A. Ng

发表

Learning Continuous Phrase Representations and Syntactic Parsing with Recursive Neural Networks

Christopher D. Manning, R. Socher, A. Ng, 2010 .

Large Scale Distributed Deep Networks

Marc'Aurelio Ranzato, Quoc V. Le, Andrew Y. Ng, 2012, NIPS.

Using inaccurate models in reinforcement learning

Pieter Abbeel, Andrew Y. Ng, Morgan Quigley, 2006, ICML.

Distance Metric Learning with Application to Clustering with Side-Information

Michael I. Jordan, Eric P. Xing, Andrew Y. Ng, 2002, NIPS.

Policy Invariance Under Reward Transformations: Theory and Application to Reward Shaping

Andrew Y. Ng, Daishi Harada, Stuart J. Russell, 1999, ICML.

Sparse deep belief net model for visual area V2

Honglak Lee, Andrew Y. Ng, Chaitanya Ekanadham, 2007, NIPS.

Convolutional deep belief networks for scalable unsupervised learning of hierarchical representations

Honglak Lee, Andrew Y. Ng, Roger B. Grosse, 2009, ICML '09.

Learning hierarchical invariant spatio-temporal features for action recognition with independent subspace analysis

Quoc V. Le, Andrew Y. Ng, Will Y. Zou, 2011, CVPR 2011.

Exploration and apprenticeship learning in reinforcement learning

Pieter Abbeel, Andrew Y. Ng, A. Ng, 2005, ICML.

Approximate Planning in Large POMDPs via Reusable Trajectories

Yishay Mansour, Andrew Y. Ng, Michael Kearns, 1999, NIPS.

Autonomous Inverted Helicopter Flight via Reinforcement Learning

Ben Tse, Andrew Y. Ng, Adam Coates, 2004, ISER.

Pharmacokinetics of a novel formulation of ivermectin after administration to goats

Andrew Y. Ng, Stuart J. Russell, A. Ng, 2000, ICML.

Autonomous Helicopter Aerobatics through Apprenticeship Learning

Pieter Abbeel, Andrew Y. Ng, Adam Coates, 2010, Int. J. Robotics Res..

Hierarchical Apprenticeship Learning with Application to Quadruped Locomotion

Pieter Abbeel, Andrew Y. Ng, J. Zico Kolter, 2007, NIPS.

Inverse Reinforcement Learning

Pieter Abbeel, Andrew Y. Ng, A. Ng, 2010, Encyclopedia of Machine Learning and Data Mining.

Area Under Curve

Sanjoy Dasgupta, Hannu Toivonen, Pieter Abbeel, 2020, Encyclopedia of Machine Learning.

Discriminative Training of Kalman Filters

Sebastian Thrun, Pieter Abbeel, Andrew Y. Ng, 2005, Robotics: Science and Systems.

Apprenticeship learning for helicopter control

Pieter Abbeel, Andrew Y. Ng, Adam Coates, 2009, CACM.

Learning Factor Graphs in Polynomial Time & Sample Complexity

Pieter Abbeel, Andrew Y. Ng, Daphne Koller, 2005, UAI.

On Spectral Clustering: Analysis and an algorithm

Michael I. Jordan, Andrew Y. Ng, Yair Weiss, 2001, NIPS.

Spam Deobfuscation using a Hidden Markov Model

Honglak Lee, Andrew Y. Ng, A. Ng, 2005, CEAS.

Hierarchical Bayesian Models for Applications in Information Retrieval

Michael I. Jordan, A. Ng, D. Blei, 2003 .

The Stanford LittleDog: A learning and rapid replanning approach to quadruped locomotion

Andrew Y. Ng, J. Zico Kolter, J. Z. Kolter, 2011, Int. J. Robotics Res..

Shaping and policy search in reinforcement learning

Andrew Y. Ng, Michael I. Jordan, A. Ng, 2003 .

PEGASUS: A policy search method for large MDPs and POMDPs pdf

Michael I. Jordan, Andrew Y. Ng, A. Ng, 2000, UAI.

Apprenticeship learning via inverse reinforcement learning

Pieter Abbeel, Andrew Y. Ng, A. Ng, 2004, ICML.

Reading Digits in Natural Images with Unsupervised Feature Learning

Andrew Y. Ng, Adam Coates, Alessandro Bissacco, 2011 .

Learning Word Vectors for Sentiment Analysis

Christopher Potts, Andrew Y. Ng, Dan Huang, 2011, ACL.

An Application of Reinforcement Learning to Aerobatic Helicopter Flight

Pieter Abbeel, Andrew Y. Ng, Morgan Quigley, 2006, NIPS.

Parsing Natural Scenes and Natural Language with Recursive Neural Networks

Andrew Y. Ng, Christopher D. Manning, Richard Socher, 2011, ICML.

The Importance of Encoding Versus Training with Sparse Coding and Vector Quantization

Andrew Y. Ng, Adam Coates, A. Ng, 2011, ICML.

Measuring Invariances in Deep Networks

Quoc V. Le, Honglak Lee, Andrew Y. Ng, 2009, NIPS.

Autonomous Helicopter Flight via Reinforcement Learning

S. Shankar Sastry, H. Jin Kim, Michael I. Jordan, 2003, NIPS.

Recursive Deep Models for Semantic Compositionality Over a Sentiment Treebank

Christopher Potts, Andrew Y. Ng, Christopher D. Manning, 2013, EMNLP.

ICA with Reconstruction Cost for Efficient Overcomplete Feature Learning

Quoc V. Le, Jiquan Ngiam, Andrew Y. Ng, 2011, NIPS.

An Analysis of Single-Layer Networks in Unsupervised Feature Learning

Honglak Lee, Andrew Y. Ng, Adam Coates, 2011, AISTATS.

Improving Word Representations via Global Context and Multiple Word Prototypes

Andrew Y. Ng, Christopher D. Manning, Richard Socher, 2012, ACL.

A control architecture for quadruped locomotion over rough terrain

Andrew Y. Ng, J. Zico Kolter, J. Z. Kolter, 2008, 2008 IEEE International Conference on Robotics and Automation.

Autonomous Autorotation of an RC Helicopter

Pieter Abbeel, Andrew Y. Ng, Adam Coates, 2008, ISER.

