Doina Precup

Q: What Schools Are Affiliated With Doina Precup

Doina Precup is affiliated with the following schools: Technical University of Cluj-Napoca, McGill University, University of Massachusetts Amherst

Doina Precup's AcademicInfluence.com Rankings

Doina Precup

Computer Science

#1385

World Rank

#1433

Historical Rank

Artificial Intelligence

#261

World Rank

#266

Historical Rank

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Computer Science

Doina Precup's Degrees

PhD Computer Science University of Massachusetts Amherst
Bachelors Computer Science McGill University

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Why Is Doina Precup Influential?

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According to Wikipedia, Doina Precup is a Romanian researcher currently living in Montreal, Canada. She specializes in artificial intelligence . Precup is associate dean of research at the faculty of science at McGill University, Canada research chair in machine learning and a senior fellow at the Canadian Institute for Advanced Research. She also heads the Montreal office of Deepmind.

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Doina Precup'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

The Multimodal Brain Tumor Image Segmentation Benchmark (BRATS) (2015) (3526)
Between MDPs and Semi-MDPs: A Framework for Temporal Abstraction in Reinforcement Learning (1999) (3115)
Deep Reinforcement Learning that Matters (2017) (1423)
Off-Policy Deep Reinforcement Learning without Exploration (2018) (807)
The Option-Critic Architecture (2016) (736)
Eligibility Traces for Off-Policy Policy Evaluation (2000) (658)
Fast gradient-descent methods for temporal-difference learning with linear function approximation (2009) (584)
Horde: a scalable real-time architecture for learning knowledge from unsupervised sensorimotor interaction (2011) (459)
Off-Policy Temporal Difference Learning with Function Approximation (2001) (365)
Learning with Pseudo-Ensembles (2014) (362)
Learning Options in Reinforcement Learning (2002) (324)
Temporal abstraction in reinforcement learning (2000) (318)
Exploring Uncertainty Measures in Deep Networks for Multiple Sclerosis Lesion Detection and Segmentation (2018) (310)
Convergent Temporal-Difference Learning with Arbitrary Smooth Function Approximation (2009) (258)
Algorithms for multi-armed bandit problems (2014) (257)
Metrics for Finite Markov Decision Processes (2004) (256)
Conditional Computation in Neural Networks for faster models (2015) (244)
Reproducibility of Benchmarked Deep Reinforcement Learning Tasks for Continuous Control (2017) (208)
Reward is enough (2021) (191)
Automatic basis function construction for approximate dynamic programming and reinforcement learning (2006) (180)
An information-theoretic approach to curiosity-driven reinforcement learning (2012) (171)
Intra-Option Learning about Temporally Abstract Actions (1998) (164)
Activity and Gait Recognition with Time-Delay Embeddings (2010) (155)
Multi-time Models for Temporally Abstract Planning (1997) (143)
Theoretical Results on Reinforcement Learning with Temporally Abstract Options (1998) (135)
Wikispeedia: An Online Game for Inferring Semantic Distances between Concepts (2009) (116)
Sparse Distributed Memories for On-Line Value-Based Reinforcement Learning (2004) (115)
Classification of Normal and Hypoxic Fetuses From Systems Modeling of Intrapartum Cardiotocography (2010) (114)
Break the Ceiling: Stronger Multi-scale Deep Graph Convolutional Networks (2019) (109)
When Waiting is not an Option : Learning Options with a Deliberation Cost (2017) (109)
A Convergent Form of Approximate Policy Iteration (2002) (107)
Towards Continual Reinforcement Learning: A Review and Perspectives (2020) (105)
Gradient Starvation: A Learning Proclivity in Neural Networks (2020) (103)
Bisimulation Metrics for Continuous Markov Decision Processes (2011) (102)
Learning from Limited Demonstrations (2013) (100)
Active Learning in Partially Observable Markov Decision Processes (2005) (82)
Between MOPs and Semi-MOP: Learning, Planning & Representing Knowledge at Multiple Temporal Scales (1998) (78)
Methods for Computing State Similarity in Markov Decision Processes (2006) (78)
Bounding Performance Loss in Approximate MDP Homomorphisms (2008) (77)
Combined Reinforcement Learning via Abstract Representations (2018) (75)
Flow Network based Generative Models for Non-Iterative Diverse Candidate Generation (2021) (72)
