Andrew Y. Ng - RankMe

309 papers A* 81A 18B 5C 3Journal 106Unranked 90

Year	Rank	Type	Title / Venue / Authors
2025	—	`conf`	Evaluating and Improving the Effectiveness of Synthetic Chest X-Rays for Medical Image Analysis. ICCVW Eva Prakash, Jeya Maria Jose Valanarasu, Zhihong Chen, Eduardo Pontes Reis, Andrew Johnston, Anuj Pareek, Christian Bluethgen, Sergios Gatidis, Cameron Olsen, Akshay Chaudhari, Andrew Y. Ng, Curtis Langlotz
2025	J	`jnl`	MedAgentBench: Dataset for Benchmarking LLMs as Agents in Medical Applications. CoRR Yixing Jiang, Kameron C. Black, Gloria Geng, Danny Park, Andrew Y. Ng, Jonathan H. Chen
2025	J	`jnl`	STARC-9: A Large-scale Dataset for Multi-Class Tissue Classification for CRC Histopathology. CoRR Barathi Subramanian, Rathinaraja Jeyaraj, Mitchell Nevin Peterson, Terry Guo, Nigam Shah, Curtis P. Langlotz, Andrew Y. Ng, Jeanne Shen
2025	J	`jnl`	Spatiotemporal Pyramid Flow Matching for Climate Emulation. CoRR Jeremy Andrew Irvin, Jiaqi Han, Zikui Wang, Abdulaziz Alharbi, Yufei Zhao, Nomin-Erdene Bayarsaikhan, Daniele Visioni, Andrew Y. Ng, Duncan Watson-Parris
2025	J	`jnl`	UQ: Assessing Language Models on Unsolved Questions. CoRR Fan Nie, Ken Ziyu Liu, Zihao Wang, Rui Sun, Wei Liu, Weijia Shi, Huaxiu Yao, Linjun Zhang, Andrew Y. Ng, James Zou, Sanmi Koyejo, Yejin Choi, Percy Liang, Niklas Muennighoff
2024	J	`jnl`	A System for Automated Vehicle Damage Localization and Severity Estimation Using Deep Learning. IEEE Trans. Intell. Transp. Syst. Yuntao Ma, Hiva Ghanbari, Tianyuan Huang, Jeremy Irvin, Oliver Brady, Sofian Zalouk, Hao Sheng, Andrew Y. Ng, Ram Rajagopal, Mayur Narsude
2024	—	`conf`	Auto-Generating Weak Labels for Real & Synthetic Data to Improve Label-Scarce Medical Image Segmentation. MIDL Tanvi Deshpande, Eva Prakash, Elsie Gyang Ross, Curtis P. Langlotz, Andrew Y. Ng, Jeya Maria Jose Valanarasu
2024	J	`jnl`	Auto-Generating Weak Labels for Real & Synthetic Data to Improve Label-Scarce Medical Image Segmentation. CoRR Tanvi Deshpande, Eva Prakash, Elsie Gyang Ross, Curtis P. Langlotz, Andrew Y. Ng, Jeya Maria Jose Valanarasu
2024	J	`jnl`	CloudTracks: A Dataset for Localizing Ship Tracks in Satellite Images of Clouds. CoRR Muhammad Ahmed Chaudhry, Lyna Kim, Jeremy Irvin, Yuzu Ido, Sonia Chu, Jared Thomas Isobe, Andrew Y. Ng, Duncan Watson-Parris
2024	J	`jnl`	Evaluating and Improving the Effectiveness of Synthetic Chest X-Rays for Medical Image Analysis. CoRR Eva Prakash, Jeya Maria Jose Valanarasu, Zhihong Chen, Eduardo Pontes Reis, Andrew Johnston, Anuj Pareek, Christian Bluethgen, Sergios Gatidis, Cameron Olsen, Akshay Chaudhari, Andrew Y. Ng, Curtis P. Langlotz
2024	J	`jnl`	Many-Shot In-Context Learning in Multimodal Foundation Models. CoRR Yixing Jiang, Jeremy Irvin, Ji Hun Wang, Muhammad Ahmed Chaudhry, Jonathan H. Chen, Andrew Y. Ng
2024	J	`jnl`	Unlocking Robust Segmentation Across All Age Groups via Continual Learning. CoRR Chih-Ying Liu, Jeya Maria Jose Valanarasu, Camila González, Curtis P. Langlotz, Andrew Y. Ng, Sergios Gatidis
2023	J	`jnl`	An Empirical Study of Automated Mislabel Detection in Real World Vision Datasets. CoRR Maya Srikanth, Jeremy Irvin, Brian Wesley Hill, Felipe Godoy, Ishan Sabane, Andrew Y. Ng
2023	A*	`conf`	DataPerf: Benchmarks for Data-Centric AI Development. NeurIPS Mark Mazumder, Colby R. Banbury, Xiaozhe Yao, Bojan Karlas, William Gaviria Rojas, Sudnya Frederick Diamos, Greg Diamos, Lynn He, Alicia Parrish, Hannah Rose Kirk, Jessica Quaye, Charvi Rastogi, Douwe Kiela, David Jurado, David Kanter, Rafael Mosquera, Will Cukierski, Juan Ciro, Lora Aroyo, Bilge Acun, Lingjiao Chen, Mehul Raje, Max Bartolo, Evan Sabri Eyuboglu, Amirata Ghorbani, Emmett D. Goodman, Addison Howard, Oana Inel, Tariq Kane, Christine R. Kirkpatrick, D. Sculley, Tzu-Sheng Kuo, Jonas W. Mueller, Tristan Thrush, Joaquin Vanschoren, Margaret Warren, Adina Williams, Serena Yeung, Newsha Ardalani, Praveen K. Paritosh, Ce Zhang, James Y. Zou, Carole-Jean Wu, Cody Coleman, Andrew Y. Ng, Peter Mattson, Vijay Janapa Reddi
2023	J	`jnl`	Detecting Neighborhood Gentrification at Scale via Street-level Visual Data. CoRR Tianyuan Huang, Timothy Dai, Zhecheng Wang, Hesu Yoon, Hao Sheng, Andrew Y. Ng, Ram Rajagopal, Jackelyn Hwang
2023	J	`jnl`	Evaluating progress in automatic chest X-ray radiology report generation. Patterns Feiyang Yu, Mark Endo, Rayan Krishnan, Ian Pan, Andy Tsai, Eduardo Pontes Reis, Eduardo Kaiser Ururahy Nunes Fonseca, Henrique Min Ho Lee, Zahra Shakeri Hossein Abad, Andrew Y. Ng, Curtis P. Langlotz, Vasantha Kumar Venugopal, Pranav Rajpurkar
2023	J	`jnl`	How to Train Your CheXDragon: Training Chest X-Ray Models for Transfer to Novel Tasks and Healthcare Systems. CoRR Cara Van Uden, Jeremy Irvin, Mars Huang, Nathan Dean, Jason Carr, Andrew Y. Ng, Curtis P. Langlotz
2023	—	`conf`	LymphoML: An interpretable artificial intelligence-based method identifies morphologic features that correlate with lymphoma subtype. ML4H@NeurIPS Vivek Shankar, Xiaoli Yang, Vrishab Krishna, Brent Tan, Oscar Silva, Rebecca Rojansky, Andrew Y. Ng, Fabiola Valvert, Edward Briercheck, David Weinstock, Yasodha Natkunam, Sebastian Fernandez-Pol, Pranav Rajpurkar
2023	J	`jnl`	LymphoML: An interpretable artificial intelligence-based method identifies morphologic features that correlate with lymphoma subtype. CoRR Vivek Shankar, Xiaoli Yang, Vrishab Krishna, Brent Tan, Oscar Silva, Rebecca Rojansky, Andrew Y. Ng, Fabiola Valvert, Edward Briercheck, David Weinstock, Yasodha Natkunam, Sebastian Fernandez-Pol, Pranav Rajpurkar
2023	J	`jnl`	Tackling Climate Change with Machine Learning. ACM Comput. Surv. David Rolnick, Priya L. Donti, Lynn H. Kaack, Kelly Kochanski, Alexandre Lacoste, Kris Sankaran, Andrew Slavin Ross, Nikola Milojevic-Dupont, Natasha Jaques, Anna Waldman-Brown, Alexandra Sasha Luccioni, Tegan Maharaj, Evan D. Sherwin, S. Karthik Mukkavilli, Konrad P. Kording, Carla P. Gomes, Andrew Y. Ng, Demis Hassabis, John C. Platt, Felix Creutzig, Jennifer T. Chayes, Yoshua Bengio
2023	J	`jnl`	USat: A Unified Self-Supervised Encoder for Multi-Sensor Satellite Imagery. CoRR Jeremy Irvin, Lucas Tao, Joanne Zhou, Yuntao Ma, Langston Nashold, Benjamin Liu, Andrew Y. Ng
2023	J	`jnl`	Weakly-semi-supervised object detection in remotely sensed imagery. CoRR Ji Hun Wang, Jeremy Irvin, Beri Kohen Behar, Ha Tran, Raghav Samavedam, Quentin Hsu, Andrew Y. Ng
2022	J	`jnl`	Benchmarking saliency methods for chest X-ray interpretation. Nat. Mac. Intell. Adriel Saporta, Xiaotong Gui, Ashwin Agrawal, Anuj Pareek, Steven Q. H. Truong, Chanh D. T. Nguyen, Van Doan Ngo, Jayne Seekins, Francis G. Blankenberg, Andrew Y. Ng, Matthew P. Lungren, Pranav Rajpurkar
2022	J	`jnl`	Contrastive learning of heart and lung sounds for label-efficient diagnosis. Patterns Pratham N. Soni, Siyu Shi, Pranav R. Sriram, Andrew Y. Ng, Pranav Rajpurkar
2022	J	`jnl`	DataPerf: Benchmarks for Data-Centric AI Development. CoRR Mark Mazumder, Colby R. Banbury, Xiaozhe Yao, Bojan Karlas, William Gaviria Rojas, Sudnya Frederick Diamos, Greg Diamos, Lynn He, Douwe Kiela, David Jurado, David Kanter, Rafael Mosquera, Juan Ciro, Lora Aroyo, Bilge Acun, Sabri Eyuboglu, Amirata Ghorbani, Emmett D. Goodman, Tariq Kane, Christine R. Kirkpatrick, Tzu-Sheng Kuo, Jonas Mueller, Tristan Thrush, Joaquin Vanschoren, Margaret Warren, Adina Williams, Serena Yeung, Newsha Ardalani, Praveen K. Paritosh, Ce Zhang, James Zou, Carole-Jean Wu, Cody Coleman, Andrew Y. Ng, Peter Mattson, Vijay Janapa Reddi