Learning to grasp objects with multiple contact points

Quoc V. Le, Andrew Y. Ng, David Kamm, 2010, 2010 IEEE International Conference on Robotics and Automation.

Make3D: Learning 3D Scene Structure from a Single Still Image

Ashutosh Saxena, Min Sun, Andrew Y. Ng, 2009, IEEE Transactions on Pattern Analysis and Machine Intelligence.

Joint calibration of multiple sensors

Quoc V. Le, Andrew Y. Ng, A. Ng, 2009, 2009 IEEE/RSJ International Conference on Intelligent Robots and Systems.

On Random Weights and Unsupervised Feature Learning

Zhenghao Chen, Andrew Y. Ng, Bipin Suresh, 2011, ICML.

Learning for control from multiple demonstrations

Pieter Abbeel, Andrew Y. Ng, Adam Coates, 2008, ICML '08.

Online Bounds for Bayesian Algorithms

Sham M. Kakade, Andrew Y. Ng, A. Ng, 2004, NIPS.

Latent Dirichlet Allocation

Michael I. Jordan, Andrew Y. Ng, David M. Blei, 2001, J. Mach. Learn. Res..

Deep Speech: Scaling up end-to-end speech recognition pdf

Erich Elsen, Andrew Y. Ng, Adam Coates, 2014, ArXiv.

Deep Speech 2 : End-to-End Speech Recognition in English and Mandarin pdf

Chong Wang, Xiangang Li, Yi Wang, 2015, ICML.

On optimization methods for deep learning

Quoc V. Le, Jiquan Ngiam, Andrew Y. Ng, 2011, ICML.

Tiled convolutional neural networks

Quoc V. Le, Jiquan Ngiam, Zhenghao Chen, 2010, NIPS.

Policy Search by Dynamic Programming

Jeff G. Schneider, Sham M. Kakade, Andrew Y. Ng, 2003, NIPS.

Efficient sparse coding algorithms

Rajat Raina, Honglak Lee, Andrew Y. Ng, 2006, NIPS.

Grasping novel objects with depth segmentation

Quoc V. Le, Thanathorn Phoka, Andrew Y. Ng, 2010, 2010 IEEE/RSJ International Conference on Intelligent Robots and Systems.

Self-taught learning: transfer learning from unlabeled data

Rajat Raina, Honglak Lee, Andrew Y. Ng, 2007, ICML '07.

Multimodal Deep Learning

Juhan Nam, Honglak Lee, Mingyu Kim, 2011, ICML.

A Sparse Sampling Algorithm for Near-Optimal Planning in Large Markov Decision Processes

Yishay Mansour, Andrew Y. Ng, Michael Kearns, 1999, Machine Learning.

Near-Bayesian exploration in polynomial time

Andrew Y. Ng, J. Zico Kolter, J. Z. Kolter, 2009, ICML '09.

End-to-end text recognition with convolutional neural networks

Tao Wang, Andrew Y. Ng, David J. Wu, 2012, Proceedings of the 21st International Conference on Pattern Recognition (ICPR2012).

Map-Reduce for Machine Learning on Multicore

Kunle Olukotun, Gary R. Bradski, Andrew Y. Ng, 2006, NIPS.

Robotic Grasping of Novel Objects using Vision

Ashutosh Saxena, Andrew Y. Ng, Justin Driemeyer, 2008, Int. J. Robotics Res..

MoCo Pretraining Improves Representation and Transferability of Chest X-ray Models pdf

Andrew Y. Ng, Pranav Rajpurkar, Hari Sowrirajan, 2020, MIDL.

Learning vehicular dynamics, with application to modeling helicopters

Pieter Abbeel, Andrew Y. Ng, Varun Ganapathi, 2005, NIPS.

On Discriminative vs. Generative Classifiers: A comparison of logistic regression and naive Bayes

Michael I. Jordan, Andrew Y. Ng, A. Ng, 2001, NIPS.

Learning first-order Markov models for control

Pieter Abbeel, Andrew Y. Ng, A. Ng, 2004, NIPS.

Multi-Dimensional Sentiment Analysis with Learned Representations

Andrew L. Maas, A. Ng, Christopher Potts, 2012 .

Improving palliative care with deep learning

Andrew Y. Ng, Nigam H. Shah, Anand Avati, 2017, 2017 IEEE International Conference on Bioinformatics and Biomedicine (BIBM).

Quadruped robot obstacle negotiation via reinforcement learning

Chih-Han Yu, Honglak Lee, Andrew Y. Ng, 2006, Proceedings 2006 IEEE International Conference on Robotics and Automation, 2006. ICRA 2006..

Unsupervised Deep Learning Applied to Breast Density Segmentation and Mammographic Risk Scoring

Nico Karssemeijer, Mads Nielsen, Christian Igel, 2016, IEEE Transactions on Medical Imaging.

Breast Density Scoring with Multiscale Denoising Autoencoders

A. Ng, K. Petersen, M. Nielsen, 2012 .

Task-space trajectories via cubic spline optimization

Andrew Y. Ng, J. Zico Kolter, J. Z. Kolter, 2009, 2009 IEEE International Conference on Robotics and Automation.

Unsupervised learning models of primary cortical receptive fields and receptive field plasticity

Andrew Y. Ng, Bipin Suresh, Andrew M. Saxe, 2011, NIPS.

Automatic Single-Image 3d Reconstructions of Indoor Manhattan World Scenes

Honglak Lee, Andrew Y. Ng, Erick Delage, 2007, ISRR.

Self-taught learning

Rajat Raina, Andrew Y. Ng, A. Ng, 2009 .

From uncertainty to belief: inferring the specification within

Dawson R. Engler, Andrew Y. Ng, Ted Kremenek, 2006, OSDI '06.

DLBCL-Morph: Morphological features computed using deep learning for an annotated digital DLBCL image set pdf

Andrew Y. Ng, Damir Vrabac, Akshay Smit, 2020, Scientific Data.

Stable algorithms for link analysis

Michael I. Jordan, Andrew Y. Ng, Alice X. Zheng, 2001, SIGIR '01.

Deep learning assistance for the histopathologic diagnosis of Helicobacter pylori

Andrew Y. Ng, Jeanne Shen, Sharon Zhou, 2020 .