Time Series Analysis Using Geometric Template Matching (2013) (70)
Invariant Causal Prediction for Block MDPs (2020) (70)
Independently Controllable Factors (2017) (67)
Learning to Schedule Straight-Line Code (1997) (67)
Fast reinforcement learning with generalized policy updates (2020) (67)
Algorithms for the multi-armed bandit problem (2000) (66)
The Option Keyboard: Combining Skills in Reinforcement Learning (2021) (65)
Using Options for Knowledge Transfer in Reinforcement Learning (1999) (63)
OptionGAN: Learning Joint Reward-Policy Options using Generative Adversarial Inverse Reinforcement Learning (2017) (62)
Independently Controllable Features (2017) (61)
Metrics for Markov Decision Processes with Infinite State Spaces (2005) (61)
Smart exploration in reinforcement learning using absolute temporal difference errors (2013) (60)
Hierarchical Probabilistic Gabor and MRF Segmentation of Brain Tumours in MRI Volumes (2013) (56)
Disentangling the independently controllable factors of variation by interacting with the world (2018) (53)
Multiple Kernel Learning-Based Transfer Regression for Electric Load Forecasting (2020) (51)
Reinforcement learning in the presence of rare events (2008) (50)
Resolving Event Coreference with Supervised Representation Learning and Clustering-Oriented Regularization (2018) (48)
Improved Switching among Temporally Abstract Actions (1998) (47)
Assessing the Predictability of Hospital Readmission Using Machine Learning (2013) (44)
Identification of the Dynamic Relationship Between Intrapartum Uterine Pressure and Fetal Heart Rate for Normal and Hypoxic Fetuses (2009) (44)
Data Generation as Sequential Decision Making (2015) (43)
Is Heterophily A Real Nightmare For Graph Neural Networks To Do Node Classification? (2021) (42)
Using Bisimulation for Policy Transfer in MDPs (2010) (42)
What can I do here? A Theory of Affordances in Reinforcement Learning (2020) (41)
Reinforcement Learning using Kernel-Based Stochastic Factorization (2011) (41)
Learning in non-stationary Partially Observable Markov Decision Processes (2005) (41)
Learnings Options End-to-End for Continuous Action Tasks (2017) (40)
Hindsight Credit Assignment (2019) (40)
The Termination Critic (2019) (40)
Iterative Multilevel MRF Leveraging Context and Voxel Information for Brain Tumour Segmentation in MRI (2014) (39)
Combining TD-learning with Cascade-correlation Networks (2003) (39)
Convergent Tree-Backup and Retrace with Function Approximation (2017) (39)
On the Expressivity of Markov Reward (2021) (39)
Constructive Function Approximation (1998) (39)
Learning Robust Options (2018) (39)
Activity Recognition with Mobile Phones (2011) (38)
Partial Model Completion in Model Driven Engineering using Constraint Logic Programming (2007) (38)
Optimal policy switching algorithms for reinforcement learning (2010) (37)
Using Finite Experiments to Study Asymptotic Performance (2000) (37)
Prediction of Disease Progression in Multiple Sclerosis Patients using Deep Learning Analysis of MRI Data (2019) (36)
A Survey of Exploration Methods in Reinforcement Learning (2021) (36)
Practical Kernel-Based Reinforcement Learning (2014) (35)
Connecting Weighted Automata and Recurrent Neural Networks through Spectral Learning (2018) (35)
Approximate Value Iteration with Temporally Extended Actions (2015) (34)
Redagent: winner of TAC SCM 2003 (2004) (34)
Interference and Generalization in Temporal Difference Learning (2020) (34)
Patterns of reintubation in extremely preterm infants: a longitudinal cohort study (2018) (33)
RedAgent-2003: an autonomous, market-based supply-chain management agent (2004) (32)
Prediction of extubation readiness in extreme preterm infants based on measures of cardiorespiratory variability (2012) (32)
Compressed Least-Squares Regression on Sparse Spaces (2012) (31)
The Impact of Time Interval between Extubation and Reintubation on Death or Bronchopulmonary Dysplasia in Extremely Preterm Infants (2019) (31)
Deep learning, reinforcement learning, and world models (2022) (31)
A new Q(lambda) with interim forward view and Monte Carlo equivalence (2014) (31)
Using Linear Programming for Bayesian Exploration in Markov Decision Processes (2007) (30)
Bisimulation Metrics are Optimal Value Functions (2014) (30)
Data Mining Using Relational Database Management Systems (2006) (29)
Real-Time Indoor Localization in Smart Homes Using Semi-Supervised Learning (2017) (29)