2022	J	`jnl`	Deep Learning-Based Sparse Whole-Slide Image Analysis for the Diagnosis of Gastric Intestinal Metaplasia. CoRR Jon Braatz, Pranav Rajpurkar, Stephanie Zhang, Andrew Y. Ng, Jeanne Shen
2022	B	`conf`	Detecting Neighborhood Gentrification at Scale via Street-level Visual Data. IEEE Big Data Tianyuan Huang, Timothy Dai, Zhecheng Wang, Hesu Yoon, Hao Sheng, Andrew Y. Ng, Ram Rajagopal, Jackelyn Hwang
2022	J	`jnl`	Improving debris flow evacuation alerts in Taiwan using machine learning. CoRR Yi-Lin Tsai, Jeremy Irvin, Suhas Chundi, João Estacio Gaspar Araujo, Andrew Y. Ng, Christopher B. Field, Peter K. Kitanidis
2022	—	`conf`	METER-ML: A Multi-Sensor Earth Observation Benchmark for Automated Methane Source Mapping. CDCEO@IJCAI Bryan Zhu, Nicholas Lui, Jeremy Irvin, Jimmy Le, Sahil Tadwalkar, Chenghao Wang, Zutao Ouyang, Frankie Y. Liu, Andrew Y. Ng, Robert B. Jackson
2022	J	`jnl`	METER-ML: A Multi-sensor Earth Observation Benchmark for Automated Methane Source Mapping. CoRR Bryan Zhu, Nicholas Lui, Jeremy Irvin, Jimmy Le, Sahil Tadwalkar, Chenghao Wang, Zutao Ouyang, Frankie Y. Liu, Andrew Y. Ng, Robert B. Jackson
2022	—	`conf`	MedSelect: Selective Labeling for Medical Image Classification Using Meta-Learning. MIDL Damir Vrabac, Akshay Smit, Yujie He, Andrew Y. Ng, Andrew L. Beam, Pranav Rajpurkar
2022	J	`jnl`	Transfer learning enables prediction of myocardial injury from continuous single-lead electrocardiography. J. Am. Medical Informatics Assoc. Boyang Tom Jin, Raj Palleti, Siyu Shi, Andrew Y. Ng, James V. Quinn, Pranav Rajpurkar, David A. Kim
2021	—	`conf`	3KG: Contrastive Learning of 12-Lead Electrocardiograms using Physiologically-Inspired Augmentations. ML4H@NeurIPS Bryan Gopal, Ryan W. Han, Gautham Raghupathi, Andrew Y. Ng, Geoffrey H. Tison, Pranav Rajpurkar
2021	J	`jnl`	3KG: Contrastive Learning of 12-Lead Electrocardiograms using Physiologically-Inspired Augmentations. CoRR Bryan Gopal, Ryan W. Han, Gautham Raghupathi, Andrew Y. Ng, Geoffrey H. Tison, Pranav Rajpurkar
2021	J	`jnl`	Automated coronary calcium scoring using deep learning with multicenter external validation. npj Digit. Medicine David Eng, Christopher Chute, Nishith Khandwala, Pranav Rajpurkar, Jin Long, Sam Shleifer, Mohamed H. Khalaf, Alexander T. Sandhu, Fátima Rodriguez, David J. Maron, Saeed Seyyedi, Daniele Marin, Ilana Golub, Matthew J. Budoff, Felipe Kitamura, Marcelo Straus Takahashi, Ross W. Filice, Rajesh Shah, John Mongan, Kimberly Kallianos, Curtis P. Langlotz, Matthew P. Lungren, Andrew Y. Ng, Bhavik N. Patel
2021	—	`conf`	CheXbreak: Misclassification Identification for Deep Learning Models Interpreting Chest X-rays. MLHC Emma Chen, Andy Kim, Rayan Krishnan, Jin Long, Andrew Y. Ng, Pranav Rajpurkar
2021	J	`jnl`	CheXbreak: Misclassification Identification for Deep Learning Models Interpreting Chest X-rays. CoRR Emma Chen, Andy Kim, Rayan Krishnan, Jin Long, Andrew Y. Ng, Pranav Rajpurkar
2021	J	`jnl`	CheXseen: Unseen Disease Detection for Deep Learning Interpretation of Chest X-rays. CoRR Siyu Shi, Ishaan Malhi, Kevin Tran, Andrew Y. Ng, Pranav Rajpurkar
2021	—	`conf`	CheXseg: Combining Expert Annotations with DNN-generated Saliency Maps for X-ray Segmentation. MIDL Soham Uday Gadgil, Mark Endo, Emily Wen, Andrew Y. Ng, Pranav Rajpurkar
2021	J	`jnl`	CheXseg: Combining Expert Annotations with DNN-generated Saliency Maps for X-ray Segmentation. CoRR Soham Gadgil, Mark Endo, Emily Wen, Andrew Y. Ng, Pranav Rajpurkar
2021	J	`jnl`	CheXternal: Generalization of Deep Learning Models for Chest X-ray Interpretation to Photos of Chest X-rays and External Clinical Settings. CoRR Pranav Rajpurkar, Anirudh Joshi, Anuj Pareek, Andrew Y. Ng, Matthew P. Lungren
2021	—	`conf`	CheXternal: generalization of deep learning models for chest X-ray interpretation to photos of chest X-rays and external clinical settings. CHIL Pranav Rajpurkar, Anirudh Joshi, Anuj Pareek, Andrew Y. Ng, Matthew P. Lungren
2021	J	`jnl`	CheXtransfer: Performance and Parameter Efficiency of ImageNet Models for Chest X-Ray Interpretation. CoRR Alexander Ke, William Ellsworth, Oishi Banerjee, Andrew Y. Ng, Pranav Rajpurkar
2021	—	`conf`	CheXtransfer: performance and parameter efficiency of ImageNet models for chest X-Ray interpretation. CHIL Alexander Ke, William Ellsworth, Oishi Banerjee, Andrew Y. Ng, Pranav Rajpurkar
2021	J	`jnl`	Data augmentation with Mobius transformations. Mach. Learn. Sci. Technol. Sharon Zhou, Jiequan Zhang, Hang Jiang, Torbjörn Lundh, Andrew Y. Ng
2021	J	`jnl`	Effect of Radiology Report Labeler Quality on Deep Learning Models for Chest X-Ray Interpretation. CoRR Saahil Jain, Akshay Smit, Andrew Y. Ng, Pranav Rajpurkar
2021	A*	`conf`	Evaluating the Disentanglement of Deep Generative Models through Manifold Topology. ICLR Sharon Zhou, Eric Zelikman, Fred Lu, Andrew Y. Ng, Gunnar E. Carlsson, Stefano Ermon
2021	—	`conf`	GloFlow: Whole Slide Image Stitching from Video Using Optical Flow and Global Image Alignment. MICCAI (8) Viswesh Krishna, Anirudh Joshi, Damir Vrabac, Philip L. Bulterys, Eric Yang, Sebastian Fernandez-Pol, Andrew Y. Ng, Pranav Rajpurkar
2021	J	`jnl`	Learning Neighborhood Representation from Multi-Modal Multi-Graph: Image, Text, Mobility Graph and Beyond. CoRR Tianyuan Huang, Zhecheng Wang, Hao Sheng, Andrew Y. Ng, Ram Rajagopal
2021	—	`conf`	MedAug: Contrastive learning leveraging patient metadata improves representations for chest X-ray interpretation. MLHC Yen Nhi Truong Vu, Richard Wang, Niranjan Balachandar, Can Liu, Andrew Y. Ng, Pranav Rajpurkar
2021	J	`jnl`	MedAug: Contrastive learning leveraging patient metadata improves representations for chest X-ray interpretation. CoRR Yen Nhi Truong Vu, Richard Wang, Niranjan Balachandar, Can Liu, Andrew Y. Ng, Pranav Rajpurkar
2021	J	`jnl`	MedSelect: Selective Labeling for Medical Image Classification Combining Meta-Learning with Deep Reinforcement Learning. CoRR Akshay Smit, Damir Vrabac, Yujie He, Andrew Y. Ng, Andrew L. Beam, Pranav Rajpurkar
2021	—	`conf`	MoCo Pretraining Improves Representation and Transferability of Chest X-ray Models. MIDL Hari Sowrirajan, Jingbo Yang, Andrew Y. Ng, Pranav Rajpurkar
2021	—	`conf`	Q-Pain: A Question Answering Dataset to Measure Social Bias in Pain Management. NeurIPS Datasets and Benchmarks Cécile Logé, Emily Ross, David Yaw Amoah Dadey, Saahil Jain, Adriel Saporta, Andrew Y. Ng, Pranav Rajpurkar
2021	J	`jnl`	Q-Pain: A Question Answering Dataset to Measure Social Bias in Pain Management. CoRR Cécile Logé, Emily Ross, David Yaw Amoah Dadey, Saahil Jain, Adriel Saporta, Andrew Y. Ng, Pranav Rajpurkar
2021	—	`conf`	RadGraph: Extracting Clinical Entities and Relations from Radiology Reports. NeurIPS Datasets and Benchmarks Saahil Jain, Ashwin Agrawal, Adriel Saporta, Steven Q. H. Truong, Du Nguyen Duong, Tan Bui, Pierre J. Chambon, Yuhao Zhang, Matthew P. Lungren, Andrew Y. Ng, Curtis P. Langlotz, Pranav Rajpurkar