Impact of a deep learning assistant on the histopathologic classification of liver cancer

Ryanne A. Brown, Simon B. Chen, A. Ng, 2020, npj Digital Medicine.

Comparing Speech and Keyboard Text Entry for Short Messages in Two Languages on Touchscreen Phones

James A. Landay, Jacob O. Wobbrock, Andrew Y. Ng, 2016, Proc. ACM Interact. Mob. Wearable Ubiquitous Technol..

CheXpert: A Large Chest Radiograph Dataset with Uncertainty Labels and Expert Comparison

Yifan Yu, Andrew Y. Ng, Curtis P. Langlotz, 2019, AAAI.

A Factor Graph Model for Software Bug Finding

Dawson R. Engler, Andrew Y. Ng, Ted Kremenek, 2007, IJCAI.

Abstract

Rajat Raina, Andrew Y. Ng, Daphne Koller, 1997, Veterinary Record.

Regularization and feature selection in least-squares temporal difference learning

Andrew Y. Ng, J. Zico Kolter, J. Z. Kolter, 2009, ICML '09.

OGNet: Towards a Global Oil and Gas Infrastructure Database using Deep Learning on Remotely Sensed Imagery pdf

Andrew Y. Ng, Ritesh Gautam, Robert B. Jackson, 2020, ArXiv.

The online revolution: education for everyone

Andrew Y. Ng, Daphne Koller, A. Ng, 2013, KDD.

CheXNet: Radiologist-Level Pneumonia Detection on Chest X-Rays with Deep Learning pdf

Andrew Y. Ng, Curtis P. Langlotz, Matthew P. Lungren, 2017, ArXiv.

Tuned Models of Peer Assessment in MOOCs

Zhenghao Chen, Andrew Y. Ng, Daphne Koller, 2013, EDM.

Offering Verified Credentials in Massive Open Online Courses: MOOCs and technology to advance learning and learning research (Ubiquity symposium)

Andrew Y. Ng, Daphne Koller, Andrew L. Maas, 2014, UBIQ.

CheXphoto: 10, 000+ Smartphone Photos and Synthetic Photographic Transformations of Chest X-rays for Benchmarking Deep Learning Robustness pdf

Andrew Y. Ng, Matthew P. Lungren, Pranav Rajpurkar, 2020, ArXiv.

Deep learning for chest radiograph diagnosis: A retrospective comparison of the CheXNeXt algorithm to practicing radiologists

A. Ng, Pranav Rajpurkar, C. Langlotz, 2018, PLoS medicine.

Ambulatory Atrial Fibrillation Monitoring Using Wearable Photoplethysmography with Deep Learning

Andrew Y. Ng, Anand Avati, Yichen Shen, 2018, KDD.

Mechatronic design of an integrated robotic hand

John Kenneth Salisbury, Andrew Y. Ng, Morgan Quigley, 2014, Int. J. Robotics Res..

Touch Based Perception for Object Manipulation

A. Ng, S. Thrun, O. Khatib, 2007 .

Cheap and Fast – But is it Good? Evaluating Non-Expert Annotations for Natural Language Tasks

Brendan T. O'Connor, Daniel Jurafsky, Andrew Y. Ng, 2008, EMNLP.

Robust Textual Inference Via Learning and Abductive Reasoning

Rajat Raina, Andrew Y. Ng, Christopher D. Manning, 2005, AAAI.

Robust Textual Inference using Diverse Knowledge Sources

Christopher D. Manning, Marie-Catherine de Marneffe, A. Ng, 2005 .

Text Detection and Character Recognition in Scene Images with Unsupervised Feature Learning

Andrew Y. Ng, Tao Wang, David J. Wu, 2011, 2011 International Conference on Document Analysis and Recognition.

Policy search via the signed derivative

Andrew Y. Ng, J. Zico Kolter, J. Z. Kolter, 2009, Robotics: Science and Systems.

Selecting Receptive Fields in Deep Networks

Andrew Y. Ng, Adam Coates, A. Ng, 2011, NIPS.

Deep learning with COTS HPC systems

Tao Wang, Andrew Y. Ng, David J. Wu, 2013, ICML.

Building high-level features using large scale unsupervised learning

Marc'Aurelio Ranzato, Quoc V. Le, Andrew Y. Ng, 2011, 2013 IEEE International Conference on Acoustics, Speech and Signal Processing.

Unsupervised feature learning for audio classification using convolutional deep belief networks

Honglak Lee, Andrew Y. Ng, Peter T. Pham, 2009, NIPS.

An Information-Theoretic Analysis of Hard and Soft Assignment Methods for Clustering

Yishay Mansour, Andrew Y. Ng, Michael Kearns, 1997, UAI.

Learning omnidirectional path following using dimensionality reduction

Andrew Y. Ng, J. Zico Kolter, J. Z. Kolter, 2007, Robotics: Science and Systems.

Semantic Compositionality through Recursive Matrix-Vector Spaces

Andrew Y. Ng, Christopher D. Manning, Richard Socher, 2012, EMNLP.

A Probabilistic Model for Semantic Word Vectors

Andrew L. Maas, A. Ng, 2010 .

Grounded Compositional Semantics for Finding and Describing Images with Sentences

Quoc V. Le, Andrew Y. Ng, Christopher D. Manning, 2014, TACL.

Peripheral-Foveal Vision for Real-time Object Recognition and Tracking in Video

Gary R. Bradski, Benjamin Sapp, Andrew Y. Ng, 2007, IJCAI.

Learning to Grasp Novel Objects Using Vision

Ashutosh Saxena, Andrew Y. Ng, Justin Driemeyer, 2006, ISER.

Online and batch learning of pseudo-metrics

Yoram Singer, Andrew Y. Ng, Shai Shalev-Shwartz, 2004, ICML.

Deep learning for class-generic object detection pdf

Andrew Y. Ng, Brody Huval, Adam Coates, 2013, ICLR.

Learning Grasp Strategies with Partial Shape Information

Lawson L. S. Wong, Ashutosh Saxena, Andrew Y. Ng, 2008, AAAI.

Autonomous Helicopter Tracking and Localization Using a Self-surveying Camera Array

Sebastian Thrun, Andrew Y. Ng, Surya P. N. Singh, 2007, Int. J. Robotics Res..