Prediction of Extubation readiness in extremely preterm infants by the automated analysis of cardiorespiratory behavior: study protocol (2017) (28)
Completing wikipedia's hyperlink structure through dimensionality reduction (2009) (28)
Differentially Private Policy Evaluation (2016) (27)
PAC-Learning of Markov Models with Hidden State (2006) (27)
Equivalence Relations in Fully and Partially Observable Markov Decision Processes (2009) (27)
Gifting in Multi-Agent Reinforcement Learning (2020) (27)
Value Preserving State-Action Abstractions (2020) (26)
A formal framework for robot learning and control under model uncertainty (2007) (26)
Automatic Construction of Temporally Extended Actions for MDPs Using Bisimulation Metrics (2011) (25)
Hierarchical temporal graphical model for head pose estimation and subsequent attribute classification in real-world videos (2015) (25)
Algorithmic Improvements for Deep Reinforcement Learning applied to Interactive Fiction (2019) (25)
Probabilistic Temporal Head Pose Estimation Using a Hierarchical Graphical Model (2014) (25)
Leveraging Lexical Resources for Learning Entity Embeddings in Multi-Relational Data (2016) (24)
Boosting Based Multiple Kernel Learning and Transfer Regression for Electricity Load Forecasting (2017) (24)
Options of Interest: Temporal Abstraction with Interest Functions (2020) (23)
An Equivalence between Loss Functions and Non-Uniform Sampling in Experience Replay (2020) (23)
Learning Safe Policies with Expert Guidance (2018) (22)
Combining and adapting software quality predictive models by genetic algorithms (2002) (22)
A Canonical Form for Weighted Automata and Applications to Approximate Minimization (2015) (22)
A Planning Algorithm for Predictive State Representations (2003) (22)
Policy Evaluation Networks (2020) (22)
Ubenwa: Cry-based Diagnosis of Birth Asphyxia (2017) (22)
On-the-Fly Algorithms for Bisimulation Metrics (2012) (21)
World Knowledge for Reading Comprehension: Rare Entity Prediction with Hierarchical LSTMs Using External Descriptions (2017) (21)
Smarter Sampling in Model-Based Bayesian Reinforcement Learning (2010) (20)
Learning with Options that Terminate Off-Policy (2017) (20)
A Machine Learning Approach to the Detection of Fetal Hypoxia during Labor and Delivery (2010) (20)
Assessment of Extubation Readiness Using Spontaneous Breathing Trials in Extremely Preterm Neonates. (2019) (20)
Revisiting Heterophily For Graph Neural Networks (2022) (20)
Optimizing Home Energy Management and Electric Vehicle Charging with Reinforcement Learning (2018) (20)
Exponentiated Gradient Methods for Reinforcement Learning (1997) (20)
Value Pursuit Iteration (2012) (19)
On-line Reinforcement Learning Using Incremental Kernel-Based Stochastic Factorization (2012) (19)
Self-supervised Learning of Distance Functions for Goal-Conditioned Reinforcement Learning (2019) (18)
Bayesian and grAphical Models for Biomedical Imaging (2014) (18)
Neural Transfer Learning for Cry-based Diagnosis of Perinatal Asphyxia (2019) (18)
Basis Function Discovery Using Spectral Clustering and Bisimulation Metrics (2011) (18)
IMaGe: Iterative Multilevel Probabilistic Graphical Model for Detection and Segmentation of Multiple Sclerosis Lesions in Brain MRI (2015) (18)
Early Prediction of Alzheimer's Disease Progression Using Variational Autoencoders (2019) (17)
Using Rewards for Belief State Updates in Partially Observable Markov Decision Processes (2005) (17)
Learning to cooperate: Emergent communication in multi-agent navigation (2020) (17)
Shaping representations through communication: community size effect in artificial learning systems (2019) (17)
Verb Phrase Ellipsis Resolution Using Discriminative and Margin-Infused Algorithms (2016) (17)
Point-Based Planning for Predictive State Representations (2008) (17)
Characterizing Markov Decision Processes (2002) (16)
Investigating Recurrence and Eligibility Traces in Deep Q-Networks (2017) (16)
On Efficiency in Hierarchical Reinforcement Learning (2020) (16)
Learning to Prove from Synthetic Theorems (2020) (16)
Bellman Error Based Feature Generation using Random Projections on Sparse Spaces (2012) (15)
Policy Iteration Based on Stochastic Factorization (2014) (15)
Soft biometric trait classification from real-world face videos conditioned on head pose estimation (2012) (15)
Randomized Exploration for Reinforcement Learning with General Value Function Approximation (2021) (15)
Quantifying the determinants of outbreak detection performance through simulation and machine learning (2015) (15)
