Andrew Y. Ng

发表

Tackling Climate Change with Machine Learning pdf

Yoshua Bengio, Demis Hassabis, David Rolnick, 2019, ACM Comput. Surv..

Online Bounds for Bayesian Algorithms

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

Learning omnidirectional path following using dimensionality reduction

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

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..

Reinforcement Learning and Apprenticeship Learning for Robotic Control

Andrew Y. Ng, 2006, Discovery Science.

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.

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

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

Deep learning for class-generic object detection pdf

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

Self-taught learning: transfer learning from unlabeled data

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

Joint calibration of multiple sensors

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

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.

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.

Guest editorial: Special issue on robot learning, Part A

Jan Peters, Andrew Y. Ng, 2009, Auton. Robots.

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

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

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.

Measuring Invariances in Deep Networks

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

Applying Online Search Techniques to Continuous-State Reinforcement Learning

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

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

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

Approximate Planning in Large POMDPs via Reusable Trajectories

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

Deep Learning: What's Next

Andrew Y. Ng, 2016, AAMAS.

Inverse Reinforcement Learning

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

Autonomous Helicopter Flight Using Reinforcement Learning

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

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..

Reinforcement Learning and Apprenticeship Learning for Robotic Control

Andrew Y. Ng, 2006, ALT.

Discriminative Training of Kalman Filters

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

Learning Grasp Strategies with Partial Shape Information

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

Using inaccurate models in reinforcement learning

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

Improving Text Classification by Shrinkage

Tom M. Mitchell, Andrew Y. Ng, Roni Rosenfeld, 1998 .

Semantic taxonomy induction

Andrew Y. Ng, Rion Snow, 2009 .

Discovery of Deep Structure from Unlabeled Data

Andrew Y. Ng, Christopher D. Manning, 2014 .

An Analysis of Single-Layer Networks in Unsupervised Feature Learning

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

Learning Factor Graphs in Polynomial Time & Sample Complexity

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

Improving Word Representations via Global Context and Multiple Word Prototypes

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

Policy Search by Dynamic Programming

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

Distance Metric Learning with Application to Clustering with Side-Information

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

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.

Abstract

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

Near-Bayesian exploration in polynomial time

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

Hierarchical Apprenticeship Learning with Application to Quadruped Locomotion

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

Apprenticeship learning for helicopter control

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

Scaling Up Machine Learning: Large-Scale Learning for Vision with GPUs

Rajat Raina, Andrew Y. Ng, Adam Coates, 2011 .

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

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

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

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

Parsing Natural Scenes and Natural Language with Recursive Neural Networks

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

From uncertainty to belief: inferring the specification within

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

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

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

Monocular depth perception and robotic grasping of novel objects

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

Large-scale deep unsupervised learning using graphics processors

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

Convolutional deep belief networks for scalable unsupervised learning of hierarchical representations

Honglak Lee, Andrew Y. Ng, Roger B. Grosse, 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.

Online and batch learning of pseudo-metrics

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

On Spectral Clustering: Analysis and an algorithm

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

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

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

Regularization and feature selection in least-squares temporal difference learning

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

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

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

Ambulatory Atrial Fibrillation Monitoring Using Wearable Photoplethysmography with Deep Learning

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

Tuned Models of Peer Assessment in MOOCs

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

Inverse Reinforcement Learning

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

Self-taught learning

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

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.

Exploration and apprenticeship learning in reinforcement learning

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

Simultaneous and Mapping With Sparse Extended Information

Zoubin Ghahramani, Andrew Y. Ng, Sebastian Thrun, 2014 .

Proceedings of the Twenty-Fifth Conference on Uncertainty in Artificial Intelligence (2009) pdf

Jeff A. Bilmes, Andrew Y. Ng, J. Bilmes, 2012, ArXiv.

Learning for control from multiple demonstrations

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

Tiled convolutional neural networks

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

Learning to Grasp Novel Objects Using Vision

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

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.

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

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

The online revolution: education for everyone

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

Deep learning assistance for the histopathologic diagnosis of Helicobacter pylori

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

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

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

A Factor Graph Model for Software Bug Finding

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

Improving palliative care with deep learning

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

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.

Deep learning with COTS HPC systems

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

Mechatronic design of an integrated robotic hand

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

The First Conference on E-mail and Anti-Spam

Joshua Goodman, Andrew Y. Ng, David Heckerman, 2005, AI Mag..

Stable algorithms for link analysis

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

Semantic Compositionality through Recursive Matrix-Vector Spaces

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

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.

Multimodal Deep Learning

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

On optimization methods for deep learning

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

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.