Applying Online Search Techniques to Continuous-State Reinforcement Learning

Andrew W. Moore, Andrew Y. Ng, Scott Davies, 1998, AAAI/IAAI.

Scalable learning for object detection with GPU hardware

Quoc V. Le, Andrew Y. Ng, Paul Baumstarck, 2009, 2009 IEEE/RSJ International Conference on Intelligent Robots and Systems.

Monocular depth perception and robotic grasping of novel objects

Ashutosh Saxena, Andrew Y. Ng, A. Ng, 2009 .

Recurrent Neural Networks for Noise Reduction in Robust ASR

Quoc V. Le, Patrick Nguyen, Andrew Y. Ng, 2012, INTERSPEECH.

Classification with Hybrid Generative/Discriminative Models

Rajat Raina, Andrew McCallum, Andrew Y. Ng, 2003, NIPS.

Learning 3-D Scene Structure from a Single Still Image

Ashutosh Saxena, Min Sun, Andrew Y. Ng, 2007, 2007 IEEE 11th International Conference on Computer Vision.

Bayesian estimation for autonomous object manipulation based on tactile sensors

Oussama Khatib, Sebastian Thrun, Andrew Y. Ng, 2006, Proceedings 2006 IEEE International Conference on Robotics and Automation, 2006. ICRA 2006..

Reactive grasping using optical proximity sensors

Ashutosh Saxena, Andrew Y. Ng, Manfred Huber, 2009, 2009 IEEE International Conference on Robotics and Automation.

High speed obstacle avoidance using monocular vision and reinforcement learning

Ashutosh Saxena, Andrew Y. Ng, Jeff Michels, 2005, ICML.

Semi-Supervised Recursive Autoencoders for Predicting Sentiment Distributions

Jeffrey Pennington, Andrew Y. Ng, Christopher D. Manning, 2011, EMNLP.

Emergence of Object-Selective Features in Unsupervised Feature Learning

Andrew Y. Ng, Adam Coates, Andrej Karpathy, 2012, NIPS.

Parsing with Compositional Vector Grammars

Andrew Y. Ng, Christopher D. Manning, Richard Socher, 2013, ACL.

Dynamic Pooling and Unfolding Recursive Autoencoders for Paraphrase Detection

Jeffrey Pennington, Andrew Y. Ng, Christopher D. Manning, 2011, NIPS.

Apprenticeship learning for motion planning with application to parking lot navigation

Sebastian Thrun, Pieter Abbeel, Andrew Y. Ng, 2008, 2008 IEEE/RSJ International Conference on Intelligent Robots and Systems.

Adaptive Control Processes

Sanjoy Dasgupta, Hannu Toivonen, Pieter Abbeel, 2010, Encyclopedia of Machine Learning and Data Mining.

High-accuracy 3D sensing for mobile manipulation: Improving object detection and door opening

Quoc V. Le, Andrew Y. Ng, Ellen Klingbeil, 2009, 2009 IEEE International Conference on Robotics and Automation.

Efficient multiple hyperparameter learning for log-linear models

Chuan-Sheng Foo, Andrew Y. Ng, Chuong B. Do, 2007, NIPS.

First-Pass Large Vocabulary Continuous Speech Recognition using Bi-Directional Recurrent DNNs pdf

Daniel Jurafsky, Andrew Y. Ng, Awni Y. Hannun, 2014, ArXiv.

Robotic Grasping of Novel Objects

Ashutosh Saxena, Andrew Y. Ng, Justin Driemeyer, 2006, NIPS.

Learning Depth from Single Monocular Images

Ashutosh Saxena, Andrew Y. Ng, Sung H. Chung, 2005, NIPS.

Learning Feature Representations with K-Means

Andrew Y. Ng, Adam Coates, A. Ng, 2012, Neural Networks: Tricks of the Trade.

Word-level Acoustic Modeling with Convolutional Vector Regression

Andrew L. Maas, Tyler M. O'Neil, A. Ng, 2012 .

Discriminative learning of Markov random fields for segmentation of 3D scan data

Ben Taskar, Dragomir Anguelov, Andrew Y. Ng, 2005, 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05).

An experimental and theoretical comparison of model selection methods

Dana Ron, Yishay Mansour, Andrew Y. Ng, 1995, COLT '95.

RECURRENT NEURAL NETWORK FEATURE ENHANCEMENT: THE 2nd CHIME CHALLENGE

Andrew L. Maas, Tyler M. O'Neil, A. Ng, 2013 .

RECURRENT NEURAL NETWORK FEATURE ENHANCEMENT : THE 2 nd CHIME CHALLENGE

Andrew L. Maas, Tyler M. O'Neil, A. Ng, 2013 .

Convolutional-Recursive Deep Learning for 3D Object Classification

Andrew Y. Ng, Christopher D. Manning, Richard Socher, 2012, NIPS.

3-D Depth Reconstruction from a Single Still Image

Ashutosh Saxena, Andrew Y. Ng, Sung H. Chung, 2007, International Journal of Computer Vision.

MURA: Large Dataset for Abnormality Detection in Musculoskeletal Radiographs.

A. Ng, Pranav Rajpurkar, C. Langlotz, 2017 .

Learning Deep Energy Models

Jiquan Ngiam, Zhenghao Chen, Andrew Y. Ng, 2011, ICML.

Zero-Shot Learning Through Cross-Modal Transfer

Andrew Y. Ng, Christopher D. Manning, Richard Socher, 2013, NIPS.

Fast Gaussian Process Regression using KD-Trees

Andrew Y. Ng, Matthias W. Seeger, Yirong Shen, 2005, NIPS.

An Empirical Evaluation of Deep Learning on Highway Driving pdf

Fernando A. Mujica, Andrew Y. Ng, Brody Huval, 2015, ArXiv.

Constructing informative priors using transfer learning

Rajat Raina, Andrew Y. Ng, Daphne Koller, 2006, ICML.

An Experimental and Theoretical Comparison of Model Selection Methods

Dana Ron, Yishay Mansour, Andrew Y. Ng, 1995, COLT '95.

Learning to open new doors

Ashutosh Saxena, Andrew Y. Ng, Ellen Klingbeil, 2010, 2010 IEEE/RSJ International Conference on Intelligent Robots and Systems.