Representing Systems with Hidden State (2006) (14)
Using MDP Characteristics to Guide Exploration in Reinforcement Learning (2003) (14)
Forethought and Hindsight in Credit Assignment (2020) (14)
Temporal Regularization in Markov Decision Process (2018) (14)
Safe option-critic: learning safety in the option-critic architecture (2018) (14)
Classification-Based Approximate Policy Iteration (2015) (13)
Hierarchical Spatio-Temporal Probabilistic Graphical Model with Multiple Feature Fusion for Binary Facial Attribute Classification in Real-World Face Videos (2016) (13)
Planning with Closed Loop Macro Actions (2008) (13)
Uncertainty Aware Learning from Demonstrations in Multiple Contexts using Bayesian Neural Networks (2019) (13)
Option-critic in cooperative multi-agent systems (2019) (13)
Belief Selection in Point-Based Planning Algorithms for POMDPs (2006) (12)
Off-policy Learning with Options and Recognizers (2005) (12)
Reward Propagation Using Graph Convolutional Networks (2020) (12)
Variational Generative Stochastic Networks with Collaborative Shaping (2015) (12)
Anytime similarity measures for faster alignment (2008) (12)
Predicting Future Disease Activity and Treatment Responders for Multiple Sclerosis Patients Using a Bag-of-Lesions Brain Representation (2017) (12)
Representation Discovery for MDPs Using Bisimulation Metrics (2015) (12)
Automatically suggesting topics for augmenting text documents (2010) (11)
Constructing a Good Behavior Basis for Transfer using Generalized Policy Updates (2021) (11)
AndroidEnv: A Reinforcement Learning Platform for Android (2021) (11)
A novel similarity measure for time series data with applications to gait and activity recognition (2010) (11)
Sparse Distributed Memories in Reinforcement Learning : Case Studies (2004) (11)
A Consciousness-Inspired Planning Agent for Model-Based Reinforcement Learning (2021) (11)
Value-driven Hindsight Modelling (2020) (10)
Off-policy Learning with Recognizers (2000) (10)
Approximate Predictive Representations of Partially Observable Systems (2010) (10)
Multi-layer temporal graphical model for head pose estimation in real-world videos (2014) (10)
System-identification noise suppression for intra-partum cardiotocography to discriminate normal and hypoxic fetuses (2006) (10)
Self-Supervised Attention-Aware Reinforcement Learning (2021) (10)
Shaping representations through communication (2018) (10)
Improving Pathological Structure Segmentation via Transfer Learning Across Diseases (2019) (10)
Why Should I Trust You, Bellman? The Bellman Error is a Poor Replacement for Value Error (2022) (10)
Classification Using Φ-Machines and Constructive Function Approximation (1998) (10)
Generalized Classication-bas ed Approximate Policy Iteration (2012) (10)
An approximation algorithm for labelled Markov processes: towards realistic approximation (2005) (9)
Using core beliefs for point-based value iteration (2005) (9)
Knowledge Transfer in Markov Decision Processes (2006) (9)
Marginalized State Distribution Entropy Regularization in Policy Optimization (2019) (9)
Using Hierarchical Mixture of Experts Model for Fusion of Outbreak Detection Methods (2013) (9)
Navigation Agents for the Visually Impaired: A Sidewalk Simulator and Experiments (2019) (9)
How to Find Big-Oh in Your Data Set (and How Not to) (1997) (9)
Bisimulation for Markov Decision Processes through Families of Functional Expressions (2014) (9)
Generating storylines from sensor data (2013) (9)
Policy Gradient Methods for Off-policy Control (2015) (8)
Temporal Abstraction in Reinforcement Learning with the Successor Representation (2021) (8)
Complete the Missing Half: Augmenting Aggregation Filtering with Diversification for Graph Convolutional Networks (2020) (8)
Clustering-Oriented Representation Learning with Attractive-Repulsive Loss (2018) (8)
Learning with options : Just deliberate and relax (2015) (8)
Training a First-Order Theorem Prover from Synthetic Data (2021) (8)
Locally Persistent Exploration in Continuous Control Tasks with Sparse Rewards (2020) (7)
Actor Critic with Differentially Private Critic (2019) (7)
Constructive Function Approximation TITLE2 (1997) (7)
Model minimization by linear PSR (2005) (7)
A Brief Look at Generalization in Visual Meta-Reinforcement Learning (2020) (7)
Augmenting learning using symmetry in a biologically-inspired domain (2019) (7)
Learning representations of Logical Formulae using Graph Neural Networks (2019) (7)
Incremental Stochastic Factorization for Online Reinforcement Learning (2016) (7)
