Showing 1 - 20 results of 62 for search 'Kaelbling, Leslie P', query time: 0.12s Refine Results
  1. 1
    The foundation of efficient robot learning
    by Kaelbling, Leslie P
    Published 2021
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  2. 2
    Tracking the spin on a ping pong ball with the quaternion Bingham filter
    by Glover, Jared, Kaelbling, Leslie P.
    Published 2016
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  3. 3
    Elimination of All Bad Local Minima in Deep Learning
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  4. 4
    Adversarially-learned Inference via an Ensemble of Discrete Undirected Graphical Models
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  5. 5
    Unifying perception, estimation and action for mobile manipulation via belief space planning
    Other Authors: “...Kaelbling, Leslie P....”
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  6. 6
    Segmentation according to natural examples: Learning static segmentation from motion segmentation
    Other Authors: “...Kaelbling, Leslie P....”
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  7. 7
    A constraint-based method for solving sequential manipulation planning problems
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  8. 8
    Integrated task and motion planning in belief space
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  9. 9
    Every Local Minimum Value Is the Global Minimum Value of Induced Model in Nonconvex Machine Learning
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  10. 10
    Regret bounds for meta Bayesian optimization with an unknown Gaussian process prior
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  11. 11
    Regret bounds for meta Bayesian optimization with an unknown Gaussian process prior
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  12. 12
    Robust grasping under object pose uncertainty
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  13. 13
    Hierarchical Solution of Large Markov Decision Processes
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  14. 14
    Adversarial Actor-Critic Method for Task and Motion Planning Problems Using Planning Experience
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  15. 15
    Hierarchical planning for multi-contact non-prehensile manipulation
    Other Authors: “...Kaelbling, Leslie P...”
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  16. 16
    Symbol acquisition for probabilistic high-level planning
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  17. 17
    Guiding search in continuous state-action spaces by learning an action sampler from off-target search experience
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  18. 18
    A hierarchical approach to manipulation with diverse actions
    Other Authors: “...Kaelbling, Leslie P....”
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  19. 19
    Learning to acquire information
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  20. 20
    Learning to guide task and motion planning using score-space representation
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