Grounded Compositional Semantics for Finding and Describing Images with Sentences

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

groupTime: preference based group scheduling

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

Sparse deep belief net model for visual area V2

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

Contextual search and name disambiguation in email using graphs

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

Learning Depth from Single Monocular Images

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

3-D Depth Reconstruction from a Single Still Image

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

Improving Text Classification by Shrinkage in a Hierarchy of Classes

Tom M. Mitchell, Andrew McCallum, Ronald Rosenfeld, 1998, ICML.

Exploring the Utility of ResearchCyc for Reasoning from Natural Language

Andrew Y. Ng, Christopher D. Manning, 2006 .

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).

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

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

Spam Deobfuscation using a Hidden Markov Model

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

Lexicon-Free Conversational Speech Recognition with Neural Networks

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

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

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

Learning sound location from a single microphone

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

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.

Fast Gaussian Process Regression using KD-Trees

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

Semi-Supervised Recursive Autoencoders for Predicting Sentiment Distributions

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

Recursive Deep Models for Semantic Compositionality Over a Sentiment Treebank

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

Efficient multiple hyperparameter learning for log-linear models

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

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.

Robotic Grasping of Novel Objects using Vision

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

Learning 3-D object orientation from images

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

Stable adaptive control with online learning

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

Make3D: Depth Perception from a Single Still Image

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

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.

Autonomous Helicopter Aerobatics through Apprenticeship Learning

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

The Online Revolution: Education at Scale

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

An approach to system modes and dynamics of the evolving Space Station Freedom

Andrew Y. Ng, Vinod J. Modi, Afzal Suleman, 1991 .

Zero-Shot Learning Through Cross-Modal Transfer

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

Neural Language Correction with Character-Based Attention pdf

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

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

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

High speed obstacle avoidance using monocular vision and reinforcement learning

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

Policy search via the signed derivative

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

Evaluating the Disentanglement of Deep Generative Models through Manifold Topology pdf

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

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

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

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

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

Shaping and policy search in reinforcement learning

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

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.

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.

Solving Uncertain Markov Decision Processes

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

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.

An Empirical Evaluation of Deep Learning on Highway Driving pdf

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

Deep Learning of Invariant Features via Simulated Fixations in Video

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

Classification with Hybrid Generative/Discriminative Models

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

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

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

Robust Textual Inference via Graph Matching

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

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

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

Approximate Inference A lgorithms for Two-Layer Bayesian Networks

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

Low-cost accelerometers for robotic manipulator perception

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

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

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

Learning random walk models for inducing word dependency distributions

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

Reasoning With Neural Tensor Networks for Knowledge Base Completion

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

Preventing "Overfitting" of Cross-Validation Data

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

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

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

Integrating Visual and Range Data for Robotic Object Detection

Andrew Y. Ng, Morgan Quigley, Stephen Gould, 2008, ECCV 2008.

Autonomous sign reading for semantic mapping

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

Autonomous Helicopter Flight via Reinforcement Learning

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

ICA with Reconstruction Cost for Efficient Overcomplete Feature Learning

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

i23 - Rapid Interactive 3D Reconstruction from a Single Image

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

Cardiologist-Level Arrhythmia Detection with Convolutional Neural Networks pdf

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

Noising and Denoising Natural Language: Diverse Backtranslation for Grammar Correction

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

NGBoost: Natural Gradient Boosting for Probabilistic Prediction pdf

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

Constructing informative priors using transfer learning

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

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

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

Synthesizing Object-Background Data for Large 3-d Datasets

Andrew Y. Ng, Stephen Gould, David Breeden, 2008 .

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).

Emergence of Object-Selective Features in Unsupervised Feature Learning

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

Efficient L1 Regularized Logistic Regression

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

Data augmentation with Mobius transformations pdf

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

Guest editorial: Special issue on robot learning, Part B

Jan Peters, Andrew Y. Ng, 2009, Auton. Robots.

Data Noising as Smoothing in Neural Network Language Models pdf

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

A majorization-minimization algorithm for (multiple) hyperparameter learning

Chuan-Sheng Foo, Andrew Y. Ng, Chuong B. Do, 2009, ICML '09.

Autonomous operation of novel elevators for robot navigation

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

Unsupervised feature learning for audio classification using convolutional deep belief networks

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

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.

Latent Dirichlet Allocation

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

An Application of Reinforcement Learning to Aerobatic Helicopter Flight

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

Selecting Receptive Fields in Deep Networks

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

Learning Word Vectors for Sentiment Analysis

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

Link Analysis, Eigenvectors and Stability

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

On Local Rewards and Scaling Distributed Reinforcement Learning

Andrew Y. Ng, J. Andrew Bagnell, 2005, NIPS.

Learning Syntactic Patterns for Automatic Hypernym Discovery

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

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

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

Learning Deep Energy Models

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

Learning Feature Representations with K-Means

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

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).