Knowledge Representation for Reinforcement Learning using General Value Functions (2018) (7)
Singular value automata and approximate minimization (2017) (7)
Multi-Time Models for Reinforcement Learning (2007) (7)
Policy Gradients Incorporating the Future (2021) (7)
Basis refinement strategies for linear value function approximation in MDPs (2015) (7)
Developing collaborative Golog agents by reinforcement learning (2001) (7)
SVRG for Policy Evaluation with Fewer Gradient Evaluations (2019) (7)
Feature selection and oversampling in analysis of clinical data for extubation readiness in extreme preterm infants (2015) (6)
A Distributional Analysis of Sampling-Based Reinforcement Learning Algorithms (2020) (6)
The Barbados 2018 List of Open Issues in Continual Learning (2018) (6)
Single-Shot Pruning for Offline Reinforcement Learning (2021) (6)
An Empirical Analysis of Off-policy Learning in Discrete MDPs (2012) (6)
Fast Image Alignment Using Anytime Algorithms (2007) (6)
Using label propagation for learning temporally abstract actions in reinforcement learning (2013) (6)
COptiDICE: Offline Constrained Reinforcement Learning via Stationary Distribution Correction Estimation (2022) (6)
Improved Switching among Temporally Abstract Actions". In Advances in Neural Information Processing Systems (1999) (6)
Temporally Abstract Partial Models (2021) (6)
Attend Before you Act: Leveraging human visual attention for continual learning (2018) (6)
An Algebraic Approach to Dynamic Epistemic Logic (2010) (6)
Entropy Regularization with Discounted Future State Distribution in Policy Gradient Methods (2019) (5)
Learning Options with Interest Functions (2019) (5)
Variance Penalized On-Policy and Off-Policy Actor-Critic (2021) (5)
An Empirical Study of Batch Normalization and Group Normalization in Conditional Computation (2019) (5)
Correcting Momentum in Temporal Difference Learning (2021) (5)
Improving Long-Term Metrics in Recommendation Systems using Short-Horizon Offline RL (2021) (5)
Dyna Planning using a Feature Based Generative Model (2018) (5)
Classification-based Approximate Policy Iteration: Experiments and Extended Discussions (2014) (5)
Eligibility Traces for Options (2018) (5)
Learning and Planning with Timing Information in Markov Decision Processes (2015) (5)
Flexible Option Learning (2021) (5)
Environments for Lifelong Reinforcement Learning (2018) (5)
A Deep Reinforcement Learning Approach to Marginalized Importance Sampling with the Successor Representation (2021) (5)
Per-Decision Option Discounting (2019) (5)
Automated ongoing data validation and quality control of multi-institutional studies (2016) (5)
Training Matters: Unlocking Potentials of Deeper Graph Convolutional Neural Networks (2020) (4)
Relative Value Function Approximation (1997) (4)
Greedy Confidence Pursuit: A Pragmatic Approach to Multi-bandit Optimization (2013) (4)
Learning Predictive State Representations From Non-Uniform Sampling (2018) (4)
Undersampling and Bagging of Decision Trees in the Analysis of Cardiorespiratory Behavior for the Prediction of Extubation Readiness in Extremely Preterm Infants (2018) (4)
Notions of State Equivalence under Partial Observability (2009) (4)
Learning Modular Safe Policies in the Bandit Setting with Application to Adaptive Clinical Trials (2019) (4)
Leveraging Observations in Bandits: Between Risks and Benefits (2019) (4)
Learning Multi-Step Predictive State Representations (2016) (4)
Fetal Heart Rate Deceleration Detection from the Discrete Cosine Transform Spectrum (2005) (4)
A Framework for Computing Bounds for the Return of a Policy (2011) (4)
Pooled Screening for Synergistic Interactions Subject to Blocking and Noise (2014) (4)
Linear models of intrapartum uterine pressure-fetal heart rate interaction for the normal and hypoxic fetus (2006) (4)
Optimal Spectral-Norm Approximate Minimization of Weighted Finite Automata (2021) (4)
Improved Estimation in Time Varying Models (2012) (4)
Organizational principles of cloud storage to support collaborative biomedical research (2015) (4)
Nonlinear Weighted Finite Automata (2018) (3)
A Fully Tensorized Recurrent Neural Network (2020) (3)
Improving Robustness against Real-World and Worst-Case Distribution Shifts through Decision Region Quantification (2022) (3)
Low-order parametric system identification for intrapartum uterine pressure-fetal heart rate interaction (2007) (3)
Temporally Extended Metrics for Markov Decision Processes (2019) (3)