2021	J	`jnl`	RadGraph: Extracting Clinical Entities and Relations from Radiology Reports. CoRR Saahil Jain, Ashwin Agrawal, Adriel Saporta, Steven Q. H. Truong, Du Nguyen Duong, Tan Bui, Pierre J. Chambon, Yuhao Zhang, Matthew P. Lungren, Andrew Y. Ng, Curtis P. Langlotz, Pranav Rajpurkar
2021	—	`conf`	Retrieval-Based Chest X-Ray Report Generation Using a Pre-trained Contrastive Language-Image Model. ML4H@NeurIPS Mark Endo, Rayan Krishnan, Viswesh Krishna, Andrew Y. Ng, Pranav Rajpurkar
2021	—	`conf`	Unseen Disease Detection for Deep Learning Interpretation of Chest X-rays. MIDL Siyu Shi, Ishaan Malhi, Kevin Tran, Andrew Y. Ng, Pranav Rajpurkar
2021	J	`jnl`	VisualCheXbert: Addressing the Discrepancy Between Radiology Report Labels and Image Labels. CoRR Saahil Jain, Akshay Smit, Steven Q. H. Truong, Chanh D. T. Nguyen, Minh-Thanh Huynh, Mudit Jain, Victoria A. Young, Andrew Y. Ng, Matthew P. Lungren, Pranav Rajpurkar
2021	—	`conf`	VisualCheXbert: addressing the discrepancy between radiology report labels and image labels. CHIL Saahil Jain, Akshay Smit, Steven Q. H. Truong, Chanh D. T. Nguyen, Minh-Thanh Huynh, Mudit Jain, Victoria A. Young, Andrew Y. Ng, Matthew P. Lungren, Pranav Rajpurkar
2020	J	`jnl`	Author Correction: PENet - a scalable deep-learning model for automated diagnosis of pulmonary embolism using volumetric CT imaging. npj Digit. Medicine Shih-Cheng Huang, Tanay Kothari, Imon Banerjee, Christopher Chute, Robyn L. Ball, Norah Borus, Andrew C. Huang, Bhavik N. Patel, Pranav Rajpurkar, Jeremy Irvin, Jared Dunnmon, Joseph Bledsoe, Katie S. Shpanskaya, Abhay Dhaliwal, Roham Zamanian, Andrew Y. Ng, Matthew P. Lungren
2020	J	`jnl`	CheXaid: deep learning assistance for physician diagnosis of tuberculosis using chest x-rays in patients with HIV. npj Digit. Medicine Pranav Rajpurkar, Chloe O'Connell, Amit Schechter, Nishit Asnani, Jason Li, Amirhossein Kiani, Robyn L. Ball, Marc Mendelson, Gary Maartens, Daniël J. van Hoving, Rulan Griesel, Andrew Y. Ng, Tom H. Boyles, Matthew P. Lungren
2020	J	`jnl`	CheXbert: Combining Automatic Labelers and Expert Annotations for Accurate Radiology Report Labeling Using BERT. CoRR Akshay Smit, Saahil Jain, Pranav Rajpurkar, Anuj Pareek, Andrew Y. Ng, Matthew P. Lungren
2020	J	`jnl`	CheXpedition: Investigating Generalization Challenges for Translation of Chest X-Ray Algorithms to the Clinical Setting. CoRR Pranav Rajpurkar, Anirudh Joshi, Anuj Pareek, Phil Chen, Amirhossein Kiani, Jeremy Irvin, Andrew Y. Ng, Matthew P. Lungren
2020	—	`conf`	CheXphoto: 10, 000+ Photos and Transformations of Chest X-rays for Benchmarking Deep Learning Robustness. ML4H@NeurIPS Nick A. Phillips, Pranav Rajpurkar, Mark Sabini, Rayan Krishnan, Sharon Zhou, Anuj Pareek, Nguyet Minh Phu, Chris Wang, Mudit Jain, Du Nguyen Duong, Steven Q. H. Truong, Andrew Y. Ng, Matthew P. Lungren
2020	J	`jnl`	CheXphoto: 10, 000+ Smartphone Photos and Synthetic Photographic Transformations of Chest X-rays for Benchmarking Deep Learning Robustness. CoRR Nick A. Phillips, Pranav Rajpurkar, Mark Sabini, Rayan Krishnan, Sharon Zhou, Anuj Pareek, Nguyet Minh Phu, Chris Wang, Andrew Y. Ng, Matthew P. Lungren
2020	J	`jnl`	CheXphotogenic: Generalization of Deep Learning Models for Chest X-ray Interpretation to Photos of Chest X-rays. CoRR Pranav Rajpurkar, Anirudh Joshi, Anuj Pareek, Jeremy Irvin, Andrew Y. Ng, Matthew P. Lungren
2020	—	`conf`	Combining Automatic Labelers and Expert Annotations for Accurate Radiology Report Labeling Using BERT. EMNLP (1) Akshay Smit, Saahil Jain, Pranav Rajpurkar, Anuj Pareek, Andrew Y. Ng, Matthew P. Lungren
2020	J	`jnl`	DLBCL-Morph: Morphological features computed using deep learning for an annotated digital DLBCL image set. CoRR Damir Vrabac, Akshay Smit, Rebecca Rojansky, Yasodha Natkunam, Ranjana H. Advani, Andrew Y. Ng, Sebastian Fernandez-Pol, Pranav Rajpurkar
2020	J	`jnl`	Data augmentation with Möbius transformations. CoRR Sharon Zhou, Jiequan Zhang, Hang Jiang, Torbjörn Lundh, Andrew Y. Ng
2020	—	`conf`	Effective Data Fusion with Generalized Vegetation Index: Evidence from Land Cover Segmentation in Agriculture. CVPR Workshops Hao Sheng, Xiao Chen, Jingyi Su, Ram Rajagopal, Andrew Y. Ng
2020	J	`jnl`	Effective Data Fusion with Generalized Vegetation Index: Evidence from Land Cover Segmentation in Agriculture. CoRR Hao Sheng, Xiao Chen, Jingyi Su, Ram Rajagopal, Andrew Y. Ng
2020	J	`jnl`	Evaluating the Disentanglement of Deep Generative Models through Manifold Topology. CoRR Sharon Zhou, Eric Zelikman, Fred Lu, Andrew Y. Ng, Stefano Ermon
2020	J	`jnl`	ForestNet: Classifying Drivers of Deforestation in Indonesia using Deep Learning on Satellite Imagery. CoRR Jeremy Irvin, Hao Sheng, Neel Ramachandran, Sonja Johnson-Yu, Sharon Zhou, Kyle Story, Rose Rustowicz, Cooper Elsworth, Kemen Austin, Andrew Y. Ng
2020	J	`jnl`	GloFlow: Global Image Alignment for Creation of Whole Slide Images for Pathology from Video. CoRR Viswesh Krishna, Anirudh Joshi, Philip L. Bulterys, Eric Yang, Andrew Y. Ng, Pranav Rajpurkar
2020	J	`jnl`	Impact of a deep learning assistant on the histopathologic classification of liver cancer. npj Digit. Medicine Amirhossein Kiani, Bora Uyumazturk, Pranav Rajpurkar, Alex Wang, Rebecca Gao, Erik Jones, Yifan Yu, Curtis P. Langlotz, Robyn L. Ball, Thomas J. Montine, Brock A. Martin, Gerald J. Berry, Michael G. Ozawa, Florette K. Hazard, Ryanne A. Brown, Simon B. Chen, Mona Wood, Libby S. Allard, Lourdes Ylagan, Andrew Y. Ng, Jeanne Shen
2020	J	`jnl`	MoCo Pretraining Improves Representation and Transferability of Chest X-ray Models. CoRR Hari Sowrirajan, Jingbo Yang, Andrew Y. Ng, Pranav Rajpurkar
2020	A*	`conf`	NGBoost: Natural Gradient Boosting for Probabilistic Prediction. ICML Tony Duan, Anand Avati, Daisy Yi Ding, Khanh K. Thai, Sanjay Basu, Andrew Y. Ng, Alejandro Schuler
2020	J	`jnl`	OGNet: Towards a Global Oil and Gas Infrastructure Database using Deep Learning on Remotely Sensed Imagery. CoRR Hao Sheng, Jeremy Irvin, Sasankh Munukutla, Shawn Zhang, Christopher Cross, Kyle Story, Rose Rustowicz, Cooper Elsworth, Zutao Yang, Mark Omara, Ritesh Gautam, Robert B. Jackson, Andrew Y. Ng
2020	J	`jnl`	PENet - a scalable deep-learning model for automated diagnosis of pulmonary embolism using volumetric CT imaging. npj Digit. Medicine Shih-Cheng Huang, Tanay Kothari, Imon Banerjee, Christopher Chute, Robyn L. Ball, Norah Borus, Andrew C. Huang, Bhavik N. Patel, Pranav Rajpurkar, Jeremy Irvin, Jared Dunnmon, Joseph Bledsoe, Katie S. Shpanskaya, Abhay Dhaliwal, Roham Zamanian, Andrew Y. Ng, Matthew P. Lungren
2020	J	`jnl`	Short-Term Solar Irradiance Forecasting Using Calibrated Probabilistic Models. CoRR Eric Zelikman, Sharon Zhou, Jeremy Irvin, Cooper Raterink, Hao Sheng, Jack Kelly, Ram Rajagopal, Andrew Y. Ng, David John Gagne II
2020	—	`conf`	The 1st Agriculture-Vision Challenge: Methods and Results. CVPR Workshops Mang Tik Chiu, Xingqian Xu, Kai Wang, Jennifer A. Hobbs, Naira Hovakimyan, Thomas S. Huang, Honghui Shi, Yunchao Wei, Zilong Huang, Alexander G. Schwing, Robert Brunner, Ivan Dozier, Wyatt Dozier, Karen Ghandilyan, David Wilson, Hyunseong Park, Jun Hee Kim, Sungho Kim, Qinghui Liu, Michael C. Kampffmeyer, Robert Jenssen, Arnt-Børre Salberg, Alexandre Barbosa, Rodrigo G. Trevisan, Bingchen Zhao, Shaozuo Yu, Siwei Yang, Yin Wang, Hao Sheng, Xiao Chen, Jingyi Su, Ram Rajagopal, Andrew Y. Ng, Van Thong Huynh, Soo-Hyung Kim, In Seop Na, Ujjwal Baid, Shubham Innani, Prasad Dutande, Bhakti Baheti, Sanjay N. Talbar, Jianyu Tang
