Yang Yu

Orcid: 0000-0002-1732-9545

Affiliations:
  • Nanjing University, State Key Laboratory for Novel Software Technology, China (PhD 2011)
  • Pazhou Lab, Guangzhou, China


According to our database1, Yang Yu authored at least 207 papers between 2005 and 2024.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

Legend:

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Bibliography

2024
Communication-robust multi-agent learning by adaptable auxiliary multi-agent adversary generation.
Frontiers Comput. Sci., December, 2024

Model gradient: unified model and policy learning in model-based reinforcement learning.
Frontiers Comput. Sci., August, 2024

MixLight: Mixed-Agent Cooperative Reinforcement Learning for Traffic Light Control.
IEEE Trans. Ind. Informatics, February, 2024

Disentangling Policy from Offline Task Representation Learning via Adversarial Data Augmentation.
CoRR, 2024

Debiased Offline Representation Learning for Fast Online Adaptation in Non-stationary Dynamics.
CoRR, 2024

Empowering Language Models with Active Inquiry for Deeper Understanding.
CoRR, 2024

Beimingwu: A Learnware Dock System.
CoRR, 2024

Generalizable Task Representation Learning for Offline Meta-Reinforcement Learning with Data Limitations.
Proceedings of the Thirty-Eighth AAAI Conference on Artificial Intelligence, 2024

ACT: Empowering Decision Transformer with Dynamic Programming via Advantage Conditioning.
Proceedings of the Thirty-Eighth AAAI Conference on Artificial Intelligence, 2024

Focus-Then-Decide: Segmentation-Assisted Reinforcement Learning.
Proceedings of the Thirty-Eighth AAAI Conference on Artificial Intelligence, 2024

2023
Fully Decentralized Multiagent Communication via Causal Inference.
IEEE Trans. Neural Networks Learn. Syst., December, 2023

Offline Model-Based Adaptable Policy Learning for Decision-Making in Out-of-Support Regions.
IEEE Trans. Pattern Anal. Mach. Intell., December, 2023

Learning Physically Realizable Skills for Online Packing of General 3D Shapes.
ACM Trans. Graph., October, 2023

Memory-efficient Transformer-based network model for Traveling Salesman Problem.
Neural Networks, April, 2023

AliExpress Learning-to-Rank: Maximizing Online Model Performance Without Going Online.
IEEE Trans. Knowl. Data Eng., 2023

A Survey of Progress on Cooperative Multi-agent Reinforcement Learning in Open Environment.
CoRR, 2023

Efficient Human-AI Coordination via Preparatory Language-based Convention.
CoRR, 2023

Imitator Learning: Achieve Out-of-the-Box Imitation Ability in Variable Environments.
CoRR, 2023

Reward-Consistent Dynamics Models are Strongly Generalizable for Offline Reinforcement Learning.
CoRR, 2023

Learning to Coordinate with Anyone.
CoRR, 2023

Learning World Models with Identifiable Factorization.
CoRR, 2023

Language Model Self-improvement by Reinforcement Learning Contemplation.
CoRR, 2023

Multi-agent Continual Coordination via Progressive Task Contextualization.
CoRR, 2023

Robust Multi-agent Communication via Multi-view Message Certification.
CoRR, 2023

Beware of Instantaneous Dependence in Reinforcement Learning.
CoRR, 2023

Efficient Communication via Self-supervised Information Aggregation for Online and Offline Multi-agent Reinforcement Learning.
CoRR, 2023

Natural Language-conditioned Reinforcement Learning with Inside-out Task Language Development and Translation.
CoRR, 2023

Theoretical Analysis of Offline Imitation With Supplementary Dataset.
CoRR, 2023

Fast Teammate Adaptation in the Presence of Sudden Policy Change.
Proceedings of the Uncertainty in Artificial Intelligence, 2023

Provably Efficient Adversarial Imitation Learning with Unknown Transitions.
Proceedings of the Uncertainty in Artificial Intelligence, 2023

Natural Language Instruction-following with Task-related Language Development and Translation.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Learning World Models with Identifiable Factorization.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Imitation Learning from Imperfection: Theoretical Justifications and Algorithms.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Adversarial Counterfactual Environment Model Learning.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Internal Logical Induction for Pixel-Symbolic Reinforcement Learning.
Proceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2023

Object-Oriented Option Framework for Robotics Manipulation in Clutter.
IROS, 2023

Policy Regularization with Dataset Constraint for Offline Reinforcement Learning.
Proceedings of the International Conference on Machine Learning, 2023