Diversity-Enriched Option-Critic (2020) (3)
Where Did You Learn That From? Surprising Effectiveness of Membership Inference Attacks Against Temporally Correlated Data in Deep Reinforcement Learning (2021) (3)
Time progression of a parametric impulse response function estimate from intra-partum cardiotocography for normal and hypoxic fetuses (2007) (3)
Probabilistic robot planning under model uncertainty : an active learning approach (2005) (3)
The Duality of State and Observation in Probabilistic Transition Systems (2011) (3)
A semi-Markov chain approach to modeling respiratory patterns prior to extubation in preterm infants (2017) (3)
Doubly Robust Off-Policy Actor-Critic Algorithms for Reinforcement Learning (2019) (3)
A Matrix Splitting Perspective on Planning with Options (2016) (3)
Horizontal and Vertical Self-Adaptive Cloud Controller with Reward Optimization for Resource Allocation (2017) (3)
Recurrent Value Functions (2019) (3)
Constructing Temporal Abstractions Autonomously in Reinforcement Learning (2018) (3)
Where Off-Policy Deep Reinforcement Learning Fails (2018) (2)
Relative Value Function Approximation TITLE2 (1997) (2)
Phylogenetic Manifold Regularization: A semi-supervised approach to predict transcription factor binding sites (2020) (2)
Exploration in POMDP belief space and its impact on value iteration approximation (2008) (2)
An Expectation-Maximization Algorithm to Compute a Stochastic Factorization From Data (2015) (2)
Improving Long-Term Metrics in Recommendation Systems using Short-Horizon Reinforcement Learning (2021) (2)
Apprentissage actif dans les processus décisionnels de Markov partiellement observables L'algorithme MEDUSA (2007) (2)
Towards Painless Policy Optimization for Constrained MDPs (2022) (2)
Continuous MDP Homomorphisms and Homomorphic Policy Gradient (2022) (2)
oIRL: Robust Adversarial Inverse Reinforcement Learning with Temporally Extended Actions (2020) (2)
Diffusion-Based Approximate Value Functions (2018) (2)
A Study of Approximate Inference in Probabilistic Relational Models (2010) (2)
Importance of Empirical Sample Complexity Analysis for Offline Reinforcement Learning (2021) (2)
Attention Option-Critic (2022) (2)
The Duality of State and Observations (2007) (2)
Fetal Heart Rate Deceleration Detection Using a Discrete Cosine Transform Implementation of Singular Spectrum Analysis (2007) (2)
Connecting Weighted Automata, Tensor Networks and Recurrent Neural Networks through Spectral Learning (2020) (2)
A Study of Off-policy Learning in Computational Sustainability (2012) (2)
Collaboration policies for case-based reasoning agents (2001) (2)
Using bisimulation for policy transfer in MDPs (Extended Abstract) (2010) (2)
Predicting extubation readiness in extreme preterm infants based on patterns of breathing (2017) (2)
An Approach to Inference in Probabilistic Relational Models using Block Sampling (2010) (2)
Preferential Temporal Difference Learning (2021) (2)
Average Reward Optimization Objective In Partially Observable Domains (2013) (1)
Understanding Decision-Time vs. Background Planning in Model-Based Reinforcement Learning (2022) (1)
Estimating individual treatment effect on disability progression in multiple sclerosis using deep learning (2022) (1)
On learning history based policies for controlling Markov decision processes (2022) (1)
Representation of Reinforcement Learning Policies in Reproducing Kernel Hilbert Spaces. (2020) (1)
Adapted MRF Segmentation of Multiple Sclerosis Lesions Using Local Contextual Information (2011) (1)
Multi-Timescale, Gradient Descent, Temporal Difference Learning with Linear Options (2017) (1)
Learning proposals for sequential importance samplers using reinforced variational inference (2019) (1)
The Paradox of Choice: Using Attention in Hierarchical Reinforcement Learning (2022) (1)
Empirical Comparison of Gradient Descent and Exponentiated Gradient Descent in Supervised and Reinforcement Learning (1996) (1)
Learning Algorithms for Automata with Observations (2007) (1)
What is Going on Inside Recurrent Meta Reinforcement Learning Agents? (2021) (1)
Neural Network Based Nonlinear Weighted Finite Automata (2017) (1)
Proving Theorems using Incremental Learning and Hindsight Experience Replay (2021) (1)
Avoidance Learning Using Observational Reinforcement Learning (2019) (1)
Learning Policies for Local Instruction Scheduling (1997) (1)
Sample-based approximate regularization (2014) (1)
Provably efficient reconstruction of policy networks (2020) (1)
