Daniel Ho

According to our database, Daniel Ho authored at least 22 papers between 1995 and 2023.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of three.

2023

Deep RL at Scale: Sorting Waste in Office Buildings with a Fleet of Mobile Manipulators.

Alexander Herzog, Kanishka Rao, Karol Hausman, Yao Lu, Paul Wohlhart, Mengyuan Yan, Jessica Lin, Montserrat Gonzalez Arenas, Ted Xiao, Daniel Kappler, Daniel Ho, Jarek Rettinghouse, Yevgen Chebotar, Kuang-Huei Lee, Keerthana Gopalakrishnan, Ryan Julian, Adrian Li, Chuyuan Kelly Fu, Bob Wei, Sangeetha Ramesh, Khem Holden, Kim Kleiven, David Rendleman, Sean Kirmani, Jeff Bingham, Jonathan Weisz, Ying Xu, Wenlong Lu, Matthew Bennice, Cody Fong, David Do, Jessica Lam, Yunfei Bai, Benjie Holson, Michael Quinlan, Noah Brown, Mrinal Kalakrishnan, Julian Ibarz, Peter Pastor, Sergey Levine

CoRR, 2023

Deep RL at Scale: Sorting Waste in Office Buildings with a Fleet of Mobile Manipulators.

Alexander Herzog, Kanishka Rao, Karol Hausman, Yao Lu, Paul Wohlhart, Mengyuan Yan, Jessica Lin, Montserrat Gonzalez Arenas, Ted Xiao, Daniel Kappler, Daniel Ho, Jarek Rettinghouse, Yevgen Chebotar, Kuang-Huei Lee, Keerthana Gopalakrishnan, Ryan Julian, Adrian Li, Chuyuan Fu, Bob Wei, Sangeetha Ramesh, Khem Holden, Kim Kleiven, David J. Rendleman, Sean Kirmani, Jeffrey Bingham, Jonathan Weisz, Ying Xu, Wenlong Lu, Matthew Bennice, Cody Fong, David Do, Jessica Lam, Yunfei Bai, Benjie Holson, Michael Quinlan, Noah Brown, Mrinal Kalakrishnan, Julian Ibarz, Peter Pastor, Sergey Levine

Proceedings of the Robotics: Science and Systems XIX, Daegu, 2023

Practical Visual Deep Imitation Learning via Task-Level Domain Consistency.

Mohi Khansari, Daniel Ho, Yuqing Du, Armando Fuentes, Matthew Bennice, Nicolas Sievers, Sean Kirmani, Yunfei Bai, Eric Jang

Proceedings of the IEEE International Conference on Robotics and Automation, 2023

Asking for Help: Failure Prediction in Behavioral Cloning through Value Approximation.

Cem Gokmen, Daniel Ho, Mohi Khansari

Proceedings of the IEEE International Conference on Robotics and Automation, 2023

2022

Do As I Can, Not As I Say: Grounding Language in Robotic Affordances.

Michael Ahn, Anthony Brohan, Noah Brown, Yevgen Chebotar, Omar Cortes, Byron David, Chelsea Finn, Keerthana Gopalakrishnan, Karol Hausman, Alexander Herzog, Daniel Ho, Jasmine Hsu, Julian Ibarz, Brian Ichter, Alex Irpan, Eric Jang, Rosario Jauregui Ruano, Kyle Jeffrey, Sally Jesmonth, Nikhil J. Joshi, Ryan Julian, Dmitry Kalashnikov, Yuheng Kuang, Kuang-Huei Lee, Sergey Levine, Yao Lu, Linda Luu, Carolina Parada, Peter Pastor, Jornell Quiambao, Kanishka Rao, Jarek Rettinghouse, Diego Reyes, Pierre Sermanet, Nicolas Sievers, Clayton Tan, Alexander Toshev, Vincent Vanhoucke, Fei Xia, Ted Xiao, Peng Xu, Sichun Xu, Mengyuan Yan

CoRR, 2022

Practical Imitation Learning in the Real World via Task Consistency Loss.

Mohi Khansari, Daniel Ho, Yuqing Du, Armando Fuentes, Matthew Bennice, Nicolas Sievers, Sean Kirmani, Yunfei Bai, Eric Jang

CoRR, 2022

Bayesian Imitation Learning for End-to-End Mobile Manipulation.

Yuqing Du, Daniel Ho, Alex Alemi, Eric Jang, Mohi Khansari

Proceedings of the International Conference on Machine Learning, 2022

Do As I Can, Not As I Say: Grounding Language in Robotic Affordances.

Brian Ichter, Anthony Brohan, Yevgen Chebotar, Chelsea Finn, Karol Hausman, Alexander Herzog, Daniel Ho, Julian Ibarz, Alex Irpan, Eric Jang, Ryan Julian, Dmitry Kalashnikov, Sergey Levine, Yao Lu, Carolina Parada, Kanishka Rao, Pierre Sermanet, Alexander Toshev, Vincent Vanhoucke, Fei Xia, Ted Xiao, Peng Xu, Mengyuan Yan, Noah Brown, Michael Ahn, Omar Cortes, Nicolas Sievers, Clayton Tan, Sichun Xu, Diego Reyes, Jarek Rettinghouse, Jornell Quiambao, Peter Pastor, Linda Luu, Kuang-Huei Lee, Yuheng Kuang, Sally Jesmonth, Nikhil J. Joshi, Kyle Jeffrey, Rosario Jauregui Ruano, Jasmine Hsu, Keerthana Gopalakrishnan, Byron David, Andy Zeng, Chuyuan Kelly Fu

Proceedings of the Conference on Robot Learning, 2022

2021

First-Generation Inference Accelerator Deployment at Facebook.