Learning 3-D object orientation from images

Ashutosh Saxena, Andrew Y. Ng, Justin Driemeyer, 2009, 2009 IEEE International Conference on Robotics and Automation.

Link Analysis, Eigenvectors and Stability

Michael I. Jordan, Andrew Y. Ng, Alice X. Zheng, 2001, IJCAI.

A Dynamic Bayesian Network Model for Autonomous 3D Reconstruction from a Single Indoor Image

Honglak Lee, Andrew Y. Ng, Erick Delage, 2006, 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'06).

Simultaneous Localization and Mapping with Sparse Extended Information Filters

Hugh F. Durrant-Whyte, Zoubin Ghahramani, Andrew Y. Ng, 2004, Int. J. Robotics Res..

Time Complexity of Sensor-Based Vehicle Routing

Sebastian Thrun, Pieter Abbeel, Andrew Y. Ng, 2005 .

Solving Uncertain Markov Decision Processes

Andrew Y. Ng, J. Andrew Bagnell, Jeff Schneider, 2001 .

Simultaneous Mapping and Localization with Sparse Extended Information Filters: Theory and Initial Results

Hugh F. Durrant-Whyte, Zoubin Ghahramani, Andrew Y. Ng, 2004, WAFR.

Reasoning With Neural Tensor Networks for Knowledge Base Completion

Danqi Chen, Andrew Y. Ng, Christopher D. Manning, 2013, NIPS.

Efficient L1 Regularized Logistic Regression

Honglak Lee, Pieter Abbeel, Andrew Y. Ng, 2006, AAAI.

CheXternal: generalization of deep learning models for chest X-ray interpretation to photos of chest X-rays and external clinical settings

Andrew Y. Ng, Matthew P. Lungren, Pranav Rajpurkar, 2021, CHIL.

Impact of a deep learning assistant on the histopathologic classification of liver cancer

Ryanne A. Brown, Simon B. Chen, A. Ng, 2020, npj Digital Medicine.

Semantic Taxonomy Induction from Heterogenous Evidence

Daniel Jurafsky, Andrew Y. Ng, Rion Snow, 2006, ACL.

Space-indexed dynamic programming: learning to follow trajectories

Yi Gu, Andrew Y. Ng, J. Zico Kolter, 2008, ICML '08.

Convergence rates of the Voting Gibbs classifier, with application to Bayesian feature selection

Michael I. Jordan, Andrew Y. Ng, A. Ng, 2001, ICML.

A Steiner tree approach to efficient object detection

Andrew Y. Ng, Olga Russakovsky, A. Ng, 2010, 2010 IEEE Computer Society Conference on Computer Vision and Pattern Recognition.

A low-cost compliant 7-DOF robotic manipulator

Andrew Y. Ng, Morgan Quigley, Alan T. Asbeck, 2011, 2011 IEEE International Conference on Robotics and Automation.

Grasping with application to an autonomous checkout robot

Oussama Khatib, Andrew Y. Ng, Ellen Klingbeil, 2011, 2011 IEEE International Conference on Robotics and Automation.

Solving the Problem of Cascading Errors: Approximate Bayesian Inference for Linguistic Annotation Pipelines

Andrew Y. Ng, Christopher D. Manning, Jenny Rose Finkel, 2006, EMNLP.

Approximate Inference A lgorithms for Two-Layer Bayesian Networks

Michael I. Jordan, Andrew Y. Ng, A. Ng, 1999, NIPS.

Deep-learning-assisted diagnosis for knee magnetic resonance imaging: Development and retrospective validation of MRNet

A. Ng, Pranav Rajpurkar, C. Langlotz, 2018, PLoS medicine.

VisualCheXbert: addressing the discrepancy between radiology report labels and image labels

Andrew Y. Ng, Matthew P. Lungren, Akshay Smit, 2021, CHIL.

CheXaid: deep learning assistance for physician diagnosis of tuberculosis using chest x-rays in patients with HIV

A. Ng, P. Rajpurkar, A. Kiani, 2020, npj Digital Medicine.

CheXphoto: 10, 000+ Photos and Transformations of Chest X-rays for Benchmarking Deep Learning Robustness

Nguyet Minh Phu, Nick A. Phillips, Nguyen Duong Du, 2020, ML4H@NeurIPS.

CheXbreak: Misclassification Identification for Deep Learning Models Interpreting Chest X-rays pdf

Andrew Y. Ng, Pranav Rajpurkar, Rayan Krishnan, 2021, ArXiv.

Depth Estimation Using Monocular and Stereo Cues

Ashutosh Saxena, Andrew Y. Ng, Jamie Schulte, 2007, IJCAI.

Unsupervised learning of hierarchical representations with convolutional deep belief networks

Honglak Lee, Andrew Y. Ng, Roger B. Grosse, 2011, Commun. ACM.

Robust Textual Inference via Graph Matching

Andrew Y. Ng, Christopher D. Manning, Aria Haghighi, 2005, HLT.

A Fast Data Collection and Augmentation Procedure for Object Recognition

Ashutosh Saxena, Benjamin Sapp, Andrew Y. Ng, 2008, AAAI.

Contextual search and name disambiguation in email using graphs

William W. Cohen, Andrew Y. Ng, Einat Minkov, 2006, SIGIR.

Autonomous sign reading for semantic mapping

Andrew Y. Ng, Adam Coates, Bipin Suresh, 2011, 2011 IEEE International Conference on Robotics and Automation.

Stereo vision and terrain modeling for quadruped robots

Andrew Y. Ng, J. Zico Kolter, Youngjun Kim, 2009, 2009 IEEE International Conference on Robotics and Automation.

Lexicon-Free Conversational Speech Recognition with Neural Networks

Daniel Jurafsky, Andrew Y. Ng, Andrew L. Maas, 2015, NAACL.

CheXtransfer: performance and parameter efficiency of ImageNet models for chest X-Ray interpretation pdf

Andrew Y. Ng, Pranav Rajpurkar, Alexander Ke, 2021, CHIL.

CheXbert: Combining Automatic Labelers and Expert Annotations for Accurate Radiology Report Labeling Using BERT

Andrew Y. Ng, Matthew P. Lungren, Akshay Smit, 2020, EMNLP.

