Kee-eung Kim
53 papers · 2011–2026 · 12 venues · across top CS/AI venues
Authors are matched by name, so researchers who share a name ("Yang Liu", "Wei Wang") appear as a single profile and their paper counts, venues and achievements are combined. How identity is handled.
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(21)
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(16)
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(6)
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Research topics
Machine Learning
(36)
Artificial Intelligence
(27)
Reinforcement Learning
(26)
Methods
(24)
Core AI
(21)
Learning Types Β· Machine Learning
(19)
Optimization & Theory
(14)
Deep Learning
(13)
Core Methods
(12)
Bayesian & Probabilistic Β· Artificial Intelligence
(9)
Application Areas
(8)
Natural Language Processing
(7)
Learning Types Β· Deep Learning
(7)
Models
(7)
Bayesian & Probabilistic Β· Machine Learning
(6)
Keywords
offline reinforcement learning
(10)
reinforcement learning
(9)
bayesian inference
(7)
stationary distribution
(6)
variational inference
(5)
model-based reinforcement learning
(4)
language model
(4)
monte carlo tree search
(4)
inverse reinforcement learning
(3)
off-policy evaluation
(3)
dialogue system
(3)
imitation learning
(3)
reward function
(3)
policy learning
(3)
policy optimization
(3)
multi-task learning
(2)
representation learning
(2)
behavior cloning
(2)
bayesian reinforcement learning
(2)
adversarial learning
(2)
Papers
Optimizing Preferential Rate in Retail Lending with Causal Inference and Domain Adaptation
AAAI 2026
Goal-Conditioned DPO: Prioritizing Safety in Misaligned Instructions
NAACL 2025
Monet: Mixture of Monosemantic Experts for Transformers
ICLR 2025
A Submodular Optimization Approach to Accountable Loan Approval
AAAI 2024
Data Augmentation with Diffusion for Open-Set Semi-Supervised Learning
NeurIPS 2024
Diversification of Adaptive Policy for Effective Offline Reinforcement Learning
IJCAI 2024
GDPO: Learning to Directly Align Language Models with Diversity Using GFlowNets
EMNLP 2024
Hard Prompts Made Interpretable: Sparse Entropy Regularization for Prompt Tuning with RL
ACL 2024
Kernel Metric Learning for In-Sample Off-Policy Evaluation of Deterministic RL Policies
ICLR 2024
Mitigating Covariate Shift in Behavioral Cloning via Robust Stationary Distribution Correction
NeurIPS 2024
Stitching Sub-trajectories with Conditional Diffusion Model for Goal-Conditioned Offline RL
AAAI 2024
SyncVSR: Data-Efficient Visual Speech Recognition with End-to-End Crossmodal Audio Token Synchronization
Interspeech 2024
AlberDICE: Addressing Out-Of-Distribution Joint Actions in Offline Multi-Agent RL via Alternating Stationary Distribution Correction Estimation
NeurIPS 2023
Bayesian Multi-Task Transfer Learning for Soft Prompt Tuning
EMNLP 2023
Information-Theoretic State Space Model for Multi-View Reinforcement Learning
ICML 2023
Regularized Behavior Cloning for Blocking the Leakage of Past Action Information
NeurIPS 2023
Trustworthy Residual Vehicle Value Prediction for Auto Finance
AAAI 2023
COptiDICE: Offline Constrained Reinforcement Learning via Stationary Distribution Correction Estimation
ICLR 2022
Data Augmentation for Learning to Play in Text-Based Games
IJCAI 2022
DemoDICE: Offline Imitation Learning with Supplementary Imperfect Demonstrations
ICLR 2022
GPT-Critic: Offline Reinforcement Learning for End-to-End Task-Oriented Dialogue Systems
ICLR 2022
Learning to Embed Multi-Modal Contexts for Situated Conversational Agents
NAACL 2022
LobsDICE: Offline Learning from Observation via Stationary Distribution Correction Estimation
NeurIPS 2022
Local Metric Learning for Off-Policy Evaluation in Contextual Bandits with Continuous Actions
NeurIPS 2022
PAC-Net: A Model Pruning Approach to Inductive Transfer Learning
ICML 2022
Structure-Aware Transformer Policy for Inhomogeneous Multi-Task Reinforcement Learning
ICLR 2022
Monte-Carlo Planning and Learning with Language Action Value Estimates
ICLR 2021
Multi-View Representation Learning via Total Correlation Objective
NeurIPS 2021
OptiDICE: Offline Policy Optimization via Stationary Distribution Correction Estimation
ICML 2021
Representation Balancing Offline Model-based Reinforcement Learning
ICLR 2021
Winning the L2RPN Challenge: Power Grid Management via Semi-Markov Afterstate Actor-Critic
ICLR 2021
Batch Reinforcement Learning with Hyperparameter Gradients
ICML 2020
Bayes-Adaptive Monte-Carlo Planning and Learning for Goal-Oriented Dialogues
AAAI 2020
End-to-End Neural Pipeline for Goal-Oriented Dialogue Systems using GPT-2
ACL 2020
Monte-Carlo Tree Search in Continuous Action Spaces with Value Gradients
AAAI 2020
Reinforcement Learning for Control with Multiple Frequencies
NeurIPS 2020
Residual Neural Processes
AAAI 2020
Variational Inference for Sequential Data with Future Likelihood Estimates
ICML 2020
Variational Interaction Information Maximization for Cross-domain Disentanglement
NeurIPS 2020
PyOpenDial: A Python-based Domain-Independent Toolkit for Developing Spoken Dialogue Systems with Probabilistic Rules
EMNLP 2019
Trust Region Sequential Variational Inference
ACML 2019
A Bayesian Approach to Generative Adversarial Imitation Learning
NeurIPS 2018
Monte-Carlo Tree Search for Constrained POMDPs
NeurIPS 2018
Constrained Bayesian Reinforcement Learning via Approximate Linear Programming
IJCAI 2017
Generative Local Metric Learning for Kernel Regression
NeurIPS 2017
Hierarchically-partitioned Gaussian Process Approximation
AISTATS 2017
Bayesian Reinforcement Learning with Behavioral Feedback
IJCAI 2016
Reactive bandits with attitude
AISTATS 2015
Bayesian Nonparametric Feature Construction for Inverse Reinforcement Learning
IJCAI 2013
Cost-Sensitive Exploration in Bayesian Reinforcement Learning
NeurIPS 2012
Nonparametric Bayesian Inverse Reinforcement Learning for Multiple Reward Functions
NeurIPS 2012
Inverse Reinforcement Learning in Partially Observable Environments
JMLR 2011
MAP Inference for Bayesian Inverse Reinforcement Learning
NeurIPS 2011