Discovering Generalizable Multi-agent Coordination Skills from Multi-task Offline Data.
Proceedings of the Eleventh International Conference on Learning Representations, 2023

Sim2Rec: A Simulator-based Decision-making Approach to Optimize Real-World Long-term User Engagement in Sequential Recommender Systems.
Proceedings of the 39th IEEE International Conference on Data Engineering, 2023

Degradation-Resistant Offline Optimization via Accumulative Risk Control.
Proceedings of the ECAI 2023 - 26th European Conference on Artificial Intelligence, September 30 - October 4, 2023, Kraków, Poland, 2023

Learning to Coordinate with Anyone.
Proceedings of the Fifth International Conference on Distributed Artificial Intelligence, 2023

Self-Motivated Multi-Agent Exploration.
Proceedings of the 2023 International Conference on Autonomous Agents and Multiagent Systems, 2023

How To Guide Your Learner: Imitation Learning with Active Adaptive Expert Involvement.
Proceedings of the 2023 International Conference on Autonomous Agents and Multiagent Systems, 2023

Model-Based Offline Weighted Policy Optimization (Student Abstract).
Proceedings of the Thirty-Seventh AAAI Conference on Artificial Intelligence, 2023

Robust Multi-Agent Coordination via Evolutionary Generation of Auxiliary Adversarial Attackers.
Proceedings of the Thirty-Seventh AAAI Conference on Artificial Intelligence, 2023

Anti-drifting Feature Selection via Deep Reinforcement Learning (Student Abstract).
Proceedings of the Thirty-Seventh AAAI Conference on Artificial Intelligence, 2023

Policy-Independent Behavioral Metric-Based Representation for Deep Reinforcement Learning.
Proceedings of the Thirty-Seventh AAAI Conference on Artificial Intelligence, 2023

Learning Generalizable Batch Active Learning Strategies via Deep Q-networks (Student Abstract).
Proceedings of the Thirty-Seventh AAAI Conference on Artificial Intelligence, 2023

Deep Anomaly Detection and Search via Reinforcement Learning (Student Abstract).
Proceedings of the Thirty-Seventh AAAI Conference on Artificial Intelligence, 2023

Untargeted Attack against Federated Recommendation Systems via Poisonous Item Embeddings and the Defense.
Proceedings of the Thirty-Seventh AAAI Conference on Artificial Intelligence, 2023

2022
A Lightweight Encoder-Decoder Path for Deep Residual Networks.
IEEE Trans. Neural Networks Learn. Syst., 2022

Efficient Reinforcement Learning for StarCraft by Abstract Forward Models and Transfer Learning.
IEEE Trans. Games, 2022

Error Bounds of Imitating Policies and Environments for Reinforcement Learning.
IEEE Trans. Pattern Anal. Mach. Intell., 2022

Cascaded Algorithm Selection With Extreme-Region UCB Bandit.
IEEE Trans. Pattern Anal. Mach. Intell., 2022

Improve generated adversarial imitation learning with reward variance regularization.
Mach. Learn., 2022

On Efficient Reinforcement Learning for Full-length Game of StarCraft II.
J. Artif. Intell. Res., 2022

Understanding or Manipulation: Rethinking Online Performance Gains of Modern Recommender Systems.
CoRR, 2022

Unified Policy Optimization for Continuous-action Reinforcement Learning in Non-stationary Tasks and Games.
CoRR, 2022

Heterogeneous Multi-agent Zero-Shot Coordination by Coevolution.
CoRR, 2022

Understanding Adversarial Imitation Learning in Small Sample Regime: A Stage-coupled Analysis.
CoRR, 2022

A Survey on Model-based Reinforcement Learning.
CoRR, 2022

Hybrid Value Estimation for Off-policy Evaluation and Offline Reinforcement Learning.
CoRR, 2022

Offline Reinforcement Learning with Causal Structured World Models.
CoRR, 2022

Transferable Reward Learning by Dynamics-Agnostic Discriminator Ensemble.
CoRR, 2022

A Note on Target Q-learning For Solving Finite MDPs with A Generative Oracle.
CoRR, 2022

Multi-Agent Policy Transfer via Task Relationship Modeling.
CoRR, 2022

Rethinking ValueDice: Does It Really Improve Performance?
CoRR, 2022

ZOOpt: a toolbox for derivative-free optimization.
Sci. China Inf. Sci., 2022

Bayesian Optimistic Optimization: Optimistic Exploration for Model-based Reinforcement Learning.
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