2020	J	`jnl`	The 1st Agriculture-Vision Challenge: Methods and Results. CoRR Mang Tik Chiu, Xingqian Xu, Kai Wang, Jennifer A. Hobbs, Naira Hovakimyan, Thomas S. Huang, Honghui Shi, Yunchao Wei, Zilong Huang, Alexander G. Schwing, Robert Brunner, Ivan Dozier, Wyatt Dozier, Karen Ghandilyan, David Wilson, Hyunseong Park, Jun Hee Kim, Sungho Kim, Qinghui Liu, Michael C. Kampffmeyer, Robert Jenssen, Arnt-Børre Salberg, Alexandre Barbosa, Rodrigo G. Trevisan, Bingchen Zhao, Shaozuo Yu, Siwei Yang, Yin Wang, Hao Sheng, Xiao Chen, Jingyi Su, Ram Rajagopal, Andrew Y. Ng, Van Thong Huynh, Soo-Hyung Kim, In Seop Na, Ujjwal Baid, Shubham Innani, Prasad Dutande, Bhakti Baheti, Sanjay N. Talbar, Jianyu Tang
2019	A*	`conf`	Ambulatory Atrial Fibrillation Monitoring Using Wearable Photoplethysmography with Deep Learning. KDD Yichen Shen, Maxime Voisin, Alireza Aliamiri, Anand Avati, Awni Y. Hannun, Andrew Y. Ng
2019	A*	`conf`	CheXpert: A Large Chest Radiograph Dataset with Uncertainty Labels and Expert Comparison. AAAI Jeremy Irvin, Pranav Rajpurkar, Michael Ko, Yifan Yu, Silviana Ciurea-Ilcus, Christopher Chute, Henrik Marklund, Behzad Haghgoo, Robyn L. Ball, Katie S. Shpanskaya, Jayne Seekins, David A. Mong, Safwan S. Halabi, Jesse K. Sandberg, Ricky Jones, David B. Larson, Curtis P. Langlotz, Bhavik N. Patel, Matthew P. Lungren, Andrew Y. Ng
2019	J	`jnl`	CheXpert: A Large Chest Radiograph Dataset with Uncertainty Labels and Expert Comparison. CoRR Jeremy Irvin, Pranav Rajpurkar, Michael Ko, Yifan Yu, Silviana Ciurea-Ilcus, Christopher Chute, Henrik Marklund, Behzad Haghgoo, Robyn L. Ball, Katie S. Shpanskaya, Jayne Seekins, David A. Mong, Safwan S. Halabi, Jesse K. Sandberg, Ricky Jones, David B. Larson, Curtis P. Langlotz, Bhavik N. Patel, Matthew P. Lungren, Andrew Y. Ng
2019	A	`conf`	Countdown Regression: Sharp and Calibrated Survival Predictions. UAI Anand Avati, Tony Duan, Sharon Zhou, Kenneth Jung, Nigam H. Shah, Andrew Y. Ng
2019	J	`jnl`	NGBoost: Natural Gradient Boosting for Probabilistic Prediction. CoRR Tony Duan, Anand Avati, Daisy Yi Ding, Sanjay Basu, Andrew Y. Ng, Alejandro Schuler
2019	J	`jnl`	Tackling Climate Change with Machine Learning. CoRR David Rolnick, Priya L. Donti, Lynn H. Kaack, Kelly Kochanski, Alexandre Lacoste, Kris Sankaran, Andrew Slavin Ross, Nikola Milojevic-Dupont, Natasha Jaques, Anna Waldman-Brown, Alexandra Luccioni, Tegan Maharaj, Evan D. Sherwin, S. Karthik Mukkavilli, Konrad P. Körding, Carla P. Gomes, Andrew Y. Ng, Demis Hassabis, John C. Platt, Felix Creutzig, Jennifer T. Chayes, Yoshua Bengio
2018	J	`jnl`	Countdown Regression: Sharp and Calibrated Survival Predictions. CoRR Anand Avati, Tony Duan, Kenneth Jung, Nigam H. Shah, Andrew Y. Ng
2018	J	`jnl`	Improving palliative care with deep learning. BMC Medical Informatics Decis. Mak. Anand Avati, Kenneth Jung, Stephanie Harman, Lance Downing, Andrew Y. Ng, Nigam H. Shah
2018	—	`conf`	Noising and Denoising Natural Language: Diverse Backtranslation for Grammar Correction. NAACL-HLT Ziang Xie, Guillaume Genthial, Stanley Xie, Andrew Y. Ng, Dan Jurafsky
2018	J	`jnl`	Predicting Inpatient Discharge Prioritization With Electronic Health Records. CoRR Anand Avati, Stephen Pfohl, Chris Lin, Thao Nguyen, Meng Zhang, Philip Hwang, Jessica Wetstone, Kenneth Jung, Andrew Y. Ng, Nigam H. Shah
2017	—	`ch.`	Autonomous Helicopter Flight Using Reinforcement Learning. Encyclopedia of Machine Learning and Data Mining Adam Coates, Pieter Abbeel, Andrew Y. Ng
2017	J	`jnl`	Building DNN acoustic models for large vocabulary speech recognition. Comput. Speech Lang. Andrew L. Maas, Peng Qi, Ziang Xie, Awni Y. Hannun, Christopher T. Lengerich, Daniel Jurafsky, Andrew Y. Ng
2017	J	`jnl`	Cardiologist-Level Arrhythmia Detection with Convolutional Neural Networks. CoRR Pranav Rajpurkar, Awni Y. Hannun, Masoumeh Haghpanahi, Codie Bourn, Andrew Y. Ng
2017	J	`jnl`	CheXNet: Radiologist-Level Pneumonia Detection on Chest X-Rays with Deep Learning. CoRR Pranav Rajpurkar, Jeremy Irvin, Kaylie Zhu, Brandon Yang, Hershel Mehta, Tony Duan, Daisy Yi Ding, Aarti Bagul, Curtis P. Langlotz, Katie S. Shpanskaya, Matthew P. Lungren, Andrew Y. Ng
2017	J	`jnl`	Comparing Speech and Keyboard Text Entry for Short Messages in Two Languages on Touchscreen Phones. Proc. ACM Interact. Mob. Wearable Ubiquitous Technol. Sherry Ruan, Jacob O. Wobbrock, Kenny Liou, Andrew Y. Ng, James A. Landay
2017	—	`conf`	Data Noising as Smoothing in Neural Network Language Models. ICLR (Poster) Ziang Xie, Sida I. Wang, Jiwei Li, Daniel Lévy, Aiming Nie, Dan Jurafsky, Andrew Y. Ng
2017	J	`jnl`	Data Noising as Smoothing in Neural Network Language Models. CoRR Ziang Xie, Sida I. Wang, Jiwei Li, Daniel Lévy, Aiming Nie, Dan Jurafsky, Andrew Y. Ng
2017	A*	`conf`	Deep Voice: Real-time Neural Text-to-Speech. ICML Sercan Ömer Arik, Mike Chrzanowski, Adam Coates, Gregory Frederick Diamos, Andrew Gibiansky, Yongguo Kang, Xian Li, John Miller, Andrew Y. Ng, Jonathan Raiman, Shubho Sengupta, Mohammad Shoeybi
2017	J	`jnl`	Improving Palliative Care with Deep Learning. CoRR Anand Avati, Kenneth Jung, Stephanie Harman, Lance Downing, Andrew Y. Ng, Nigam H. Shah
2017	—	`conf`	Improving palliative care with deep learning. BIBM Anand Avati, Kenneth Jung, Stephanie Harman, Lance Downing, Andrew Y. Ng, Nigam H. Shah
2017	—	`ch.`	Inverse Reinforcement Learning. Encyclopedia of Machine Learning and Data Mining Pieter Abbeel, Andrew Y. Ng
2017	J	`jnl`	MURA Dataset: Towards Radiologist-Level Abnormality Detection in Musculoskeletal Radiographs. CoRR Pranav Rajpurkar, Jeremy Irvin, Aarti Bagul, Daisy Yi Ding, Tony Duan, Hershel Mehta, Brandon Yang, Kaylie Zhu, Dillon Laird, Robyn L. Ball, Curtis P. Langlotz, Katie S. Shpanskaya, Matthew P. Lungren, Andrew Y. Ng
2016	A	`conf`	Deep Learning: What's Next. AAMAS Andrew Y. Ng
2016	A*	`conf`	Deep Speech 2 : End-to-End Speech Recognition in English and Mandarin. ICML Dario Amodei, Sundaram Ananthanarayanan, Rishita Anubhai, Jingliang Bai, Eric Battenberg, Carl Case, Jared Casper, Bryan Catanzaro, Jingdong Chen, Mike Chrzanowski, Adam Coates, Greg Diamos, Erich Elsen, Jesse H. Engel, Linxi Fan, Christopher Fougner, Awni Y. Hannun, Billy Jun, Tony Han, Patrick LeGresley, Xiangang Li, Libby Lin, Sharan Narang, Andrew Y. Ng, Sherjil Ozair, Ryan Prenger, Sheng Qian, Jonathan Raiman, Sanjeev Satheesh, David Seetapun, Shubho Sengupta, Chong Wang, Yi Wang, Zhiqian Wang, Bo Xiao, Yan Xie, Dani Yogatama, Jun Zhan, Zhenyao Zhu
2016	A*	`conf`	End-to-End People Detection in Crowded Scenes. CVPR Russell Stewart, Mykhaylo Andriluka, Andrew Y. Ng
2016	J	`jnl`	Neural Language Correction with Character-Based Attention. CoRR Ziang Xie, Anand Avati, Naveen Arivazhagan, Dan Jurafsky, Andrew Y. Ng
2016	J	`jnl`	Speech Is 3x Faster than Typing for English and Mandarin Text Entry on Mobile Devices. CoRR Sherry Ruan, Jacob O. Wobbrock, Kenny Liou, Andrew Y. Ng, James A. Landay
