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2019

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Publications | Results For: 2019
Choy, Christopher, JunYoung Gwak, and Silvio Savarese. “4D Spatio-Temporal ConvNet: Minkowski Convolutional Neural Network”. IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2019.
Chen, Kevin, Juan Pablo de Vicente, Gabriel Sepulveda, Xia Fei, Alvaro Soto, Marynel Vazquez, and Silvio Savarese. “A Behavioral Approach to Visual Navigation With Graph Localization Networks}”, Robotics: Science and Systems (RSS).
Salazar, M., M. Tsao, I. Aguiar, M. Schiffer, and M. Pavone. “A Congestion-Aware Routing Scheme for Autonomous Mobility-on-Demand Systems”. European Control Conference, 2019.
Zgraggen, J., Matthew Tsao, M. Salazar, M. Schiffer, and Marco Pavone. “A Model Predictive Control Scheme for Intermodal Autonomous Mobility-on-Demand”. IEEE Int. Conf. on Intelligent Transportation Systems, 2019.
Kurenkov, Andrey, Ajay Mandlekar, Roberto Martin-Martin, Silvio Savarese, and Animesh Garg. “AC-Teach: A Bayesian Actor-Critic Method for Policy Learning With an Ensemble of Suboptimal Teachers”. Conference on Robot Learning (CoRL), 2019.
Basu, Chandrayee, Erdem Biyik, Zhixun He, Mukesh Singhal, and Dorsa Sadigh. “Active Learning of Reward Dynamics from Hierarchical Queries”. IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), 2019.
Ren, Hongyu, Shengjia Zhao, and Stefano Ermon. “Adaptive Antithetic Sampling for Variance Reduction”. International Conference on Machine Learning, 2019.
Park, Junwon, Ranjay Krishna, Pranav Khadpe, Fei-Fei Li, and Michael Bernstein. “AI-Based Request Augmentation to Increase Crowdsourcing Participation”. AAAI Conference on Human Computation and Crowdsourcing (HCOMP), 2019.
Sagawa, Shiori, Pang Wei Koh, Tatsunori Hashimoto, and Percy Liang. “An Empirical Study of Generalization in Distributionally Robust Neural Networks”.
Bao, Yajie, Yang Li, Shao-Lun Huang, Lin Zhang, Lizhong Zheng, Amir Zamir, and Leonidas Guibas. “An Information-Theoretic Approach to Transferability in Task Transfer Learning”. IEEE International Conference on Image Processing (ICIP), 2019.
Biyik, Erdem, Malayandi Palan, Nicholas Landolfi, Dylan Losey, and Dorsa Sadigh. “Asking Easy Questions: A User-Friendly Approach to Active Reward Learning”. Conference on Robot Learning (CoRL), 2019.
Leung, K., Nikos Arechiga, and Marco Pavone. “Backpropagation for Parametric STL”. IEEE Intelligent Vehicles Symposium, Workshop on Unsupervised Learning for Automated Driving, 2019.
Ivanovic, Boris, James Harrison, A. Sharma, Mo Chen, and Marco Pavone. “BaRC: Backward Reachability Curriculum for Robotic Reinforcement Learning”. IEEE International Conference on Robotics and Automation (ICRA), 2019.
Biyik, Erdem, Kenneth Wang, Nima Anari, and Dorsa Sadigh. “Batch Active Learning Using Determinantal Point Processes”, arXiv preprint arXiv:1906.07975.
Jorda, Mikael, Elena Galbally Herrero, and Oussama Khatib. “Contact-Driven Posture Behavior for Safe and Interactive Robot Operation”. IEEE International Conference on Robotics and Automation (ICRA), 2019.
Huang, De-An, Danfei Xu, Yuke Zhu, Animesh Garg, Silvio Savarese, Fei-Fei Li, and Juan Carlos Niebles. “Continuous Relaxation of Symbolic Planner for One-Shot Imitation Learning”. IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), 2019.
Emmons, John, Sadjad Fouladi, Ganesh Ananthanarayanan, Shivaram Venkataraman, Silvio Savarese, and Keith Winstein. “Cracking Open the {DNN} Black-Box: Video Analytics With {DNNs} across the Camera-Cloud Boundary”. Workshop on Hot Topics in Video Analytics and Intelligent Edges (HotEdgeVideo), 2019.
Chang, Chien-Yi, De-An Huang, Yanan Sui, Fei-Fei Li, and Juan Carlos Niebles. “D3TW: Discriminative Differentiable Dynamic Time Warping for Weakly Supervised Action Alignment and Segmentation”. IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2019.
Wei, Colin, and Tengyu Ma. “Data-Dependent Sample Complexity of Deep Neural Networks via Lipschitz Augmentation”. Advances in Neural Information Processing Systems, 2019.
Jedoui, Khaled, Ranjay Krishna, Michael Bernstein, and Fei-Fei Li. “Deep Bayesian Active Learning for Multiple Correct Outputs”. IEEE Conference on Computer Vision and Pattern Recognition, 2019.