NeoRL: A Near Real-World Benchmark for Offline Reinforcement Learning.
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Efficient Multi-agent Communication via Self-supervised Information Aggregation.
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Multi-agent Dynamic Algorithm Configuration.
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Multi-Agent Concentrative Coordination with Decentralized Task Representation.
Proceedings of the Thirty-First International Joint Conference on Artificial Intelligence, 2022

Efficient Multi-Agent Communication via Shapley Message Value.
Proceedings of the Thirty-First International Joint Conference on Artificial Intelligence, 2022

The Teaching Dimension of Regularized Kernel Learners.
Proceedings of the International Conference on Machine Learning, 2022

Learning Efficient Online 3D Bin Packing on Packing Configuration Trees.
Proceedings of the Tenth International Conference on Learning Representations, 2022

Active Hierarchical Exploration with Stable Subgoal Representation Learning.
Proceedings of the Tenth International Conference on Learning Representations, 2022

Context-Aware Sparse Deep Coordination Graphs.
Proceedings of the Tenth International Conference on Learning Representations, 2022

A Searchable Re-encryption-based Scheme for Massive Data Transactions.
Proceedings of the 9th IEEE International Conference on Cyber Security and Cloud Computing, 2022

Invariant Action Effect Model for Reinforcement Learning.
Proceedings of the Thirty-Sixth AAAI Conference on Artificial Intelligence, 2022

Multi-Agent Incentive Communication via Decentralized Teammate Modeling.
Proceedings of the Thirty-Sixth AAAI Conference on Artificial Intelligence, 2022

Adapt to Environment Sudden Changes by Learning a Context Sensitive Policy.
Proceedings of the Thirty-Sixth AAAI Conference on Artificial Intelligence, 2022

2021
Guest Editorial: Automated Machine Learning.
IEEE Trans. Pattern Anal. Mach. Intell., 2021

Partially observable environment estimation with uplift inference for reinforcement learning based recommendation.
Mach. Learn., 2021

Machine learning steered symbolic execution framework for complex software code.
Formal Aspects Comput., 2021

Online Allocation with Two-sided Resource Constraints.
CoRR, 2021

LINDA: Multi-Agent Local Information Decomposition for Awareness of Teammates.
CoRR, 2021

Neural-to-Tree Policy Distillation with Policy Improvement Criterion.
CoRR, 2021

Imitate TheWorld: A Search Engine Simulation Platform.
CoRR, 2021

Nearly Minimax Optimal Adversarial Imitation Learning with Known and Unknown Transitions.
CoRR, 2021

Sparsity Prior Regularized Q-learning for Sparse Action Tasks.
CoRR, 2021

Regret Minimization Experience Replay.
CoRR, 2021

An Introduction of mini-AlphaStar.
CoRR, 2021

Derivative-Free Reinforcement Learning: A Review.
CoRR, 2021

NeoRL: A Near Real-World Benchmark for Offline Reinforcement Learning.
CoRR, 2021

On the robustness of median sampling in noisy evolutionary optimization.
Sci. China Inf. Sci., 2021

Analysis of Noisy Evolutionary Optimization When Sampling Fails.
Algorithmica, 2021

Improving Search Engine Efficiency through Contextual Factor Selection.
AI Mag., 2021

Adaptive Online Packing-guided Search for POMDPs.
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Regret Minimization Experience Replay in Off-Policy Reinforcement Learning.
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Offline Model-based Adaptable Policy Learning.
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Cross-modal Domain Adaptation for Cost-Efficient Visual Reinforcement Learning.
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Sequential and Dynamic constraint Contrastive Learning for Reinforcement Learning.
Proceedings of the International Joint Conference on Neural Networks, 2021

Fast Pareto Optimization for Subset Selection with Dynamic Cost Constraints.
Proceedings of the Thirtieth International Joint Conference on Artificial Intelligence, 2021

QPLEX: Duplex Dueling Multi-Agent Q-Learning.
Proceedings of the 9th International Conference on Learning Representations, 2021

Enhancing Context-Based Meta-Reinforcement Learning Algorithms via An Efficient Task Encoder (Student Abstract).
Proceedings of the Thirty-Fifth AAAI Conference on Artificial Intelligence, 2021

LB-DESPOT: Efficient Online POMDP Planning Considering Lower Bound in Action Selection (Student Abstract).
Proceedings of the Thirty-Fifth AAAI Conference on Artificial Intelligence, 2021

