The Impact of Information Technology on the Accountancy Profession in Hong Kong. - Daniel Ho; Wing-hung Tam (PACIS, 1995)

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)

Improvements to Context Based Self-Supervised Learning. - T. Nathan Mundhenk; Daniel Ho; Barry Y. Chen (CVPR, 2018)

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 (EMBC, 2019)

Population Based Augmentation: Efficient Learning of Augmentation Policy Schedules. - Daniel Ho; Eric Liang; Xi Chen 022; Ion Stoica; Pieter Abbeel (ICML, 2019)

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)

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 001; Jay Pujara (CoRR, 2020)

SegNBDT: Visual Decision Rules for Segmentation. - Alvin Wan; Daniel Ho; Younjin Song; Henk Tillman; Sarah Adel Bargal; Joseph E. Gonzalez (CoRR, 2020)

RICA: Evaluating Robust Inference Capabilities Based on Commonsense Axioms. - Pei Zhou; Rahul Khanna; Seyeon Lee; Bill Yuchen Lin; Daniel Ho; Jay Pujara; Xiang Ren 001 (EMNLP (1), 2021)

NBDT: Neural-Backed Decision Tree. - Alvin Wan; Lisa Dunlap; Daniel Ho; Jihan Yin; Scott Lee; Suzanne Petryk; Sarah Adel Bargal; Joseph E. Gonzalez (ICLR, 2021)

SimGAN: Hybrid Simulator Identification for Domain Adaptation via Adversarial Reinforcement Learning. - Yifeng Jiang 002; Tingnan Zhang; Daniel Ho; Yunfei Bai; C. Karen Liu; Sergey Levine; Jie Tan 001 (ICRA, 2021)

RetinaGAN: An Object-aware Approach to Sim-to-Real Transfer. - Daniel Ho; Kanishka Rao; Zhuo Xu; Eric Jang; Mohi Khansari; Yunfei Bai (ICRA, 2021)

COCOI: Contact-aware Online Context Inference for Generalizable Non-planar Pushing. - Zhuo Xu; Wenhao Yu 003; Alexander Herzog; Wenlong Lu; Chuyuan Fu; Masayoshi Tomizuka; Yunfei Bai; C. Karen Liu; Daniel Ho (IROS, 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; et al. (CoRR, 2021)

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; et al. (CoRL, 2022)

Bayesian Imitation Learning for End-to-End Mobile Manipulation. - Yuqing Du; Daniel Ho; Alex Alemi; Eric Jang; Mohi Khansari (ICML, 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)

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; et al. (CoRR, 2022)

Asking for Help: Failure Prediction in Behavioral Cloning through Value Approximation. - Cem Gokmen; Daniel Ho; Mohi Khansari (ICRA, 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 (ICRA, 2023)

Deep RL at Scale: Sorting Waste in Office Buildings with a Fleet of Mobile Manipulators. - Alexander Herzog; Kanishka Rao; Karol Hausman; Yao Lu 006; Paul Wohlhart; Mengyuan Yan; Jessica Lin; Montserrat Gonzalez Arenas; Ted Xiao; Daniel Kappler; Daniel Ho; Jarek Rettinghouse; et al. (Robotics: Science and Systems, 2023)

Deep RL at Scale: Sorting Waste in Office Buildings with a Fleet of Mobile Manipulators. - Alexander Herzog; Kanishka Rao; Karol Hausman; Yao Lu 006; Paul Wohlhart; Mengyuan Yan; Jessica Lin; Montserrat Gonzalez Arenas; Ted Xiao; Daniel Kappler; Daniel Ho; Jarek Rettinghouse; et al. (CoRR, 2023)