2016	J	`jnl`	Unsupervised Deep Learning Applied to Breast Density Segmentation and Mammographic Risk Scoring. IEEE Trans. Medical Imaging Michiel Kallenberg, Kersten Petersen, Mads Nielsen, Andrew Y. Ng, Pengfei Diao, Christian Igel, Celine M. Vachon, Katharina Holland, Rikke Rass Winkel, Nico Karssemeijer, Martin Lillholm
2015	J	`jnl`	An Empirical Evaluation of Deep Learning on Highway Driving. CoRR Brody Huval, Tao Wang, Sameep Tandon, Jeff Kiske, Will Song, Joel Pazhayampallil, Mykhaylo Andriluka, Pranav Rajpurkar, Toki Migimatsu, Royce Cheng-Yue, Fernando A. Mujica, Adam Coates, Andrew Y. Ng
2015	J	`jnl`	Deep Speech 2: End-to-End Speech Recognition in English and Mandarin. CoRR Dario Amodei, Rishita Anubhai, Eric Battenberg, Carl Case, Jared Casper, Bryan Catanzaro, Jingdong Chen, Mike Chrzanowski, Adam Coates, Greg Diamos, Erich Elsen, Jesse H. Engel, Linxi Fan, Christopher Fougner, Tony Han, Awni Y. Hannun, Billy Jun, Patrick LeGresley, Libby Lin, Sharan Narang, Andrew Y. Ng, Sherjil Ozair, Ryan Prenger, Jonathan Raiman, Sanjeev Satheesh, David Seetapun, Shubho Sengupta, Yi Wang, Zhiqian Wang, Chong Wang, Bo Xiao, Dani Yogatama, Jun Zhan, Zhenyao Zhu
2015	J	`jnl`	Driverseat: Crowdstrapping Learning Tasks for Autonomous Driving. CoRR Pranav Rajpurkar, Toki Migimatsu, Jeff Kiske, Royce Cheng-Yue, Sameep Tandon, Tao Wang, Andrew Y. Ng
2015	—	`conf`	Lexicon-Free Conversational Speech Recognition with Neural Networks. HLT-NAACL Andrew L. Maas, Ziang Xie, Dan Jurafsky, Andrew Y. Ng
2014	J	`jnl`	Deep Speech: Scaling up end-to-end speech recognition. CoRR Awni Y. Hannun, Carl Case, Jared Casper, Bryan Catanzaro, Greg Diamos, Erich Elsen, Ryan Prenger, Sanjeev Satheesh, Shubho Sengupta, Adam Coates, Andrew Y. Ng
2014	—	`conf`	Deep learning for class-generic object detection. ICLR (Workshop Poster) Brody Huval, Adam Coates, Andrew Y. Ng
2014	J	`jnl`	First-Pass Large Vocabulary Continuous Speech Recognition using Bi-Directional Recurrent DNNs. CoRR Andrew L. Maas, Awni Y. Hannun, Daniel Jurafsky, Andrew Y. Ng
2014	J	`jnl`	Grounded Compositional Semantics for Finding and Describing Images with Sentences. Trans. Assoc. Comput. Linguistics Richard Socher, Andrej Karpathy, Quoc V. Le, Christopher D. Manning, Andrew Y. Ng
2014	J	`jnl`	Increasing Deep Neural Network Acoustic Model Size for Large Vocabulary Continuous Speech Recognition. CoRR Andrew L. Maas, Awni Y. Hannun, Christopher T. Lengerich, Peng Qi, Daniel Jurafsky, Andrew Y. Ng
2014	J	`jnl`	Mechatronic design of an integrated robotic hand. Int. J. Robotics Res. Morgan Quigley, Curt Salisbury, Andrew Y. Ng, J. Kenneth Salisbury
2014	J	`jnl`	Offering Verified Credentials in Massive Open Online Courses: MOOCs and technology to advance learning and learning research (Ubiquity symposium). Ubiquity Andrew L. Maas, Chris Heather, Chuong B. Do, Relly Brandman, Daphne Koller, Andrew Y. Ng
2013	J	`jnl`	An Information-Theoretic Analysis of Hard and Soft Assignment Methods for Clustering CoRR Michael J. Kearns, Yishay Mansour, Andrew Y. Ng
2013	—	`conf`	Deep learning with COTS HPC systems. ICML (3) Adam Coates, Brody Huval, Tao Wang, David J. Wu, Bryan Catanzaro, Andrew Y. Ng
2013	—	`conf`	Learning New Facts From Knowledge Bases With Neural Tensor Networks and Semantic Word Vectors ICLR (Workshop Poster) Danqi Chen, Richard Socher, Christopher D. Manning, Andrew Y. Ng
2013	J	`jnl`	PEGASUS: A Policy Search Method for Large MDPs and POMDPs CoRR Andrew Y. Ng, Michael I. Jordan
2013	—	`conf`	Parsing with Compositional Vector Grammars. ACL (1) Richard Socher, John Bauer, Christopher D. Manning, Andrew Y. Ng
2013	—	`conf`	Reasoning With Neural Tensor Networks for Knowledge Base Completion. NIPS Richard Socher, Danqi Chen, Christopher D. Manning, Andrew Y. Ng
2013	A*	`conf`	Recursive Deep Models for Semantic Compositionality Over a Sentiment Treebank. EMNLP Richard Socher, Alex Perelygin, Jean Wu, Jason Chuang, Christopher D. Manning, Andrew Y. Ng, Christopher Potts
2013	A	`conf`	The online revolution: education for everyone. CIKM Andrew Y. Ng
2013	A*	`conf`	The online revolution: education for everyone. KDD Andrew Y. Ng, Daphne Koller
2013	B	`conf`	Tuned Models of Peer Assessment in MOOCs. EDM Chris Piech, Jonathan Huang, Zhenghao Chen, Chuong B. Do, Andrew Y. Ng, Daphne Koller
2013	J	`jnl`	Tuned Models of Peer Assessment in MOOCs. CoRR Chris Piech, Jonathan Huang, Zhenghao Chen, Chuong B. Do, Andrew Y. Ng, Daphne Koller
2013	—	`conf`	Zero-Shot Learning Through Cross-Modal Transfer ICLR (Workshop) Richard Socher, Milind Ganjoo, Hamsa Sridhar, Osbert Bastani, Christopher D. Manning, Andrew Y. Ng
2013	—	`conf`	Zero-Shot Learning Through Cross-Modal Transfer. NIPS Richard Socher, Milind Ganjoo, Christopher D. Manning, Andrew Y. Ng
2012	A*	`conf`	Building high-level features using large scale unsupervised learning. ICML Quoc V. Le, Marc'Aurelio Ranzato, Rajat Monga, Matthieu Devin, Greg Corrado, Kai Chen, Jeffrey Dean, Andrew Y. Ng
2012	—	`conf`	Convolutional-Recursive Deep Learning for 3D Object Classification. NIPS Richard Socher, Brody Huval, Bharath Putta Bath, Christopher D. Manning, Andrew Y. Ng
2012	—	`conf`	Deep Learning of Invariant Features via Simulated Fixations in Video. NIPS Will Y. Zou, Andrew Y. Ng, Shenghuo Zhu, Kai Yu
2012	—	`conf`	Emergence of Object-Selective Features in Unsupervised Feature Learning. NIPS Adam Coates, Andrej Karpathy, Andrew Y. Ng
2012	B	`conf`	End-to-end text recognition with convolutional neural networks. ICPR Tao Wang, David J. Wu, Adam Coates, Andrew Y. Ng
2012	—	`conf`	Improving Word Representations via Global Context and Multiple Word Prototypes. ACL (1) Eric H. Huang, Richard Socher, Christopher D. Manning, Andrew Y. Ng
2012	—	`conf`	Large Scale Distributed Deep Networks. NIPS Jeffrey Dean, Greg Corrado, Rajat Monga, Kai Chen, Matthieu Devin, Quoc V. Le, Mark Z. Mao, Marc'Aurelio Ranzato, Andrew W. Senior, Paul A. Tucker, Ke Yang, Andrew Y. Ng
2012	J	`jnl`	Learning Factor Graphs in Polynomial Time & Sample Complexity CoRR Pieter Abbeel, Daphne Koller, Andrew Y. Ng
2012	—	`ch.`	Learning Feature Representations with K-Means. Neural Networks: Tricks of the Trade (2nd ed.) Adam Coates, Andrew Y. Ng
2012	J	`jnl`	Proceedings of the Twenty-Fifth Conference on Uncertainty in Artificial Intelligence (2009) CoRR Jeff A. Bilmes, Andrew Y. Ng
2012	A	`conf`	Recurrent Neural Networks for Noise Reduction in Robust ASR. INTERSPEECH Andrew L. Maas, Quoc V. Le, Tyler M. O'Neil, Oriol Vinyals, Patrick Nguyen, Andrew Y. Ng
2012	—	`conf`	Semantic Compositionality through Recursive Matrix-Vector Spaces. EMNLP-CoNLL Richard Socher, Brody Huval, Christopher D. Manning, Andrew Y. Ng
2012	J	`jnl`	Shift-Invariance Sparse Coding for Audio Classification CoRR Roger B. Grosse, Rajat Raina, Helen Kwong, Andrew Y. Ng
2011	A*	`conf`	A low-cost compliant 7-DOF robotic manipulator. ICRA Morgan Quigley, Alan T. Asbeck, Andrew Y. Ng
2011	A	`conf`	An Analysis of Single-Layer Networks in Unsupervised Feature Learning. AISTATS Adam Coates, Andrew Y. Ng, Honglak Lee
2011	A*	`conf`	Autonomous sign reading for semantic mapping. ICRA Carl Case, Bipin Suresh, Adam Coates, Andrew Y. Ng
2011	J	`jnl`	Building high-level features using large scale unsupervised learning CoRR Quoc V. Le, Rajat Monga, Matthieu Devin, Greg Corrado, Kai Chen, Marc'Aurelio Ranzato, Jeffrey Dean, Andrew Y. Ng