2020
Running time analysis of the (1+1)-EA for robust linear optimization.
Theor. Comput. Sci., 2020

A technical view on neural architecture search.
Int. J. Mach. Learn. Cybern., 2020

Validation Set Evaluation can be Wrong: An Evaluator-Generator Approach for Maximizing Online Performance of Ranking in E-commerce.
CoRR, 2020

Novelty-Prepared Few-Shot Classification.
CoRR, 2020

Temporal-adaptive Hierarchical Reinforcement Learning.
CoRR, 2020

Error Bounds of Imitating Policies and Environments.
Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Offline Imitation Learning with a Misspecified Simulator.
Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Derivative-Free Optimization with Adaptive Experience for Efficient Hyper-Parameter Tuning.
Proceedings of the ECAI 2020 - 24th European Conference on Artificial Intelligence, 29 August-8 September 2020, Santiago de Compostela, Spain, August 29 - September 8, 2020, 2020

Reinforcement Learning with Action-Specific Focuses in Video Games.
Proceedings of the IEEE Conference on Games, 2020

An Efficient Evolutionary Algorithm for Subset Selection with General Cost Constraints.
Proceedings of the Thirty-Fourth AAAI Conference on Artificial Intelligence, 2020

2019
Improving Fictitious Play Reinforcement Learning with Expanding Models.
CoRR, 2019

On Value Discrepancy of Imitation Learning.
CoRR, 2019

On the Robustness of Median Sampling in Noisy Evolutionary Optimization.
CoRR, 2019

Towards AutoML in the presence of Drift: first results.
CoRR, 2019

Efficient Reinforcement Learning with a Mind-Game for Full-Length StarCraft II.
CoRR, 2019

Maximizing submodular or monotone approximately submodular functions by multi-objective evolutionary algorithms.
Artif. Intell., 2019

Bridging Machine Learning and Logical Reasoning by Abductive Learning.
Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

Environment Reconstruction with Hidden Confounders for Reinforcement Learning based Recommendation.
Proceedings of the 25th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining, 2019

Reinforcement Learning Experience Reuse with Policy Residual Representation.
Proceedings of the Twenty-Eighth International Joint Conference on Artificial Intelligence, 2019

Cascaded Algorithm-Selection and Hyper-Parameter Optimization with Extreme-Region Upper Confidence Bound Bandit.
Proceedings of the Twenty-Eighth International Joint Conference on Artificial Intelligence, 2019

Only Image Cosine Embedding for Few-Shot Learning.
Proceedings of the Neural Information Processing - 26th International Conference, 2019

Asynchronous classification-based optimization.
Proceedings of the First International Conference on Distributed Artificial Intelligence, 2019

Reinforcement Learning with Derivative-Free Exploration.
Proceedings of the 18th International Conference on Autonomous Agents and MultiAgent Systems, 2019

Virtual-Taobao: Virtualizing Real-World Online Retail Environment for Reinforcement Learning.
Proceedings of the Thirty-Third AAAI Conference on Artificial Intelligence, 2019

On Reinforcement Learning for Full-Length Game of StarCraft.
Proceedings of the Thirty-Third AAAI Conference on Artificial Intelligence, 2019

Multi-Fidelity Automatic Hyper-Parameter Tuning via Transfer Series Expansion.
Proceedings of the Thirty-Third AAAI Conference on Artificial Intelligence, 2019

Evolutionary Learning: Advances in Theories and Algorithms
Springer, ISBN: 978-981-13-5955-2, 2019

2018
Reusable Reinforcement Learning via Shallow Trails.
IEEE Trans. Neural Networks Learn. Syst., 2018

Analyzing Evolutionary Optimization in Noisy Environments.
Evol. Comput., 2018

On the Effectiveness of Sampling for Evolutionary Optimization in Noisy Environments.
Evol. Comput., 2018

Taking Human out of Learning Applications: A Survey on Automated Machine Learning.
CoRR, 2018

Accelerating E-Commerce Search Engine Ranking by Contextual Factor Selection.
CoRR, 2018

Tunneling Neural Perception and Logic Reasoning through Abductive Learning.
CoRR, 2018

ZOOpt/ZOOjl: Toolbox for Derivative-Free Optimization.
CoRR, 2018

Multi-Layered Gradient Boosting Decision Trees.
Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018

Reinforcement Learning to Rank in E-Commerce Search Engine: Formalization, Analysis, and Application.
Proceedings of the 24th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining, 2018

