2018
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Results for: 2018
- Ivanovic, Boris, E. Schmerling, K. Leung, and M. Pavone. “Generative Modeling of Multimodal Multi-Human Behavior”. International Conference on Intelligent Robots and Systems (IROS), 2018.
- Xia, Fei, Amir Zamir, Zhiyanng He, Alexander Sax, Jitendra Malik, and Silvio Savarese. “Gibson Env: Real-World Perception for Embodied Agents”. IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2018.
- Hirose, Noriaki, Amir Sadeghian, Marynel Vazquez, Patrick Goebel, and Silvio Savarese. “GONet: A Semi-Supervised Deep Learning Approach For Traversability Estimation”, arXiv preprint arXiv:1803.03254.
- Paredes, P., Y. Zhou, N. Hamdan, Stephanie Balters, E. Murnane, W. Ju, and J. Landay. “Just Breathe: In-Car Interventions for Guided Slow Breathing”. ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies, 2018.
- Ma, Rui, Akshay Gadi Patil, Matthew Fisher, Manyi Li, Soren Pirk, Binh-Son Hua, Sai-Kit Yeung, Xin Tong, Leonidas Guibas, and Hao Zhang. “Language-Driven Synthesis of 3D Scenes from Scene Databases”, ACM Transactions on Graphics (Proc. SIGGRAPH ASIA).
- Duchi, John, and Hongseok Namkoong. “Learning Models With Uniform Performance via Distributionally Robust Optimization”, arXiv preprint arXiv:1810.08750.
- Fang, Kuan, Yuke Zhu, Animesh Garg, Andrey Kurenkov, Mehta Viraj, Fei-Fei Li, and Silvio Savarese. “Learning Task-Oriented Grasping for Tool Manipulation from Simulated Self-Supervision”, arXiv preprint arXiv:1806.09266.
- Rong, Kexin, Clara Yoon, Karianne Bergen, Hashem Elezabi, Peter Bailis, Philip Levis, and Gregory Beroza. “Locality-Sensitive Hashing for Earthquake Detection: A Case Study of Scaling Data-Driven Science”, Proc. VLDB Endow.
- Bailis, Peter, Edward Gan, S. Madden, D. Narayanan, K. Rong, and S. Suri. “MacroBase: Prioritizing Attention in Fast Data”, ACM TODS, Best of SIGMOD 2017 Special Issue.
- Harrison, James, Apoorva Sharma, and Marco Pavone. “Meta-Learning Priors for Efficient Online Bayesian Regression”, Workshop on the Algorithmic Foundations of Robotics (WAFR).
- Sax, Alexander, Bradley Emi, Amir Zamir, Leonidas Guibas, Silvio Savarese, and Malik Jitendra. “Mid-Level Visual Representations Improve Generalization and Sample Efficiency for Learning Active Tasks”. arXiv, 2018.
- Kang, Daniel, Deepti Raghavan, Peter Bailis, and Matei Zaharia. “Model Assertions for Debugging Machine Learning”. NIPS ML Systems Workshop, 2018.
- Ivanovic, Boris, and Marco Pavone. “Modeling Multimodal Dynamic Spatiotemporal Graphs”. arXiv, 2018.
- Gan, Edward, Jialin Ding, Kai Sheng Tai, Vatsal Sharan, and Peter Bailis. “Moment-Based Quantile Sketches for Efficient High Cardinality Aggregation Queries”, Proc. VLDB Endow.
- Song, Jiaming, Hongyu Ren, Dorsa Sadigh, and Stefano Ermon. “Multi-Agent Generative Adversarial Imitation Learning”. Advances in Neural Information Processing Systems, 2018.
- Bhattacharyya, R., D. Phillips, B. Wulfe, J. Morton, A. Kuefler, and M. Kochenderfer. “Multi-Agent Imitation Learning for Driving Simulation”. IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), 2018.
- Schmerling, E., K. Leung, W. Vollprecht, and M. Pavone. “Multimodal Probabilistic Model-Based Planning for Human-Robot Interaction”. International Conference on Robotics and Automation (ICRA), 2018.
- Huang, De-An, Suraj Nair, Danfei Xu, Yuke Zhu, Amimesh Garg, Fei-Fei Li, Silvio Savarese, and Juan Carlos Niebles. “Neural Task Graphs: Generalizing to Unseen Tasks from a Single Video Demonstration”. IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2018.
- Xu, Danfei, Suraj Nair, Yuke Zhu, J. Gao, Animesh Garg, Fei-Fei Li, and Silvio Savarese. “Neural Task Programming: Learning to Generalize Across Hierarchical Tasks”. International Conference on Robotics and Automation (ICRA), 2018.
- Leung, K., E. Schmerling, Mo Chen, J. Tilbot, J. Gerdes, and Marco Pavone. “On Infusing Reachability-Based Safety Assurance Within Probabilistic Planning Frameworks for Human-Robot Vehicle Interactions”. Int. Symp. on Experimental Robotics, 2018.