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ORCIDDaniel Ho
Person information
Other persons with a similar name
- Daniel Sai Ho Chung
- Alvin Daniel Ho
- Daniel Chi Wing Ho
- Daniel E. Ho
![[0000-0002-2195-5469]](/googleai/decoding-https-dblp.org/img/orcid-mark.12x12.png "0000-0002-2195-5469")
— Stanford University, CA, USA - Daniel H. Ho
- Daniel M. Ho
- Daniel W. C. Ho (aka: Daniel Wing Cheong Ho) — City University of Hong Kong
- Daniel Ho Teck Khieng
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2020 – today
- 2023
[c14]Mohi Khansari, Daniel Ho, Yuqing Du, Armando Fuentes, Matthew Bennice, Nicolas Sievers, Sean Kirmani, Yunfei Bai, Eric Jang:
Practical Visual Deep Imitation Learning via Task-Level Domain Consistency. ICRA 2023: 1837-1844- [c13]Cem Gokmen, Daniel Ho, Mohi Khansari:
Asking for Help: Failure Prediction in Behavioral Cloning through Value Approximation. ICRA 2023: 5821-5828 - [c12]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 T. 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:
Deep RL at Scale: Sorting Waste in Office Buildings with a Fleet of Mobile Manipulators. Robotics: Science and Systems 2023 - [i14]Cem Gokmen, Daniel Ho, Mohi Khansari:
Asking for Help: Failure Prediction in Behavioral Cloning through Value Approximation. CoRR abs/2302.04334 (2023) - [i13]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, Jeffrey T. 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:
Deep RL at Scale: Sorting Waste in Office Buildings with a Fleet of Mobile Manipulators. CoRR abs/2305.03270 (2023) - 2022
- [c11]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:
Do As I Can, Not As I Say: Grounding Language in Robotic Affordances. CoRL 2022: 287-318 - [c10]Yuqing Du, Daniel Ho, Alex Alemi, Eric Jang, Mohi Khansari:
Bayesian Imitation Learning for End-to-End Mobile Manipulation. ICML 2022: 5531-5546 - [i12]Mohi Khansari, Daniel Ho, Yuqing Du, Armando Fuentes, Matthew Bennice, Nicolas Sievers, Sean Kirmani, Yunfei Bai, Eric Jang:
Practical Imitation Learning in the Real World via Task Consistency Loss. CoRR abs/2202.01862 (2022) - [i11]Yuqing Du, Daniel Ho, Alexander A. Alemi, Eric Jang, Mohi Khansari:
Bayesian Imitation Learning for End-to-End Mobile Manipulation. CoRR abs/2202.07600 (2022) - [i10]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:
Do As I Can, Not As I Say: Grounding Language in Robotic Affordances. CoRR abs/2204.01691 (2022) - 2021
- [c9]Pei Zhou, Rahul Khanna, Seyeon Lee, Bill Yuchen Lin, Daniel Ho, Jay Pujara, Xiang Ren:
RICA: Evaluating Robust Inference Capabilities Based on Commonsense Axioms. EMNLP (1) 2021: 7560-7579 - [c8]Alvin Wan, Lisa Dunlap, Daniel Ho, Jihan Yin, Scott Lee, Suzanne Petryk, Sarah Adel Bargal, Joseph E. Gonzalez:
NBDT: Neural-Backed Decision Tree. ICLR 2021 - [c7]Yifeng Jiang, Tingnan Zhang, Daniel Ho, Yunfei Bai, C. Karen Liu, Sergey Levine, Jie Tan:
SimGAN: Hybrid Simulator Identification for Domain Adaptation via Adversarial Reinforcement Learning. ICRA 2021: 2884-2890 - [c6]Daniel Ho, Kanishka Rao, Zhuo Xu, Eric Jang, Mohi Khansari, Yunfei Bai:
RetinaGAN: An Object-aware Approach to Sim-to-Real Transfer. ICRA 2021: 10920-10926 - [c5]Zhuo Xu, Wenhao Yu, Alexander Herzog, Wenlong Lu, Chuyuan Fu, Masayoshi Tomizuka, Yunfei Bai, C. Karen Liu, Daniel Ho:
COCOI: Contact-aware Online Context Inference for Generalizable Non-planar Pushing. IROS 2021: 176-182 - [i9]Yifeng Jiang, Tingnan Zhang, Daniel Ho, Yunfei Bai, C. Karen Liu, Sergey Levine, Jie Tan:
SimGAN: Hybrid Simulator Identification for Domain Adaptation via Adversarial Reinforcement Learning. CoRR abs/2101.06005 (2021) - [i8]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.:
First-Generation Inference Accelerator Deployment at Facebook. CoRR abs/2107.04140 (2021) - 2020
- [i7]Alvin Wan, Lisa Dunlap, Daniel Ho, Jihan Yin, Scott Lee, Henry Jin, Suzanne Petryk, Sarah Adel Bargal, Joseph E. Gonzalez:
NBDT: Neural-Backed Decision Trees. CoRR abs/2004.00221 (2020) - [i6]Pei Zhou, Rahul Khanna, Bill Yuchen Lin, Daniel Ho, Xiang Ren, Jay Pujara:
Can BERT Reason? Logically Equivalent Probes for Evaluating the Inference Capabilities of Language Models. CoRR abs/2005.00782 (2020) - [i5]Alvin Wan, Daniel Ho, Younjin Song, Henk Tillman, Sarah Adel Bargal, Joseph E. Gonzalez:
SegNBDT: Visual Decision Rules for Segmentation. CoRR abs/2006.06868 (2020) - [i4]Daniel Ho, Kanishka Rao, Zhuo Xu, Eric Jang, Mohi Khansari, Yunfei Bai:
RetinaGAN: An Object-aware Approach to Sim-to-Real Transfer. CoRR abs/2011.03148 (2020) - [i3]Zhuo Xu, Wenhao Yu, Alexander Herzog, Wenlong Lu, Chuyuan Fu, Masayoshi Tomizuka, Yunfei Bai, C. Karen Liu, Daniel Ho:
COCOI: Contact-aware Online Context Inference for Generalizable Non-planar Pushing. CoRR abs/2011.11270 (2020)
2010 – 2019
- 2019
- [c4]Yonatan Nozik, Laura A. Hallock, Daniel Ho, Sai Mandava, Chris Mitchell, Thomas Hui Li, Ruzena Bajcsy:
OpenArm 2.0: Automated Segmentation of 3D Tissue Structures for Multi-Subject Study of Muscle Deformation Dynamics. EMBC 2019: 982-988 - [c3]Daniel Ho, Eric Liang, Xi Chen, Ion Stoica, Pieter Abbeel:
Population Based Augmentation: Efficient Learning of Augmentation Policy Schedules. ICML 2019: 2731-2741 - [i2]Daniel Ho, Eric Liang, Ion Stoica, Pieter Abbeel, Xi Chen:
Population Based Augmentation: Efficient Learning of Augmentation Policy Schedules. CoRR abs/1905.05393 (2019) - 2018
- [c2]T. Nathan Mundhenk, Daniel Ho, Barry Y. Chen:
Improvements to Context Based Self-Supervised Learning. CVPR 2018: 9339-9348 - 2017
- [i1]T. Nathan Mundhenk, Daniel Ho, Barry Y. Chen:
Improvements to context based self-supervised learning. CoRR abs/1711.06379 (2017) - 2016
- [j1]Elena Denisenko, Daniel Ho, Ousman Tamgue, Mumin Ozturk, Harukazu Suzuki, Frank Brombacher, Reto Guler, Sebastian Schmeier:
IRNdb: the database of immunologically relevant non-coding RNAs. Database J. Biol. Databases Curation 2016 (2016)
1990 – 1999
- 1995
- [c1]Daniel Ho, Wing-hung Tam:
The Impact of Information Technology on the Accountancy Profession in Hong Kong. PACIS 1995: 97
Coauthor Index
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