Stabilizing Reinforcement Learning in Dynamic Environment with Application to Online Recommendation.
Proceedings of the 24th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining, 2018

Learning Environmental Calibration Actions for Policy Self-Evolution.
Proceedings of the Twenty-Seventh International Joint Conference on Artificial Intelligence, 2018

Mixture of GANs for Clustering.
Proceedings of the Twenty-Seventh International Joint Conference on Artificial Intelligence, 2018

Towards Sample Efficient Reinforcement Learning.
Proceedings of the Twenty-Seventh International Joint Conference on Artificial Intelligence, 2018

Approximation Guarantees of Stochastic Greedy Algorithms for Subset Selection.
Proceedings of the Twenty-Seventh International Joint Conference on Artificial Intelligence, 2018

Experienced Optimization with Reusable Directional Model for Hyper-Parameter Search.
Proceedings of the Twenty-Seventh International Joint Conference on Artificial Intelligence, 2018

An Alternating Minimization Approach to Optimizing Subarray Configuration for a Large Phased Array.
Proceedings of the 10th IEEE Sensor Array and Multichannel Signal Processing Workshop, 2018

Noisy Derivative-Free Optimization With Value Suppression.
Proceedings of the Thirty-Second AAAI Conference on Artificial Intelligence, 2018

2017
Maximizing Non-monotone/Non-submodular Functions by Multi-objective Evolutionary Algorithms.
CoRR, 2017

Open-Category Classification by Adversarial Sample Generation.
CoRR, 2017

Subset Selection under Noise.
Proceedings of the Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017, 2017

Binary Linear Compression for Multi-label Classification.
Proceedings of the Twenty-Sixth International Joint Conference on Artificial Intelligence, 2017

AGRA: An Analysis-Generation-Ranking Framework for Automatic Abbreviation from Paper Titles.
Proceedings of the Twenty-Sixth International Joint Conference on Artificial Intelligence, 2017

Open Category Classification by Adversarial Sample Generation.
Proceedings of the Twenty-Sixth International Joint Conference on Artificial Intelligence, 2017

Life-Stage Modeling by Customer-Manifold Embedding.
Proceedings of the Twenty-Sixth International Joint Conference on Artificial Intelligence, 2017

Optimizing Ratio of Monotone Set Functions.
Proceedings of the Twenty-Sixth International Joint Conference on Artificial Intelligence, 2017

On Subset Selection with General Cost Constraints.
Proceedings of the Twenty-Sixth International Joint Conference on Artificial Intelligence, 2017

Evolutionary multi-objective optimization made faster by sequential decomposition.
Proceedings of the 2017 IEEE Congress on Evolutionary Computation, 2017

Solving High-Dimensional Multi-Objective Optimization Problems with Low Effective Dimensions.
Proceedings of the Thirty-First AAAI Conference on Artificial Intelligence, 2017

Sequential Classification-Based Optimization for Direct Policy Search.
Proceedings of the Thirty-First AAAI Conference on Artificial Intelligence, 2017

2016
Exploring Multi-action Relationship in Reinforcement Learning.
Proceedings of the PRICAI 2016: Trends in Artificial Intelligence, 2016

Symbolic execution of complex program driven by machine learning based constraint solving.
Proceedings of the 31st IEEE/ACM International Conference on Automated Software Engineering, 2016

Parallel Pareto Optimization for Subset Selection.
Proceedings of the Twenty-Fifth International Joint Conference on Artificial Intelligence, 2016

Derivative-Free Optimization of High-Dimensional Non-Convex Functions by Sequential Random Embeddings.
Proceedings of the Twenty-Fifth International Joint Conference on Artificial Intelligence, 2016

A Lower Bound Analysis of Population-Based Evolutionary Algorithms for Pseudo-Boolean Functions.
Proceedings of the Intelligent Data Engineering and Automated Learning - IDEAL 2016, 2016

On sampling-and-classification optimization in discrete domains.
Proceedings of the IEEE Congress on Evolutionary Computation, 2016

A Multi-task Learning Approach by Combining Derivative-Free and Gradient Methods.
Proceedings of the Bio-inspired Computing - Theories and Applications, 2016

Boosting Nonparametric Policies.
Proceedings of the 2016 International Conference on Autonomous Agents & Multiagent Systems, 2016

Derivative-Free Optimization via Classification.
Proceedings of the Thirtieth AAAI Conference on Artificial Intelligence, 2016