Michael J. Anderson, Benny Chen, Stephen Chen, Summer Deng, Jordan Fix, Michael Gschwind, Aravind Kalaiah, Changkyu Kim, Jaewon Lee, Jason Liang, Haixin Liu, Yinghai Lu, Jack Montgomery, Arun Moorthy, Nadathur Satish, Sam Naghshineh, Avinash Nayak, Jongsoo Park, Chris Petersen, Martin Schatz, Narayanan Sundaram, Bangsheng Tang, Peter Tang, Amy Yang, Jiecao Yu, Hector Yuen, Ying Zhang, Aravind Anbudurai, Vandana Balan, Harsha Bojja, Joe Boyd, Matthew Breitbach, Claudio Caldato, Anna Calvo, Garret Catron, Sneh Chandwani, Panos Christeas, Brad Cottel, Brian Coutinho, Arun Dalli, Abhishek Dhanotia, Oniel Duncan, Roman Dzhabarov, Simon Elmir, Chunli Fu, Wenyin Fu, Michael Fulthorp, Adi Gangidi, Nick Gibson, Sean Gordon, Beatriz Padilla Hernandez, Daniel Ho, Yu-Cheng Huang, Olof Johansson, Shishir Juluri, et al.

CoRR, 2021

COCOI: Contact-aware Online Context Inference for Generalizable Non-planar Pushing.

Zhuo Xu, Wenhao Yu, Alexander Herzog, Wenlong Lu, Chuyuan Fu, Masayoshi Tomizuka, Yunfei Bai, C. Karen Liu, Daniel Ho

Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems, 2021

RetinaGAN: An Object-aware Approach to Sim-to-Real Transfer.

Daniel Ho, Kanishka Rao, Zhuo Xu, Eric Jang, Mohi Khansari, Yunfei Bai

Proceedings of the IEEE International Conference on Robotics and Automation, 2021

SimGAN: Hybrid Simulator Identification for Domain Adaptation via Adversarial Reinforcement Learning.

Yifeng Jiang, Tingnan Zhang, Daniel Ho, Yunfei Bai, C. Karen Liu, Sergey Levine, Jie Tan

Proceedings of the IEEE International Conference on Robotics and Automation, 2021

NBDT: Neural-Backed Decision Tree.

Alvin Wan, Lisa Dunlap, Daniel Ho, Jihan Yin, Scott Lee, Suzanne Petryk, Sarah Adel Bargal, Joseph E. Gonzalez

Proceedings of the 9th International Conference on Learning Representations, 2021

RICA: Evaluating Robust Inference Capabilities Based on Commonsense Axioms.

Pei Zhou, Rahul Khanna, Seyeon Lee, Bill Yuchen Lin, Daniel Ho, Jay Pujara, Xiang Ren

Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing, 2021

2020

SegNBDT: Visual Decision Rules for Segmentation.

Alvin Wan, Daniel Ho, Younjin Song, Henk Tillman, Sarah Adel Bargal, Joseph E. Gonzalez

CoRR, 2020

Can BERT Reason? Logically Equivalent Probes for Evaluating the Inference Capabilities of Language Models.

Pei Zhou, Rahul Khanna, Bill Yuchen Lin, Daniel Ho, Xiang Ren, Jay Pujara

CoRR, 2020

NBDT: Neural-Backed Decision Trees.

Alvin Wan, Lisa Dunlap, Daniel Ho, Jihan Yin, Scott Lee, Henry Jin, Suzanne Petryk, Sarah Adel Bargal, Joseph E. Gonzalez

CoRR, 2020

2019

Population Based Augmentation: Efficient Learning of Augmentation Policy Schedules.

Daniel Ho, Eric Liang, Xi Chen, Ion Stoica, Pieter Abbeel

Proceedings of the 36th International Conference on Machine Learning, 2019

OpenArm 2.0: Automated Segmentation of 3D Tissue Structures for Multi-Subject Study of Muscle Deformation Dynamics.

Yonatan Nozik, Laura A. Hallock, Daniel Ho, Sai Mandava, Chris Mitchell, Thomas Hui Li, Ruzena Bajcsy

Proceedings of the 41st Annual International Conference of the IEEE Engineering in Medicine and Biology Society, 2019

2018

Improvements to Context Based Self-Supervised Learning.

T. Nathan Mundhenk, Daniel Ho, Barry Y. Chen

Proceedings of the 2018 IEEE Conference on Computer Vision and Pattern Recognition, 2018

2016

IRNdb: the database of immunologically relevant non-coding RNAs.

Elena Denisenko, Daniel Ho, Ousman Tamgue, Mumin Ozturk, Harukazu Suzuki, Frank Brombacher, Reto Guler, Sebastian Schmeier

Database J. Biol. Databases Curation, 2016

1995

The Impact of Information Technology on the Accountancy Profession in Hong Kong.

Daniel Ho, Wing-hung Tam

Proceedings of the Second Pacific Asia Conference on Information Systems, 1995