2011	—	`conf`	Dynamic Pooling and Unfolding Recursive Autoencoders for Paraphrase Detection. NIPS Richard Socher, Eric H. Huang, Jeffrey Pennington, Andrew Y. Ng, Christopher D. Manning
2011	A*	`conf`	Grasping with application to an autonomous checkout robot. ICRA Ellen Klingbeil, Deepak Rao, Blake Carpenter, Varun Ganapathi, Andrew Y. Ng, Oussama Khatib
2011	—	`conf`	ICA with Reconstruction Cost for Efficient Overcomplete Feature Learning. NIPS Quoc V. Le, Alexandre Karpenko, Jiquan Ngiam, Andrew Y. Ng
2011	A*	`conf`	Learning Deep Energy Models. ICML Jiquan Ngiam, Zhenghao Chen, Pang Wei Koh, Andrew Y. Ng
2011	A*	`conf`	Learning Word Vectors for Sentiment Analysis. ACL Andrew L. Maas, Raymond E. Daly, Peter T. Pham, Dan Huang, Andrew Y. Ng, Christopher Potts
2011	A*	`conf`	Learning hierarchical invariant spatio-temporal features for action recognition with independent subspace analysis. CVPR Quoc V. Le, Will Y. Zou, Serena Y. Yeung, Andrew Y. Ng
2011	A*	`conf`	Multimodal Deep Learning. ICML Jiquan Ngiam, Aditya Khosla, Mingyu Kim, Juhan Nam, Honglak Lee, Andrew Y. Ng
2011	A*	`conf`	On Random Weights and Unsupervised Feature Learning. ICML Andrew M. Saxe, Pang Wei Koh, Zhenghao Chen, Maneesh Bhand, Bipin Suresh, Andrew Y. Ng
2011	A*	`conf`	On optimization methods for deep learning. ICML Quoc V. Le, Jiquan Ngiam, Adam Coates, Ahbik Lahiri, Bobby Prochnow, Andrew Y. Ng
2011	A*	`conf`	Parsing Natural Scenes and Natural Language with Recursive Neural Networks. ICML Richard Socher, Cliff Chiung-Yu Lin, Andrew Y. Ng, Christopher D. Manning
2011	—	`conf`	Selecting Receptive Fields in Deep Networks. NIPS Adam Coates, Andrew Y. Ng
2011	A*	`conf`	Semi-Supervised Recursive Autoencoders for Predicting Sentiment Distributions. EMNLP Richard Socher, Jeffrey Pennington, Eric H. Huang, Andrew Y. Ng, Christopher D. Manning
2011	—	`conf`	Sparse Filtering. NIPS Jiquan Ngiam, Pang Wei Koh, Zhenghao Chen, Sonia A. Bhaskar, Andrew Y. Ng
2011	A	`conf`	Text Detection and Character Recognition in Scene Images with Unsupervised Feature Learning. ICDAR Adam Coates, Blake Carpenter, Carl Case, Sanjeev Satheesh, Bipin Suresh, Tao Wang, David J. Wu, Andrew Y. Ng
2011	A*	`conf`	The Importance of Encoding Versus Training with Sparse Coding and Vector Quantization. ICML Adam Coates, Andrew Y. Ng
2011	J	`jnl`	The Stanford LittleDog: A learning and rapid replanning approach to quadruped locomotion. Int. J. Robotics Res. J. Zico Kolter, Andrew Y. Ng
2011	—	`conf`	Unsupervised learning models of primary cortical receptive fields and receptive field plasticity. NIPS Andrew M. Saxe, Maneesh Bhand, Ritvik Mudur, Bipin Suresh, Andrew Y. Ng
2011	J	`jnl`	Unsupervised learning of hierarchical representations with convolutional deep belief networks. Commun. ACM Honglak Lee, Roger B. Grosse, Rajesh Ranganath, Andrew Y. Ng
2010	A*	`conf`	A Steiner tree approach to efficient object detection. CVPR Olga Russakovsky, Andrew Y. Ng
2010	A*	`conf`	A probabilistic approach to mixed open-loop and closed-loop control, with application to extreme autonomous driving. ICRA J. Zico Kolter, Christian Plagemann, David T. Jackson, Andrew Y. Ng, Sebastian Thrun
2010	J	`jnl`	Autonomous Helicopter Aerobatics through Apprenticeship Learning. Int. J. Robotics Res. Pieter Abbeel, Adam Coates, Andrew Y. Ng
2010	—	`ch.`	Autonomous Helicopter Flight Using Reinforcement Learning. Encyclopedia of Machine Learning Adam Coates, Pieter Abbeel, Andrew Y. Ng
2010	A*	`conf`	Autonomous operation of novel elevators for robot navigation. ICRA Ellen Klingbeil, Blake Carpenter, Olga Russakovsky, Andrew Y. Ng
2010	—	`conf`	Energy Disaggregation via Discriminative Sparse Coding. NIPS J. Zico Kolter, Siddharth Batra, Andrew Y. Ng
2010	A	`conf`	Grasping novel objects with depth segmentation. IROS Deepak Rao, Quoc V. Le, Thanathorn Phoka, Morgan Quigley, Attawith Sudsang, Andrew Y. Ng
2010	—	`ch.`	Inverse Reinforcement Learning. Encyclopedia of Machine Learning Pieter Abbeel, Andrew Y. Ng
2010	A*	`conf`	Learning to grasp objects with multiple contact points. ICRA Quoc V. Le, David Kamm, Arda F. Kara, Andrew Y. Ng
2010	A	`conf`	Learning to open new doors. IROS Ellen Klingbeil, Ashutosh Saxena, Andrew Y. Ng
2010	—	`conf`	Low-Cost Manipulation Powered by ROS. Enabling Intelligence through Middleware Morgan Quigley, Alan T. Asbeck, Andrew Y. Ng
2010	A	`conf`	Low-cost accelerometers for robotic manipulator perception. IROS Morgan Quigley, Reuben D. Brewer, Sai Prashanth Soundararaj, Vijay Pradeep, Quoc V. Le, Andrew Y. Ng
2010	A*	`conf`	Multi-camera object detection for robotics. ICRA Adam Coates, Andrew Y. Ng
2010	—	`conf`	Tiled convolutional neural networks. NIPS Quoc V. Le, Jiquan Ngiam, Zhenghao Chen, Daniel Jin hao Chia, Pang Wei Koh, Andrew Y. Ng
2009	A*	`conf`	A majorization-minimization algorithm for (multiple) hyperparameter learning. ICML Chuan-Sheng Foo, Chuong B. Do, Andrew Y. Ng
2009	J	`jnl`	Apprenticeship learning for helicopter control. Commun. ACM Adam Coates, Pieter Abbeel, Andrew Y. Ng
2009	A*	`conf`	Convolutional deep belief networks for scalable unsupervised learning of hierarchical representations. ICML Honglak Lee, Roger B. Grosse, Rajesh Ranganath, Andrew Y. Ng
2009	A*	`conf`	Exponential Family Sparse Coding with Application to Self-taught Learning. IJCAI Honglak Lee, Rajat Raina, Alex Teichman, Andrew Y. Ng
2009	J	`jnl`	Guest editorial: Special issue on robot learning, Part A. Auton. Robots Jan Peters, Andrew Y. Ng
2009	J	`jnl`	Guest editorial: Special issue on robot learning, Part B. Auton. Robots Jan Peters, Andrew Y. Ng
2009	A*	`conf`	High-accuracy 3D sensing for mobile manipulation: Improving object detection and door opening. ICRA Morgan Quigley, Siddharth Batra, Stephen Gould, Ellen Klingbeil, Quoc V. Le, Ashley Wellman, Andrew Y. Ng
2009	A	`conf`	Joint calibration of multiple sensors. IROS Quoc V. Le, Andrew Y. Ng
2009	A*	`conf`	Large-scale deep unsupervised learning using graphics processors. ICML Rajat Raina, Anand Madhavan, Andrew Y. Ng
2009	A*	`conf`	Learning 3-D object orientation from images. ICRA Ashutosh Saxena, Justin Driemeyer, Andrew Y. Ng
2009	A*	`conf`	Learning sound location from a single microphone. ICRA Ashutosh Saxena, Andrew Y. Ng
2009	J	`jnl`	Make3D: Learning 3D Scene Structure from a Single Still Image. IEEE Trans. Pattern Anal. Mach. Intell. Ashutosh Saxena, Min Sun, Andrew Y. Ng
2009	—	`conf`	Measuring Invariances in Deep Networks. NIPS Ian J. Goodfellow, Quoc V. Le, Andrew M. Saxe, Honglak Lee, Andrew Y. Ng
2009	A*	`conf`	Near-Bayesian exploration in polynomial time. ICML J. Zico Kolter, Andrew Y. Ng
2009	—	`conf`	Policy search via the signed derivative. Robotics: Science and Systems J. Zico Kolter, Andrew Y. Ng
2009	A*	`conf`	Reactive grasping using optical proximity sensors. ICRA Kaijen Hsiao, Paul Nangeroni, Manfred Huber, Ashutosh Saxena, Andrew Y. Ng
2009	A*	`conf`	Regularization and feature selection in least-squares temporal difference learning. ICML J. Zico Kolter, Andrew Y. Ng
2009	A	`conf`	Scalable learning for object detection with GPU hardware. IROS Adam Coates, Paul Baumstarck, Quoc V. Le, Andrew Y. Ng
2009	A*	`conf`	Stereo vision and terrain modeling for quadruped robots. ICRA J. Zico Kolter, Youngjun Kim, Andrew Y. Ng