Mining Administrative Data to Predict Falls in the Elderly Population (2012) (1)
Correlation of clinical parameters with cardiorespiratory behavior in successfully extubated extremely preterm infants (2015) (1)
RedAgent: An Autonomous, Market-based Supply-Chain Management Agent for the Trading Agents Competition (2006) (1)
When Do We Need GNN for Node Classification? (2022) (1)
Efficient Planning under Partial Observability with Unnormalized Q Functions and Spectral Learning (2019) (1)
Building Knowledge for AI Agents with Reinforcement Learning (2019) (1)
Finite time analysis of temporal difference learning with linear function approximation: the tail averaged case (2021) (1)
Learning the Difference between Partially Observable Dynamical Systems (2009) (1)
Multi-Environment Pretraining Enables Transfer to Action Limited Datasets (2022) (1)
Detecting the temporal extent of the impulse response function from intra-partum cardiotocography for normal and hypoxic fetuses (2008) (1)
Context-Driven Predictions (2007) (1)
On Average Reward Policy Evaluation in Infinite-State Partially Observable Systems (2012) (1)
ERRATUM: DEVELOPING COLLABORATIVE GOLOG AGENTS BY REINFORCEMENT LEARNING (2002) (1)
Optimizing Energy Production Using Policy Search and Predictive State Representations (2014) (1)
Automated prediction of extubation success in extremely preterm infants: the APEX multicenter study (2022) (1)
Improving Sample Efficiency of Value Based Models Using Attention and Vision Transformers (2022) (0)
Learning how to Interact with a Complex Interface using Hierarchical Reinforcement Learning (2022) (0)
Bayesian Q-learning With Imperfect Expert Demonstrations (2022) (0)
Crosslingual Implementation of Linguistic Taggers using a Bitext Corpus 6 (2008) (0)
Function Approximation using Dividing Features (2006) (0)
Model-based Bayesian Reinforcement Learning with Tree-based State Aggregation (2008) (0)
Assessing Generalization in TD methods for Deep Reinforcement Learning (2019) (0)
Approximate Value Iteration with Temporally Extended Actions (Extended Abstract) (2017) (0)
Determinants of Outbreak Detection Performance (2013) (0)
Information Theoretic Approaches for Predictive Models : Results and Analysis (2006) (0)
Learning-based interactive segmentation using the maximum mean cycle weight formalism (2017) (0)
Reinforcement learning of conditional computation policies for neural networks (2016) (0)
Estimating treatment effect for individuals with progressive multiple sclerosis using deep learning (2021) (0)
P OLICY G RADIENTS I NCORPORATING THE F UTURE (2022) (0)
Smart Classifier Selection for Activity Recognition on Wearable Devices (2016) (0)
Continual Reinforcement Learning with Multi-Timescale Successor Features (2022) (0)
APEX_SCOPE: A graphical user interface for visualization of multi-modal data in inter-disciplinary studies (2017) (0)
Reports of the AAAI 2011 Conference Workshops (2012) (0)
Bandits in a network (2015) (0)
MUDiff: Unified Diffusion for Complete Molecule Generation (2023) (0)
Sample-based Approximate Regularization (Extended Version) (2014) (0)
Low-Rank Representation of Reinforcement Learning Policies (2022) (0)
Memory Based Learning in Partially Observable Markov Decision Processes with Variable Length Histories (2007) (0)
FORCEMENT LEARNING AGENTS? (2021) (0)
Simulating Human Gaze with Neural Visual Attention (2022) (0)
UvA-DARE (Digital Academic Repository) Uncertainty Aware Learning from Demonstrations in Multiple Contexts using Bayesian Neural Networks (2019) (0)
Prediction of Cell Type Specific Transcription Factor Binding Site Occupancy (2016) (0)
On the Challenges of using Reinforcement Learning in Precision Drug Dosing: Delay and Prolongedness of Action Effects (2023) (0)
Faster and More Accurate Trace-based Policy Evaluation via Overall Target Error Meta-Optimization (2019) (0)
Finite time analysis of temporal difference learning with linear function approximation: Tail averaging and regularisation (2022) (0)
On the Expressivity of Markov Reward (Extended Abstract) (2022) (0)
Keynote Lecture - Building Knowledge For AI AgentsWith Reinforcement Learning (2020) (0)
AAAI Workshop - Technical Report: Preface (2011) (0)
A Study of Policy Gradient on a Class of Exactly Solvable Models (2020) (0)
CO PTI DICE: O FFLINE C ONSTRAINED R EINFORCE MENT L EARNING VIA S TATIONARY D ISTRIBUTION C ORRECTION E STIMATION (2022) (0)