Scaling Simultaneous Optimistic Optimization for High-Dimensional Non-Convex Functions with Low Effective Dimensions.
Proceedings of the Thirtieth AAAI Conference on Artificial Intelligence, 2016

2015
Switch Analysis for Running Time Analysis of Evolutionary Algorithms.
IEEE Trans. Evol. Comput., 2015

A two-layer surrogate-assisted particle swarm optimization algorithm.
Soft Comput., 2015

Variable solution structure can be helpful in evolutionary optimization.
Sci. China Inf. Sci., 2015

Subset Selection by Pareto Optimization.
Proceedings of the Advances in Neural Information Processing Systems 28: Annual Conference on Neural Information Processing Systems 2015, 2015

On Constrained Boolean Pareto Optimization.
Proceedings of the Twenty-Fourth International Joint Conference on Artificial Intelligence, 2015

Running time analysis: Convergence-based analysis reduces to switch analysis.
Proceedings of the IEEE Congress on Evolutionary Computation, 2015

Pareto Ensemble Pruning.
Proceedings of the Twenty-Ninth AAAI Conference on Artificial Intelligence, 2015

2014
On the Effectiveness of Sampling for Evolutionary Optimization in Noisy Environments.
Proceedings of the Parallel Problem Solving from Nature - PPSN XIII, 2014

The sampling-and-learning framework: A statistical view of evolutionary algorithms.
Proceedings of the IEEE Congress on Evolutionary Computation, 2014

Napping for functional representation of policy.
Proceedings of the International conference on Autonomous Agents and Multi-Agent Systems, 2014

Learning with Augmented Class by Exploiting Unlabeled Data.
Proceedings of the Twenty-Eighth AAAI Conference on Artificial Intelligence, 2014

2013
An analysis on recombination in multi-objective evolutionary optimization.
Artif. Intell., 2013

Self-Practice Imitation Learning from Weak Policy.
Proceedings of the Partially Supervised Learning - Second IAPR International Workshop, 2013

On the Approximation Ability of Evolutionary Optimization with Application to Minimum Set Cover: Extended Abstract.
Proceedings of the IJCAI 2013, 2013

2012
On the approximation ability of evolutionary optimization with application to minimum set cover.
Artif. Intell., 2012

On Algorithm-Dependent Boundary Case Identification for Problem Classes.
Proceedings of the Parallel Problem Solving from Nature - PPSN XII, 2012

Diversity Regularized Ensemble Pruning.
Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2012

Multi-label hypothesis reuse.
Proceedings of the 18th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2012

2011
Towards Analyzing Crossover Operators in Evolutionary Search via General Markov Chain Switching Theorem
CoRR, 2011

Diversity Regularized Machine.
Proceedings of the IJCAI 2011, 2011

Lifted-Rollout for Approximate Policy Iteration of Markov Decision Process.
Proceedings of the Data Mining Workshops (ICDMW), 2011

Collisions are helpful for computing unique input-output sequences.
Proceedings of the 13th Annual Genetic and Evolutionary Computation Conference, 2011

2010
A framework for modeling positive class expansion with single snapshot.
Knowl. Inf. Syst., 2010

Evolutionary Algorithms as Guaranteed Approximation Optimizers
CoRR, 2010

Towards Analyzing Recombination Operators in Evolutionary Search.
Proceedings of the Parallel Problem Solving from Nature, 2010

2009
Semi-naive Exploitation of One-Dependence Estimators.
Proceedings of the ICDM 2009, 2009

2008
Spectrum of Variable-Random Trees.
J. Artif. Intell. Res., 2008

A new approach to estimating the expected first hitting time of evolutionary algorithms.
Artif. Intell., 2008

TEFE: A Time-Efficient Approach to Feature Extraction.
Proceedings of the 8th IEEE International Conference on Data Mining (ICDM 2008), 2008

On the usefulness of infeasible solutions in evolutionary search: A theoretical study.
Proceedings of the IEEE Congress on Evolutionary Computation, 2008

2007
Predicting Future Customers via Ensembling Gradually Expanded Trees.
Int. J. Data Warehous. Min., 2007

Cocktail Ensemble for Regression.
Proceedings of the 7th IEEE International Conference on Data Mining (ICDM 2007), 2007

2005
Ensembling local learners ThroughMultimodal perturbation.
IEEE Trans. Syst. Man Cybern. Part B, 2005

Adapt Bagging to Nearest Neighbor Classifiers.
J. Comput. Sci. Technol., 2005


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