2009	A*	`conf`	Task-space trajectories via cubic spline optimization. ICRA J. Zico Kolter, Andrew Y. Ng
2009	A	`ed.`	UAI 2009, Proceedings of the Twenty-Fifth Conference on Uncertainty in Artificial Intelligence, Montreal, QC, Canada, June 18-21, 2009 UAI Jeff A. Bilmes, Andrew Y. Ng
2009	—	`conf`	Unsupervised feature learning for audio classification using convolutional deep belief networks. NIPS Honglak Lee, Peter T. Pham, Yan Largman, Andrew Y. Ng
2009	—	`conf`	i23 - Rapid Interactive 3D Reconstruction from a Single Image. VMV Savil Srivastava, Ashutosh Saxena, Christian Theobalt, Sebastian Thrun, Andrew Y. Ng
2008	J	`jnl`	3-D Depth Reconstruction from a Single Still Image. Int. J. Comput. Vis. Ashutosh Saxena, Sung H. Chung, Andrew Y. Ng
2008	A*	`conf`	A Fast Data Collection and Augmentation Procedure for Object Recognition. AAAI Benjamin Sapp, Ashutosh Saxena, Andrew Y. Ng
2008	A*	`conf`	A control architecture for quadruped locomotion over rough terrain. ICRA J. Zico Kolter, Mike P. Rodgers, Andrew Y. Ng
2008	A	`conf`	Apprenticeship learning for motion planning with application to parking lot navigation. IROS Pieter Abbeel, Dmitri Dolgov, Andrew Y. Ng, Sebastian Thrun
2008	—	`conf`	Autonomous Autorotation of an RC Helicopter. ISER Pieter Abbeel, Adam Coates, Timothy Hunter, Andrew Y. Ng
2008	A*	`conf`	Cheap and Fast - But is it Good? Evaluating Non-Expert Annotations for Natural Language Tasks. EMNLP Rion Snow, Brendan O'Connor, Daniel Jurafsky, Andrew Y. Ng
2008	A*	`conf`	Learning Grasp Strategies with Partial Shape Information. AAAI Ashutosh Saxena, Lawson L. S. Wong, Andrew Y. Ng
2008	A*	`conf`	Learning for control from multiple demonstrations. ICML Adam Coates, Pieter Abbeel, Andrew Y. Ng
2008	A*	`conf`	Make3D: Depth Perception from a Single Still Image. AAAI Ashutosh Saxena, Min Sun, Andrew Y. Ng
2008	J	`jnl`	Robotic Grasping of Novel Objects using Vision. Int. J. Robotics Res. Ashutosh Saxena, Justin Driemeyer, Andrew Y. Ng
2008	A*	`conf`	Space-indexed dynamic programming: learning to follow trajectories. ICML J. Zico Kolter, Adam Coates, Andrew Y. Ng, Yi Gu, Charles DuHadway
2007	A*	`conf`	3-D Reconstruction from Sparse Views using Monocular Vision. ICCV Ashutosh Saxena, Min Sun, Andrew Y. Ng
2007	A*	`conf`	A Factor Graph Model for Software Bug Finding. IJCAI Ted Kremenek, Andrew Y. Ng, Dawson R. Engler
2007	C	`conf`	A Vision-Based System for Grasping Novel Objects in Cluttered Environments. ISRR Ashutosh Saxena, Lawson L. S. Wong, Morgan Quigley, Andrew Y. Ng
2007	J	`jnl`	Autonomous Helicopter Tracking and Localization Using a Self-surveying Camera Array. Int. J. Robotics Res. Masayoshi Matsuoka, Alan Chen, Surya P. N. Singh, Adam Coates, Andrew Y. Ng, Sebastian Thrun
2007	A*	`conf`	Depth Estimation Using Monocular and Stereo Cues. IJCAI Ashutosh Saxena, Jamie Schulte, Andrew Y. Ng
2007	—	`conf`	Efficient multiple hyperparameter learning for log-linear models. NIPS Chuong B. Do, Chuan-Sheng Foo, Andrew Y. Ng
2007	—	`conf`	Hierarchical Apprenticeship Learning with Application to Quadruped Locomotion. NIPS J. Zico Kolter, Pieter Abbeel, Andrew Y. Ng
2007	A*	`conf`	Learning 3-D Scene Structure from a Single Still Image. ICCV Ashutosh Saxena, Min Sun, Andrew Y. Ng
2007	—	`conf`	Learning omnidirectional path following using dimensionality reduction. Robotics: Science and Systems J. Zico Kolter, Andrew Y. Ng
2007	—	`conf`	Learning to Merge Word Senses. EMNLP-CoNLL Rion Snow, Sushant Prakash, Daniel Jurafsky, Andrew Y. Ng
2007	A*	`conf`	Peripheral-Foveal Vision for Real-time Object Recognition and Tracking in Video. IJCAI Stephen Gould, Joakim Arfvidsson, Adrian Kaehler, Benjamin Sapp, Marius Messner, Gary R. Bradski, Paul Baumstarck, Sukwon Chung, Andrew Y. Ng
2007	A*	`conf`	Probabilistic Mobile Manipulation in Dynamic Environments, with Application to Opening Doors. IJCAI Anna Petrovskaya, Andrew Y. Ng
2007	A*	`conf`	Self-taught learning: transfer learning from unlabeled data. ICML Rajat Raina, Alexis J. Battle, Honglak Lee, Benjamin Packer, Andrew Y. Ng
2007	A	`conf`	Shift-Invariance Sparse Coding for Audio Classification. UAI Roger B. Grosse, Rajat Raina, Helen Kwong, Andrew Y. Ng
2007	—	`conf`	Sparse deep belief net model for visual area V2. NIPS Honglak Lee, Chaitanya Ekanadham, Andrew Y. Ng
2006	—	`conf`	A Dynamic Bayesian Network Model for Autonomous 3D Reconstruction from a Single Indoor Image. CVPR (2) Erick Delage, Honglak Lee, Andrew Y. Ng
2006	—	`conf`	An Application of Reinforcement Learning to Aerobatic Helicopter Flight. NIPS Pieter Abbeel, Adam Coates, Morgan Quigley, Andrew Y. Ng
2006	A*	`conf`	Bayesian Estimation for Autonomous Object Manipulation based on Tactile Sensors. ICRA Anna Petrovskaya, Oussama Khatib, Sebastian Thrun, Andrew Y. Ng
2006	A*	`conf`	Constructing informative priors using transfer learning. ICML Rajat Raina, Andrew Y. Ng, Daphne Koller
2006	A*	`conf`	Contextual search and name disambiguation in email using graphs. SIGIR Einat Minkov, William W. Cohen, Andrew Y. Ng
2006	A*	`conf`	Efficient L1 Regularized Logistic Regression. AAAI Su-In Lee, Honglak Lee, Pieter Abbeel, Andrew Y. Ng
2006	—	`conf`	Efficient sparse coding algorithms. NIPS Honglak Lee, Alexis J. Battle, Rajat Raina, Andrew Y. Ng
2006	A*	`conf`	From Uncertainty to Belief: Inferring the Specification Within. OSDI Ted Kremenek, Paul Twohey, Godmar Back, Andrew Y. Ng, Dawson R. Engler
2006	A	`conf`	Have we met? MDP based speaker ID for robot dialogue. INTERSPEECH Filip Krsmanovic, Curtis Spencer, Daniel Jurafsky, Andrew Y. Ng
2006	J	`jnl`	Learning Factor Graphs in Polynomial Time and Sample Complexity. J. Mach. Learn. Res. Pieter Abbeel, Daphne Koller, Andrew Y. Ng
2006	—	`conf`	Learning to Grasp Novel Objects Using Vision. ISER Ashutosh Saxena, Justin Driemeyer, Justin Kearns, Chioma Osondu, Andrew Y. Ng
2006	—	`conf`	Map-Reduce for Machine Learning on Multicore. NIPS Cheng-Tao Chu, Sang Kyun Kim, Yi-An Lin, Yuanyuan Yu, Gary R. Bradski, Andrew Y. Ng, Kunle Olukotun
2006	A*	`conf`	Quadruped Robot Obstacle Negotiation via Reinforcement Learning. ICRA Honglak Lee, Yirong Shen, Chih-Han Yu, Gurjeet Singh, Andrew Y. Ng
2006	B	`conf`	Reinforcement Learning and Apprenticeship Learning for Robotic Control. ALT Andrew Y. Ng
2006	B	`conf`	Reinforcement Learning and Apprenticeship Learning for Robotic Control. Discovery Science Andrew Y. Ng
2006	—	`conf`	Robotic Grasping of Novel Objects. NIPS Ashutosh Saxena, Justin Driemeyer, Justin Kearns, Andrew Y. Ng
2006	A*	`conf`	Semantic Taxonomy Induction from Heterogenous Evidence. ACL Rion Snow, Daniel Jurafsky, Andrew Y. Ng
2006	A*	`conf`	Solving the Problem of Cascading Errors: Approximate Bayesian Inference for Linguistic Annotation Pipelines. EMNLP Jenny Rose Finkel, Christopher D. Manning, Andrew Y. Ng
2006	A*	`conf`	Using inaccurate models in reinforcement learning. ICML Pieter Abbeel, Morgan Quigley, Andrew Y. Ng
2006	A*	`conf`	groupTime: preference based group scheduling. CHI Mike Brzozowski, Kendra Carattini, Scott R. Klemmer, Patrick Mihelich, Jiang Hu, Andrew Y. Ng
2005	C	`conf`	Automatic Single-Image 3d Reconstructions of Indoor Manhattan World Scenes. ISRR Erick Delage, Honglak Lee, Andrew Y. Ng