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

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

Efficient sparse coding algorithms

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

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.

STAIR: Hardware and Software Architecture

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

Energy Disaggregation via Discriminative Sparse Coding

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

Multi-camera object detection for robotics

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

Portable GPS Baseband Logging

Pieter Abbeel, Andrew Y. Ng, Morgan Quigley, 2007 .

Map-Reduce for Machine Learning on Multicore

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

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.

Sparse Filtering

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

On Random Weights and Unsupervised Feature Learning

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

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.

Simultaneous Localization and Mapping with Sparse Extended Information Filters

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

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.

Space-indexed dynamic programming: learning to follow trajectories

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

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.

Low-Cost Manipulation Powered by ROS

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

Robotic Grasping of Novel Objects

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

Data-Intensive Question Answering

Jimmy J. Lin, Susan T. Dumais, Michele Banko, 2001, TREC.

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..

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

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

Autonomous Helicopter Flight Using Reinforcement Learning

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

Approximate Dynamic Programming

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

Recursive Deep Learning on 3D Point Clouds

Andrew Y. Ng, 2012, NIPS 2012.

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.

Reading Digits in Natural Images with Unsupervised Feature Learning

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

Autonomous Inverted Helicopter Flight via Reinforcement Learning

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

Building DNN acoustic models for large vocabulary speech recognition

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

Convolutional-Recursive Deep Learning for 3D Object Classification

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

A Graphical Framework for Contextual Search and Name Disambiguation in Email

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

Recurrent Neural Networks for Noise Reduction in Robust ASR

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

Transfer learning for text classification

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

Discriminative structured models for biological sequence analysis

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

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

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

Short-Term Solar Irradiance Forecasting Using Calibrated Probabilistic Models pdf

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

Web question answering: is more always better?

Jimmy J. Lin, Susan T. Dumais, Michele Banko, 2002, SIGIR '02.

Unsupervised learning of hierarchical representations with convolutional deep belief networks

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

Reactive grasping using optical proximity sensors

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

Policy Search via Density Estimation

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

Pharmacokinetics of a novel formulation of ivermectin after administration to goats

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

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..

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

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

Large Scale Distributed Deep Networks

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

Semantic Taxonomy Induction from Heterogenous Evidence

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

Learning first-order Markov models for control

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

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.

Depth Estimation Using Monocular and Stereo Cues

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

Learning Factor Graphs in Polynomial Time and Sample Complexity

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

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..

Uncertainty in artificial intelligence : proceedings of the Twenty-fifth Conference (2009) : June 18-21, 2009, Montreal, Quebec

Jeff A. Bilmes, Andrew Y. Ng, David McAllester, 2009 .

An Experimental and Theoretical Comparison of Model Selection Methods

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

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

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

Robust Textual Inference Via Learning and Abductive Reasoning

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

Have we met? MDP based speaker ID for robot dialogue

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

A Fast Data Collection and Augmentation Procedure for Object Recognition

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

Learning to Merge Word Senses

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

Parsing with Compositional Vector Grammars

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

Grasping with application to an autonomous checkout robot

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

An efficient approach to dynamics and control of flexible multibody systems

Andrew Y. Ng, Vinod J. Modi, Afzal Suleman, 1993 .

Driverseat: Crowdstrapping Learning Tasks for Autonomous Driving pdf

Andrew Y. Ng, Tao Wang, Pranav Rajpurkar, 2015, ArXiv.

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).

Apprenticeship learning via inverse reinforcement learning

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

Learning vehicular dynamics, with application to modeling helicopters

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

Autonomous Autorotation of an RC Helicopter

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

Time Complexity of Sensor-Based Vehicle Routing

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

Predicting Inpatient Discharge Prioritization With Electronic Health Records pdf

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

Learning to open new doors

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

Dynamic Pooling and Unfolding Recursive Autoencoders for Paraphrase Detection

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

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..

An experimental and theoretical comparison of model selection methods

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

Evaluating the Disentanglement of Deep Generative Models through Manifold Topology pdf

Andrew Y. Ng, Gunnar E. Carlsson, Stefano Ermon, 2021, ICLR 2021 Poster.

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

Andrew Y. Ng, Pranav Rajpurkar, Ishaan Malhi, 2021, ArXiv.

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

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

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.

Evaluating the Disentanglement of Deep Generative Models through Manifold Topology pdf

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

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

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

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

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

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.

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

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

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

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

Active Perception : Interactive Manipulation for Improvin g Object Detection

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

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

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

NGBoost: Natural Gradient Boosting for Probabilistic Prediction pdf

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

Automatic Hilghter of Lengthy Legal Documents

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

STAIR: The STanford Artificial Intelligence Robot project

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