Short-Term Solar Irradiance Forecasting Using Calibrated Probabilistic Models pdf

Andrew Y. Ng, Hao Sheng, Ram Rajagopal, 2020, ArXiv.

CheXphotogenic: Generalization of Deep Learning Models for Chest X-ray Interpretation to Photos of Chest X-rays pdf

Andrew Y. Ng, Pranav Rajpurkar, Matthew Lungren, 2020, ArXiv.

A Vision-Based System for Grasping Novel Objects in Cluttered Environments

Lawson L. S. Wong, Ashutosh Saxena, Andrew Y. Ng, 2007, ISRR.

Learning New Facts From Knowledge Bases With Neural Tensor Networks and Semantic Word Vectors pdf

Danqi Chen, Andrew Y. Ng, Christopher D. Manning, 2013, ICLR.

Probabilistic Mobile Manipulation in Dynamic Environments, with Application to Opening Doors

Andrew Y. Ng, Anna Petrovskaya, A. Ng, 2007, IJCAI.

Learning sound location from a single microphone

Ashutosh Saxena, Andrew Y. Ng, A. Ng, 2009, 2009 IEEE International Conference on Robotics and Automation.

NGBoost: Natural Gradient Boosting for Probabilistic Prediction pdf

Andrew Y. Ng, Anand Avati, Daisy Yi Ding, 2019, ICML.

Deep Learning for the Digital Pathologic Diagnosis of Cholangiocarcinoma and Hepatocellular Carcinoma: Evaluating the Impact of a Web-based Diagnostic Assistant

Alex Wang, Andrew Y. Ng, Curtis P. Langlotz, 2019, 1911.07372.

Evaluating the Disentanglement of Deep Generative Models through Manifold Topology pdf

Stefano Ermon, Andrew Y. Ng, Sharon Zhou, 2020, ICLR.

Discriminative structured models for biological sequence analysis

Andrew Y. Ng, Chuong B. Do, A. Ng, 2009 .

groupTime: preference based group scheduling

Scott R. Klemmer, Jiang Hu, Andrew Y. Ng, 2006, CHI.

On Feature Selection: Learning with Exponentially Many Irrelevant Features as Training Examples

Andrew Y. Ng, A. Ng, 1998, ICML.

CheXpedition: Investigating Generalization Challenges for Translation of Chest X-Ray Algorithms to the Clinical Setting pdf

Andrew Y. Ng, Matthew P. Lungren, Pranav Rajpurkar, 2020, ArXiv.

Clinical Value of Predicting Individual Treatment Effects for Intensive Blood Pressure Therapy: A Machine Learning Experiment to Estimate Treatment Effects from Randomized Trial Data

A. Ng, Pranav Rajpurkar, T. Duan, 2019, Circulation. Cardiovascular quality and outcomes.

Deep Learning–Assisted Diagnosis of Cerebral Aneurysms Using the HeadXNet Model

A. Ng, Pranav Rajpurkar, Robyn L. Ball, 2019, JAMA network open.

Have we met? MDP based speaker ID for robot dialogue

Daniel Jurafsky, Andrew Y. Ng, Filip Krsmanovic, 2006, INTERSPEECH.

The Online Revolution: Education at Scale

Andrew Y. Ng, Daphne Koller, A. Ng, 2012 .

Learning to Merge Word Senses

Daniel Jurafsky, Andrew Y. Ng, Rion Snow, 2007, EMNLP.

Energy Disaggregation via Discriminative Sparse Coding

Andrew Y. Ng, J. Zico Kolter, J. Z. Kolter, 2010, NIPS.

Deep Learning of Invariant Features via Simulated Fixations in Video

Shenghuo Zhu, Andrew Y. Ng, Kai Yu, 2012, NIPS.

Cardiologist-Level Arrhythmia Detection with Convolutional Neural Networks pdf

Andrew Y. Ng, Awni Y. Hannun, Masoumeh Haghpanahi, 2017, ArXiv.

STAIR: Hardware and Software Architecture

Andrew Y. Ng, Morgan Quigley, Eric Berger, 2007 .

Noising and Denoising Natural Language: Diverse Backtranslation for Grammar Correction

Daniel Jurafsky, Andrew Y. Ng, Guillaume Genthial, 2018, NAACL.

Data augmentation with Mobius transformations pdf

Andrew Y. Ng, Hang Jiang, Sharon Zhou, 2020, Mach. Learn. Sci. Technol..

Transfer learning for text classification

Andrew Y. Ng, Chuong B. Do, A. Ng, 2005, NIPS.

MURA Dataset: Towards Radiologist-Level Abnormality Detection in Musculoskeletal Radiographs pdf

Andrew Y. Ng, Curtis P. Langlotz, Matthew P. Lungren, 2017, ArXiv.

A probabilistic approach to mixed open-loop and closed-loop control, with application to extreme autonomous driving

Sebastian Thrun, Christian Plagemann, Andrew Y. Ng, 2010, 2010 IEEE International Conference on Robotics and Automation.

3-D Reconstruction from Sparse Views using Monocular Vision

Ashutosh Saxena, Min Sun, Andrew Y. Ng, 2007, 2007 IEEE 11th International Conference on Computer Vision.

Predicting Inpatient Discharge Prioritization With Electronic Health Records pdf

Andrew Y. Ng, Nigam H. Shah, Anand Avati, 2018, ArXiv.

Learning Syntactic Patterns for Automatic Hypernym Discovery

Daniel Jurafsky, Andrew Y. Ng, Rion Snow, 2004, NIPS.

Preventing "Overfitting" of Cross-Validation Data

Andrew Y. Ng, A. Ng, 1997, ICML.

ForestNet: Classifying Drivers of Deforestation in Indonesia using Deep Learning on Satellite Imagery pdf

Andrew Y. Ng, Hao Sheng, Kemen Austin, 2020, ArXiv.

End-to-End People Detection in Crowded Scenes

Andrew Y. Ng, Mykhaylo Andriluka, Russell Stewart, 2015, 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).

Rapid Interactive 3 D Reconstruction from a Single Still Image

A. Ng, Ashutosh Saxena, N. Senaratna, 2008 .

Building DNN acoustic models for large vocabulary speech recognition

Daniel Jurafsky, Andrew Y. Ng, Peng Qi, 2014, Comput. Speech Lang..

