Daniel Ho

Publication Activity (10 Years)

Years Active: 1995-2023
Publications (10 Years): 32

Top Topics

Automated Segmentation

Failure Prediction

Imitation Learning

Top Venues

Publications

Cem Gokmen, Daniel Ho, Mohi Khansari
Asking for Help: Failure Prediction in Behavioral Cloning through Value Approximation. CoRR (2023)
Christie Lawrence, Isaac Cui, Daniel Ho
The Bureaucratic Challenge to AI Governance: An Empirical Assessment of Implementation at U.S. Federal Agencies. AIES (2023)
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)
Jennifer King, Daniel Ho, Arushi Gupta, Victor Wu, Helen Webley-Brown
The Privacy-Bias Tradeoff: Data Minimization and Racial Disparity Assessments in U.S. Government. FAccT (2023)
Cem Gokmen, Daniel Ho, Mohi Khansari
Asking for Help: Failure Prediction in Behavioral Cloning through Value Approximation. ICRA (2023)
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
Deep RL at Scale: Sorting Waste in Office Buildings with a Fleet of Mobile Manipulators. Robotics: Science and Systems (2023)
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
Deep RL at Scale: Sorting Waste in Office Buildings with a Fleet of Mobile Manipulators. CoRR (2023)
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 (2022)
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 (2022)
Yuqing Du, Daniel Ho, Alexander A. Alemi, Eric Jang, Mohi Khansari
Bayesian Imitation Learning for End-to-End Mobile Manipulation. CoRR (2022)
Emily Black, Hadi Elzayn, Alexandra Chouldechova, Jacob Goldin, Daniel Ho
Algorithmic Fairness and Vertical Equity: Income Fairness with IRS Tax Audit Models. FAccT (2022)
Weixin Liang, Girmaw Abebe Tadesse, Daniel Ho, Li Fei-Fei, Matei Zaharia, Ce Zhang, James Zou
Advances, challenges and opportunities in creating data for trustworthy AI. Nat. Mach. Intell. 4 (8) (2022)
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)
Yuqing Du, Daniel Ho, Alex Alemi, Eric Jang, Mohi Khansari
Bayesian Imitation Learning for End-to-End Mobile Manipulation. ICML (2022)
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 (2021)
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)
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)
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 (2021)
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)
Daniel Ho, Kanishka Rao, Zhuo Xu, Eric Jang, Mohi Khansari, Yunfei Bai
RetinaGAN: An Object-aware Approach to Sim-to-Real Transfer. ICRA (2021)
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)
Alvin Wan, Daniel Ho, Younjin Song, Henk Tillman, Sarah Adel Bargal, Joseph E. Gonzalez
SegNBDT: Visual Decision Rules for Segmentation. CoRR (2020)
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 (2020)
Daniel Ho, Kanishka Rao, Zhuo Xu, Eric Jang, Mohi Khansari, Yunfei Bai
RetinaGAN: An Object-aware Approach to Sim-to-Real Transfer. CoRR (2020)
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 (2020)
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 (2020)
Daniel Ho, Eric Liang, Xi Chen, Ion Stoica, Pieter Abbeel
Population Based Augmentation: Efficient Learning of Augmentation Policy Schedules. ICML (2019)
Daniel Ho, Eric Liang, Ion Stoica, Pieter Abbeel, Xi Chen
Population Based Augmentation: Efficient Learning of Augmentation Policy Schedules. CoRR (2019)
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)
T. Nathan Mundhenk, Daniel Ho, Barry Y. Chen
Improvements to Context Based Self-Supervised Learning. CVPR (2018)
T. Nathan Mundhenk, Daniel Ho, Barry Y. Chen
Improvements to context based self-supervised learning. CoRR (2017)
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)
Daniel Ho, Wing-hung Tam
The Impact of Information Technology on the Accountancy Profession in Hong Kong. PACIS (1995)