2005	—	`conf`	Autonomous Helicopter Tracking and Localization Using a Self-Surveying Camera Array. FSR Masayoshi Matsuoka, Alan Chen, Surya P. N. Singh, Adam Coates, Andrew Y. Ng, Sebastian Thrun
2005	—	`conf`	Discriminative Learning of Markov Random Fields for Segmentation of 3D Scan Data. CVPR (2) Dragomir Anguelov, Benjamin Taskar, Vassil Chatalbashev, Daphne Koller, Dinkar Gupta, Geremy Heitz, Andrew Y. Ng
2005	—	`conf`	Discriminative Training of Kalman Filters. Robotics: Science and Systems Pieter Abbeel, Adam Coates, Michael Montemerlo, Andrew Y. Ng, Sebastian Thrun
2005	A*	`conf`	Exploration and apprenticeship learning in reinforcement learning. ICML Pieter Abbeel, Andrew Y. Ng
2005	—	`conf`	Fast Gaussian Process Regression using KD-Trees. NIPS Yirong Shen, Andrew Y. Ng, Matthias W. Seeger
2005	A*	`conf`	High speed obstacle avoidance using monocular vision and reinforcement learning. ICML Jeff Michels, Ashutosh Saxena, Andrew Y. Ng
2005	—	`conf`	Learning Depth from Single Monocular Images. NIPS Ashutosh Saxena, Sung H. Chung, Andrew Y. Ng
2005	A	`conf`	Learning Factor Graphs in Polynomial Time & Sample Complexity. UAI Pieter Abbeel, Daphne Koller, Andrew Y. Ng
2005	—	`conf`	Learning vehicular dynamics, with application to modeling helicopters. NIPS Pieter Abbeel, Varun Ganapathi, Andrew Y. Ng
2005	—	`conf`	On Local Rewards and Scaling Distributed Reinforcement Learning. NIPS J. Andrew Bagnell, Andrew Y. Ng
2005	A*	`conf`	Robust Textual Inference Via Learning and Abductive Reasoning. AAAI Rajat Raina, Andrew Y. Ng, Christopher D. Manning
2005	—	`conf`	Robust Textual Inference via Graph Matching. HLT/EMNLP Aria Haghighi, Andrew Y. Ng, Christopher D. Manning
2005	—	`conf`	Spam Deobfuscation using a Hidden Markov Model. CEAS Honglak Lee, Andrew Y. Ng
2005	J	`jnl`	The First Conference on E-mail and Anti-Spam. AI Mag. David Heckerman, Tom Berson, Joshua Goodman, Andrew Y. Ng
2005	—	`conf`	Transfer learning for text classification. NIPS Chuong B. Do, Andrew Y. Ng
2004	A*	`conf`	Apprenticeship learning via inverse reinforcement learning. ICML Pieter Abbeel, Andrew Y. Ng
2004	—	`conf`	Autonomous Inverted Helicopter Flight via Reinforcement Learning. ISER Andrew Y. Ng, Adam Coates, Mark Diel, Varun Ganapathi, Jamie Schulte, Ben Tse, Eric Berger, Eric Liang
2004	—	`conf`	Learning Syntactic Patterns for Automatic Hypernym Discovery. NIPS Rion Snow, Daniel Jurafsky, Andrew Y. Ng
2004	—	`conf`	Learning first-order Markov models for control. NIPS Pieter Abbeel, Andrew Y. Ng
2004	A*	`conf`	Learning random walk models for inducing word dependency distributions. ICML Kristina Toutanova, Christopher D. Manning, Andrew Y. Ng
2004	—	`conf`	Online Bounds for Bayesian Algorithms. NIPS Sham M. Kakade, Andrew Y. Ng
2004	A*	`conf`	Online and batch learning of pseudo-metrics. ICML Shai Shalev-Shwartz, Yoram Singer, Andrew Y. Ng
2004	J	`jnl`	Simultaneous Localization and Mapping with Sparse Extended Information Filters. Int. J. Robotics Res. Sebastian Thrun, Yufeng Liu, Daphne Koller, Andrew Y. Ng, Zoubin Ghahramani, Hugh F. Durrant-Whyte
2004	—	`conf`	Stable adaptive control with online learning. NIPS Andrew Y. Ng, H. Jin Kim
2003	—	`conf`	Autonomous Helicopter Flight via Reinforcement Learning. NIPS Andrew Y. Ng, H. Jin Kim, Michael I. Jordan, Shankar Sastry
2003	—	`conf`	Classification with Hybrid Generative/Discriminative Models. NIPS Rajat Raina, Yirong Shen, Andrew Y. Ng, Andrew McCallum
2003	J	`jnl`	Latent Dirichlet Allocation. J. Mach. Learn. Res. David M. Blei, Andrew Y. Ng, Michael I. Jordan
2003	—	`conf`	Policy Search by Dynamic Programming. NIPS J. Andrew Bagnell, Sham M. Kakade, Andrew Y. Ng, Jeff G. Schneider
2002	J	`jnl`	A Sparse Sampling Algorithm for Near-Optimal Planning in Large Markov Decision Processes. Mach. Learn. Michael J. Kearns, Yishay Mansour, Andrew Y. Ng
2002	—	`conf`	Distance Metric Learning with Application to Clustering with Side-Information. NIPS Eric P. Xing, Andrew Y. Ng, Michael I. Jordan, Stuart Russell
2002	C	`conf`	Simultaneous Mapping and Localization with Sparse Extended Information Filters: Theory and Initial Results. WAFR Sebastian Thrun, Daphne Koller, Zoubin Ghahramani, Hugh F. Durrant-Whyte, Andrew Y. Ng
2002	A*	`conf`	Web question answering: is more always better?. SIGIR Susan T. Dumais, Michele Banko, Eric Brill, Jimmy Lin, Andrew Y. Ng
2001	A*	`conf`	Convergence rates of the Voting Gibbs classifier, with application to Bayesian feature selection. ICML Andrew Y. Ng, Michael I. Jordan
2001	—	`conf`	Data-Intensive Question Answering. TREC Eric Brill, Jimmy Lin, Michele Banko, Susan T. Dumais, Andrew Y. Ng
2001	—	`conf`	Latent Dirichlet Allocation. NIPS David M. Blei, Andrew Y. Ng, Michael I. Jordan
2001	A*	`conf`	Link Analysis, Eigenvectors and Stability. IJCAI Andrew Y. Ng, Alice X. Zheng, Michael I. Jordan
2001	—	`conf`	On Discriminative vs. Generative Classifiers: A comparison of logistic regression and naive Bayes. NIPS Andrew Y. Ng, Michael I. Jordan
2001	—	`conf`	On Spectral Clustering: Analysis and an algorithm. NIPS Andrew Y. Ng, Michael I. Jordan, Yair Weiss
2001	A*	`conf`	Stable Algorithms for Link Analysis. SIGIR Alice X. Zheng, Andrew Y. Ng, Michael I. Jordan
2000	A*	`conf`	Algorithms for Inverse Reinforcement Learning. ICML Andrew Y. Ng, Stuart Russell
2000	A	`conf`	PEGASUS: A policy search method for large MDPs and POMDPs. UAI Andrew Y. Ng, Michael I. Jordan
1999	A*	`conf`	A Sparse Sampling Algorithm for Near-Optimal Planning in Large Markov Decision Processes. IJCAI Michael J. Kearns, Yishay Mansour, Andrew Y. Ng
1999	—	`conf`	Approximate Inference A lgorithms for Two-Layer Bayesian Networks. NIPS Andrew Y. Ng, Michael I. Jordan
1999	—	`conf`	Approximate Planning in Large POMDPs via Reusable Trajectories. NIPS Michael J. Kearns, Yishay Mansour, Andrew Y. Ng
1999	A*	`conf`	Policy Invariance Under Reward Transformations: Theory and Application to Reward Shaping. ICML Andrew Y. Ng, Daishi Harada, Stuart Russell
1999	—	`conf`	Policy Search via Density Estimation. NIPS Andrew Y. Ng, Ronald Parr, Daphne Koller
1998	—	`ch.`	An Information-Theoretic Analysis of Hard and Soft Assignment Methods for Clustering. Learning in Graphical Models Michael J. Kearns, Yishay Mansour, Andrew Y. Ng
1998	—	`conf`	Applying Online Search Techniques to Continuous-State Reinforcement Learning. AAAI/IAAI Scott Davies, Andrew Y. Ng, Andrew W. Moore
1998	A*	`conf`	Improving Text Classification by Shrinkage in a Hierarchy of Classes. ICML Andrew McCallum, Ronald Rosenfeld, Tom M. Mitchell, Andrew Y. Ng
1998	A*	`conf`	On Feature Selection: Learning with Exponentially Many Irrelevant Features as Training Examples. ICML Andrew Y. Ng
1997	J	`jnl`	An Experimental and Theoretical Comparison of Model Selection Methods. Mach. Learn. Michael J. Kearns, Yishay Mansour, Andrew Y. Ng, Dana Ron
1997	A	`conf`	An Information-Theoretic Analysis of Hard and Soft Assignment Methods for Clustering. UAI Michael J. Kearns, Yishay Mansour, Andrew Y. Ng
1997	A*	`conf`	Preventing "Overfitting" of Cross-Validation Data. ICML Andrew Y. Ng
1995	A*	`conf`	An Experimental and Theoretical Comparison of Model Selection Methods. COLT Michael J. Kearns, Yishay Mansour, Andrew Y. Ng, Dana Ron