Assessing Intrapartum Risk of Hypoxic Ischemic Encephalopathy Using Fetal Heart Rate With Long Short-Term Memory Networks (2022) (0)
Prediction of Progression in Multiple Sclerosis Patients (2018) (0)
Initializing Entity Representations in Relational Models (2016) (0)
Data-driven Chance Constrained Programming based Electric Vehicle Penetration Analysis (2019) (0)
Recognizers : A study in learning how to model temporally extended behaviors (2007) (0)
Editorial on Special Issue on Probabilistic Models for Biomedical Image Analysis (2016) (0)
Learning and Discovery in Dynamical Systems with Hidden State (2007) (0)
Behind the Machine's Gaze: Neural Networks with Biologically-inspired Constraints Exhibit Human-like Visual Attention (2022) (0)
Learning Reliable Policies in the Bandit Setting with Application to Adaptive Clinical Trials (2019) (0)
Theoretical results on the effect of ‘shortcut’ actions in MDPs (2014) (0)
Multi-Time Models for Reinforcement Learning Doina PrecupDepartment of Computer ScienceUniversity of MassachusettsAmherst (1997) (0)
Predictive Timing Models (2014) (0)
Revisit Policy Optimization in Matrix Form (2019) (0)
Minimal Value-Equivalent Partial Models for Scalable and Robust Planning in Lifelong Reinforcement Learning (2023) (0)
“ Structure & Priors in Reinforcement Learning ” at ICLR 2019 V ALUE P RESERVING S TATE-A CTION A BSTRACTIONS ( A PPENDIX ) (2019) (0)
Community size effect in artificial learning systems (2019) (0)
Towards Safe Mechanical Ventilation Treatment Using Deep Offline Reinforcement Learning (2022) (0)
META-Learning State-based Eligibility Traces for More Sample-Efficient Policy Evaluation (2019) (0)
Leveraging Observational Learning for Exploration in Bandits (2018) (0)
Selective Credit Assignment (2022) (0)
Accelerating exploration and representation learning with offline pre-training (2023) (0)
Towards Painless Policy Optimization for Constrained MDPs: Supplementary material (2022) (0)
Behind the Machine's Gaze: Biologically Constrained Neural Networks Exhibit Human-like Visual Attention (2022) (0)
META-Learning State-based {\lambda} for More Sample-Efficient Policy Evaluation (2019) (0)
Reinforcement Learning Algorithms in Markov Decision Processes AAAI-10 Tutorial Part II: Learning to predict values (2010) (0)
Automated ongoing data validation and quality control of multi-institutional studies. (2016) (0)
Learning Control Policies for Virtual Grasping Applications (2010) (0)
Model-based Bayesian Reinforcement Learning with Adaptive State Aggregation (2009) (0)
An information-theoretic approach to curiosity-driven reinforcement learning (2012) (0)
Analyzing User Trajectories from Mobile Device Data with Hierarchical Dirichlet Processes (2014) (0)
Gifting in Multi-Agent Reinforcement Learning (Student Abstract) (2020) (0)
PhyloPGM: boosting regulatory function prediction accuracy using evolutionary information (2022) (0)
Differentially Private Policy Evaluation ( Supplementary Material ) (2016) (0)
When Do Graph Neural Networks Help with Node Classification: Investigating the Homophily Principle on Node Distinguishability (2023) (0)
Offline Policy Optimization in RL with Variance Regularizaton (2022) (0)
Trajectory Simulation and Optimization for a Fuzzy-Controlled Mobile Robot (1995) (0)
Learning Compact Representations of Time-Varying Processes (2011) (0)
Activity Recognition with Time-Delay Emobeddings (2011) (0)
The Stable Entropy Hypothesis and Entropy-Aware Decoding: An Analysis and Algorithm for Robust Natural Language Generation (2023) (0)
Randomized Least Squares Policy Optimization (2021) (0)
The Paradox of Choice: On the Role of Attention in Hierarchical Reinforcement Learning (2022) (0)
Testing Visual Attention in Dynamic Environments (2015) (0)
Membership Inference Attacks Against Temporally Correlated Data in Deep Reinforcement Learning (2021) (0)
Using Policy Gradients to Account for Changes in Behaviour Policies Using Policy Gradients to Account for Changes in Behaviour Policies under Off-policy Control (2016) (0)
Exploration in RL using MDP characteristics (2003) (0)
Convergent Temporal-Difference Learning with Arbitrary Differentiable Function Approximator (2010) (0)
The Workshop Program at the Nineteenth National Conference on Artificial Intelligence (2005) (0)
Imitation Upper Confidence Bound for Bandits on a Graph (2018) (0)
Reinforcement Learning Algorithms in Markov Decision Processes AAAI-10 Tutorial Part IV: Take home message (2010) (0)

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