Stable adaptive control with online learning

H. Jin Kim, Andrew Y. Ng, A. Ng, 2004, NIPS.

Learning random walk models for inducing word dependency distributions

Andrew Y. Ng, Christopher D. Manning, Kristina Toutanova, 2004, ICML.

Make3D: Depth Perception from a Single Still Image

Ashutosh Saxena, Min Sun, Andrew Y. Ng, 2008, AAAI.

NGBoost: Natural Gradient Boosting for Probabilistic Prediction pdf

Andrew Y. Ng, Anand Avati, Daisy Yi Ding, 2019, ICML.

Active Perception : Interactive Manipulation for Improvin g Object Detection

Quoc V. Le, Ashutosh Saxena, Andrew Y. Ng, 2010 .

Incorporating machine learning and social determinants of health indicators into prospective risk adjustment for health plan payments

A. Ng, P. Rajpurkar, J. Irvin, 2020, BMC Public Health.

Feature selection, L1 vs. L2 regularization, and rotational invariance

A. Ng, 2004, Twenty-first international conference on Machine learning - ICML '04.

STAIR: The STanford Artificial Intelligence Robot project

Ashutosh Saxena, Andrew Y. Ng, Morgan Quigley, 2008 .

Shift-Invariance Sparse Coding for Audio Classification

Roger B. Grosse, A. Ng, R. Raina, 2007, UAI.

Deep learning saliency maps do not accurately highlight diagnostically relevant regions for medical image interpretation

A. Ng, P. Rajpurkar, J. Seekins, 2021, medRxiv.

PD60-05 AUTOMATED DETECTION OF PROSTATE CANCER ON MULTIPARAMETRIC MRI USING DEEP NEURAL NETWORKS TRAINED ON SPATIAL COORDINATES AND PATHOLOGY OF BIOPSY CORES

Richard E. Fan, A. Ng, Pranav Rajpurkar, 2019, Journal of Urology.

Autonomous Helicopter Tracking and Localization Using a Self-surveying Camera Array

Sebastian Thrun, Andrew Y. Ng, Surya P. N. Singh, 2007, Int. J. Robotics Res..

Low-Cost Manipulation Powered by ROS

Andrew Y. Ng, Morgan Quigley, Alan T. Asbeck, 2010, Enabling Intelligence through Middleware.

MedAug: Contrastive learning leveraging patient metadata improves representations for chest X-ray interpretation pdf

Andrew Y. Ng, Richard Wang, Pranav Rajpurkar, 2021, MLHC.

PENet-a scalable deep-learning model for automated diagnosis of pulmonary embolism using volumetric CT imaging.

Jared A. Dunnmon, A. Ng, Pranav Rajpurkar, 2020, npj Digital Medicine.

Approximate Dynamic Programming

Geoffrey I. Webb, Stephen Grossberg, Mauro Birattari, 2011 .

Speech Is 3x Faster than Typing for English and Mandarin Text Entry on Mobile Devices

A. Ng, S. Ruan, J. Wobbrock, 2016, ArXiv.

Deep learning-based Helicobacter pylori detection: A diagnostic pathology study

A. Ng, H. Marklund, O. Bláha, 2020, medRxiv.

AppendiXNet: Deep Learning for Diagnosis of Appendicitis from A Small Dataset of CT Exams Using Video Pretraining

Curtis P. Langlotz, Matthew P. Lungren, Pranav Rajpurkar, 2020, Scientific Reports.

Autonomous Helicopter Flight Using Reinforcement Learning

Pieter Abbeel, Andrew Y. Ng, Adam Coates, 2010, Encyclopedia of Machine Learning.

Autonomous Helicopter Flight Using Reinforcement Learning

Pieter Abbeel, Andrew Y. Ng, Adam Coates, 2010, Encyclopedia of Machine Learning.

Inverse Reinforcement Learning

Pieter Abbeel, Andrew Y. Ng, A. Ng, 2017, Encyclopedia of Machine Learning and Data Mining.

Inverse Resolution

Pierre Flener, Eamonn J. Keogh, Ricardo Vilalta, 2010, Encyclopedia of Machine Learning and Data Mining.

Transfer learning by constructing informative priors

A. Ng, D. Koller, R. Raina, 2005, ICML 2005.

Shift-invariant sparse coding for audio classification

A. Ng, R. Raina, H. Kwong, 2007, UAI 2007.

Make3D: Learning 3D Scene Structure from a Single Still Image

A. Ng, Ashutosh Saxena, Min Sun, 2022 .

Evaluation of a Machine Learning Model Based on Pretreatment Symptoms and Electroencephalographic Features to Predict Outcomes of Antidepressant Treatment in Adults With Depression

Arielle S. Keller, A. Ng, Pranav Rajpurkar, 2020, JAMA network open.

Autonomous operation of novel elevators for robot navigation

Andrew Y. Ng, Ellen Klingbeil, Olga Russakovsky, 2010, 2010 IEEE International Conference on Robotics and Automation.

Evaluating the Disentanglement of Deep Generative Models through Manifold Topology pdf

Stefano Ermon, Andrew Y. Ng, Eric Zelikman, 2020, ICLR.

Automatic Hilghter of Lengthy Legal Documents

Michael I. Jordan, Andrew Y. Ng, A. Ng, 2015 .

Cardiologist-level arrhythmia detection and classification in ambulatory electrocardiograms using a deep neural network

A. Ng, Pranav Rajpurkar, Awni Y. Hannun, 2019, Nature Medicine.

MoCo-CXR: MoCo Pretraining Improves Representation and Transferability of Chest X-ray Models

A. Ng, Hari Sowrirajan, Jingbo Yang, 2020, 2010.05352.

Large-scale deep unsupervised learning using graphics processors

Rajat Raina, Andrew Y. Ng, Anand Madhavan, 2009, ICML '09.

PENet—a scalable deep-learning model for automated diagnosis of pulmonary embolism using volumetric CT imaging

Matthew P. Lungren, Pranav Rajpurkar, Jared A. Dunnmon, 2020, npj Digital Medicine.

