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Welcome to LAMDA-BBO Group 👋

We are the LAMDA-BBO (Black-Box Optimization) group, led by Professor Chao Qian. Our group is a part of LAMDA Group @ Nanjing University, which is led by Professor Zhi-Hua Zhou.

Our research focuses on advancing the theories, algorithms, and applications of black-box optimization. Our key areas of interest include, but are not limited to:

  • Theoretical analysis of evolutionary algorithms
  • Designing safe evolutionary algorithms, i.e., evolutionary algorithms with provable approximation guarantee
  • Designing efficient black-box optimization algorithms, e.g., Bayesian optimization, evolutionary strategies, evolutionary gradient optimization, cooperative coevolution, and learning to optimize
  • Evolutionary learning, particularly evolutionary reinforcement learning, deep learning, and ensemble learning
  • Applications to solve real-world complex optimziation problems, e.g., in wireless network, electronic design automation, and geoscience

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  1. MCTS-VS MCTS-VS Public

    Official implementation of NeurIPS'22 paper "Monte Carlo Tree Search based Variable Selection for High-Dimensional Bayesian Optimization"

    Python 30 6

  2. madac madac Public

    Official implementation of NeurIPS22 paper “Multi-agent Dynamic Algorithm Configuration”

    Python 23 7

  3. WireMask-BBO WireMask-BBO Public

    Official implementation of NeurIPS'23 paper "Macro Placement by Wire-Mask-Guided Black-Box Optimization"

    Perl 16 4

  4. CCQD CCQD Public

    Official implementation of ICLR'24 spotlight paper "Sample-Efficient Quality-Diversity by Cooperative Coevolution".

    Python 4

  5. ELG ELG Public

    Forked from gaocrr/ELG

    Official implementation of IJCAI'24 paper "Towards Generalizable Neural Solvers for Vehicle Routing Problems via Ensemble with Transferrable Local Policy"

    Python 4

  6. offline-moo offline-moo Public

    Official implementation of ICML'24 paper "Offline Multi-Objective Optimization".

    Python 16 4

Repositories

Showing 10 of 15 repositories
  • lamda-bbo/neural-solver-selection’s past year of commit activity
    Python 3 MIT 0 0 0 Updated Oct 16, 2024
  • offline-moo Public

    Official implementation of ICML'24 paper "Offline Multi-Objective Optimization".

    lamda-bbo/offline-moo’s past year of commit activity
    Python 16 4 2 0 Updated Oct 16, 2024
  • .github Public
    lamda-bbo/.github’s past year of commit activity
    0 0 0 0 Updated Aug 26, 2024
  • MR-EMO Public
    lamda-bbo/MR-EMO’s past year of commit activity
    Python 0 0 0 0 Updated Aug 26, 2024
  • PVD-EMO Public

    Official implementation of IJCAI'24 paper "Peptide Vaccine Design by Evolutionary Multi-objective Optimization."

    lamda-bbo/PVD-EMO’s past year of commit activity
    Python 0 1 0 0 Updated Jun 17, 2024
  • BPODC Public

    Official implementation of PPSN'24 paper "Biased Pareto Optimization for Subset Selection with Dynamic Cost Constraints"

    lamda-bbo/BPODC’s past year of commit activity
    Python 1 0 0 0 Updated Jun 17, 2024
  • RefQD Public

    Official repository of ICML'24 paper "Quality-Diversity with Limited Resources".

    lamda-bbo/RefQD’s past year of commit activity
    Python 3 MIT 0 0 0 Updated Jun 9, 2024
  • CCL-SC Public

    Official implementation of ICML'24 paper Confidence-aware Contrastive Learning for Selective Classification.

    lamda-bbo/CCL-SC’s past year of commit activity
    Python 6 MIT 1 2 0 Updated Jun 3, 2024
  • ELG Public Forked from gaocrr/ELG

    Official implementation of IJCAI'24 paper "Towards Generalizable Neural Solvers for Vehicle Routing Problems via Ensemble with Transferrable Local Policy"

    lamda-bbo/ELG’s past year of commit activity
    Python 4 MIT 6 0 0 Updated May 20, 2024
  • CCQD Public

    Official implementation of ICLR'24 spotlight paper "Sample-Efficient Quality-Diversity by Cooperative Coevolution".

    lamda-bbo/CCQD’s past year of commit activity
    Python 4 MIT 0 0 0 Updated Mar 6, 2024

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