (0)
Policy-contingent state abstraction for hierarchical MDPs (2002) (0)
Contact RingDoorBell GotoPatientRoom Move GuidetoPhysio CheckUserPresent TerminateGuidance ConfirmGuidetoPhysio Assist Act Remind RemindPhysioAppt RemindVitamin Rest Recharge (2007) (0)
Àààööö Blockin Blockin Blockinð Ôôöóó Øó Èçååè Èððòòòòò Òò Üü Blockinùøøóò (2007) (0)
Circulating proteins to predict COVID-19 severity. (2023) (0)
Machine Learning to Automate Clinician Designed Empirical Manual for Congenital Heart Disease Identification in Large Claims Database (0)
Literature Mining for Incorporating Inductive Bias in Biomedical Prediction Tasks (Student Abstract) (2020) (0)
Piecewise Latent Variables for Neural Variational Text Processing (2017) (0)
A Generalized Bootstrap Target for Value-Learning, Efficiently Combining Value and Feature Predictions (2022) (0)
UvA-DARE ( Digital Academic Repository ) Bayesian posterior sampling via stochastic gradient (2012) (0)
Do Encoder Representations of Generative Dialogue Models have sufficient summary of the Information about the task ? (2021) (0)
2017 Formatting Instructions for Authors Using LaTeX (2017) (0)
The RLLChatbot: a solution to the ConvAI challenge (2018) (0)
Learning and Discovery in Dynamical Systems with Hidden State (2007) (0)
Multitask Metric Learning : Theory and Algorithm 1 Generalization Bound of Multitask Metric Learning (2019) (0)
Abstraction in Reinforcement Learning Situation Dependent Spatial Abstraction in Reinforcement Learning Based on Structural Knowledge . . . . . . . . . . . . . . . . . 12 Improving Bayesian Reinforcement Learning Using Transition Abstraction (2009) (0)
Socially Adaptive Path Planning in Human Environments Using Inverse Reinforcement Learning (2015) (0)
Improving the Design and Discovery of Dynamic Treatment Strategies Using Recent Results in Sequential Decision-Making (2015) (0)
AAAI 2008 Workshop Reports (2009) (0)
Conference Organizing Committee (2021) (0)
Optimizing Treatment Strategies for Epilepsy Using Reinforcement Learning (2008) (0)
A Sparse Probabilistic Model of User Preference Data (2017) (0)
Prévalence des anomalies dysimmunitaires biologiques et des cryoglobulines chez les patients infectés par le VIH. Étude transversale chez 97 patients (2002) (0)
Sequential Coordination of Deep Models for Learning Visual Arithmetic (2018) (0)
Model-based Bayesian Reinforcement Learning with Adaptive State Aggregation (2009) (0)
Genomic Prediction of Osteoporosis Using 426,000 Individuals from UK Biobank (2018) (0)
Low-Rank Representation of Reinforcement Learning Policies (2022) (0)
Hierarchical Methods for Planning under Uncertainty (2001) (0)
Adversarial Gain (2018) (0)
Set-up of a Decentralized Automated Dispensing System in a Medical Resuscitation Unit (2001) (0)
Do Encoder Representations of Generative Dialogue Models Encode Sufficient Information about the Task ? (2021) (0)
A survey of point-based POMDP solvers (2012) (0)
A Brief Study on the Effects of Training Generative Dialogue Models with a Semantic loss (2021) (0)
TDprop: Does Adaptive Optimization With Jacobi Preconditioning Help Temporal Difference Learning? (2021) (0)
Data-Driven Dialogue Systems: Models, Algorithms, Evaluation, and Ethical Challenges (2018) (0)
HIDDEN-PARAMETER BLOCK MDPS (2021) (0)

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