Gap-filling eddy covariance methane fluxes: Comparison of machine learning model predictions and uncertainties at FLUXNET-CH4 wetlands

A. Ng, W. Oechel, G. Vourlitis, 2021 .

Data Noising as Smoothing in Neural Network Language Models pdf

Daniel Jurafsky, Andrew Y. Ng, Jiwei Li, 2017, ICLR.

CheXtransfer: performance and parameter efficiency of ImageNet models for chest X-Ray interpretation

A. Ng, P. Rajpurkar, Alexander Ke, 2021, CHIL.

PENet—a scalable deep-learning model for automated diagnosis of pulmonary embolism using volumetric CT imaging

Jared A. Dunnmon, A. Ng, P. Rajpurkar, 2020, NPJ Digital Medicine.

Improving Hospital Readmission Prediction using Individualized Utility Analysis

N. Shah, M. Ko, E. Chen, 2020, medRxiv.

AppendiXNet: Deep Learning for Diagnosis of Appendicitis from A Small Dataset of CT Exams Using Video Pretraining

A. Ng, P. Rajpurkar, C. Langlotz, 2020, Scientific Reports.

Multi-camera object detection for robotics

Andrew Y. Ng, Adam Coates, A. Ng, 2010, 2010 IEEE International Conference on Robotics and Automation.

Optimal Feature Extraction based Machine Learning Approach for Sarcasm Type Detection in News Headlines

Xirong Que, Mondher Bouazizi, Christopher D. Manning, 2020 .

Neural Text Style Transfer via Denoising and Reranking

Andrew Y. Ng, Joseph Lee, Dan Jurafsky, 2019, Proceedings of the Workshop on Methods for Optimizing and Evaluating Neural Language Generation.

Neural Language Correction with Character-Based Attention pdf

Daniel Jurafsky, Andrew Y. Ng, Naveen Arivazhagan, 2016, ArXiv.

CheXseen: Unseen Disease Detection for Deep Learning Interpretation of Chest X-rays

Ke M. Tran, A. Ng, P. Rajpurkar, 2021, ArXiv.

Exponential Family Sparse Coding with Application to Self-taught Learning

A. Ng, Honglak Lee, R. Raina, 2009, IJCAI.

Cardiologist-level arrhythmia detection and classification in ambulatory electrocardiograms using a deep neural network

Masoumeh Haghpanahi, Pranav Rajpurkar, Awni Y Hannun, 2019, Nature Medicine.

Impact of a deep learning assistant on the histopathologic classification of liver cancer.

Ryanne A. Brown, Simon B. Chen, A. Ng, 2020, NPJ digital medicine.

Learning Factor Graphs in Polynomial Time and Sample Complexity

Pieter Abbeel, Andrew Y. Ng, Daphne Koller, 2006, J. Mach. Learn. Res..

GloFlow: Global Image Alignment for Creation of Whole Slide Images for Pathology from Video pdf

Andrew Y. Ng, Pranav Rajpurkar, Eric Yang, 2020, ArXiv.

MedSelect: Selective Labeling for Medical Image Classification Combining Meta-Learning with Deep Reinforcement Learning

A. Ng, P. Rajpurkar, Damir Vrabac, 2021, ArXiv.

CheXseg: Combining Expert Annotations with DNN-generated Saliency Maps for X-ray Segmentation pdf

Andrew Y. Ng, Pranav Rajpurkar, Soham Gadgil, 2021, MIDL.

Deep Speech 2 : End-to-End Speech Recognition in English and Mandarin

A. Ng, Dario Amodei, P. LeGresley, 2015, ICML.

Deep learning-based Helicobacter pylori detection for histopathology: A diagnostic study

A. Ng, Sharon Zhou, H. Marklund, 2020 .

CheXphoto: 10, 000+ Photos and Transformations of Chest X-rays for Benchmarking Deep Learning Robustness

Andrew Y. Ng, Matthew P. Lungren, Pranav Rajpurkar, 2020, ML4H@NeurIPS.

Countdown Regression: Sharp and Calibrated Survival Predictions

Nigam H. Shah, Anand Avati, Kenneth Jung, 2018, UAI.

CheXbreak: Misclassification Identification for Deep Learning Models Interpreting Chest X-rays

A. Ng, P. Rajpurkar, E. Chen, 2021, MLHC.

Policy Search via Density Estimation

Andrew Y. Ng, Daphne Koller, Ronald Parr, 1999, NIPS.

i23 - Rapid Interactive 3D Reconstruction from a Single Image

Sebastian Thrun, Ashutosh Saxena, Christian Theobalt, 2009, VMV.

Integrating Visual and Range Data for Robotic Object Detection

A. Ng, M. Quigley, D. Koller, 2008 .

Cardiologist-Level Arrhythmia Detection with Convolutional Neural Networks

A. Ng, Pranav Rajpurkar, Awni Y. Hannun, 2017, arXiv.org.

Multimodal Deep Learning

A. Ng, A. Khosla, Honglak Lee, 2011, ICML.

Evaluating Progress in Automatic Chest X-Ray Radiology Report Generation

A. Ng, Pranav Rajpurkar, P. Rajpurkar, 2022, medRxiv.

Latent Dirichlet Allocation

Michael I. Jordan, A. Ng, D. Blei, 2009 .

Effect of Radiology Report Labeler Quality on Deep Learning Models for Chest X-Ray Interpretation pdf

Andrew Y. Ng, Akshay Smit, Pranav Rajpurkar, 2021, ArXiv.

Contextual search and name disambiguation in email using graphs

William W. Cohen, A. Ng, Einat Minkov, 2006, SIGIR.

Matrix Factorization

Michael I. Jordan, A. Ng, D. Blei, 2018, Encyclopedia of Social Network Analysis and Mining. 2nd Ed..

Learning Word Vectors for Sentiment Analysis

Andrew L. Maas, A. Ng, Raymond E. Daly, 2011, ACL.

CheXNet: Radiologist-Level Pneumonia Detection on Chest X-Rays with Deep Learning

A. Ng, Pranav Rajpurkar, C. Langlotz, 2017, ArXiv.

Increasing Deep Neural Network Acoustic Model Size for Large Vocabulary Continuous Speech Recognition

Andrew L. Maas, Christopher T. Lengerich, A. Ng, 2014, arXiv.org.