Andrew Y. Ng
Publication record assembled from the DBLP archive of ranked conferences.
Papers indexed
120
Venues
27
Active years
1995–2025
Best venue rank
A*
Where they publish
- A*ICML32 papers
- A*ICRA16 papers
- A*AAAI8 papers
- A*CVPR7 papers
- A*EMNLP7 papers
- A*IJCAI7 papers
- AIROS6 papers
- AUAI5 papers
- A*ACL4 papers
- A*ICCV3 papers
- ANAACL3 papers
- A*SIGIR3 papers
- A*ICLR2 papers
- A*KDD2 papers
- AInterspeech2 papers
- CISRR2 papers
- AMICCAI1 paper
- ACIKM1 paper
- BEDM1 paper
- BICPR1 paper
- AICDAR1 paper
- BALT1 paper
- A*CHI1 paper
- ADIS1 paper
- A*OSDI1 paper
- CWAFR1 paper
- A*COLT1 paper
Papers
120 indexed papers, newest first.
| Year | Venue | Title | Authors |
|---|---|---|---|
| 2025 | ICCV | Evaluating and Improving the Effectiveness of Synthetic Chest X-Rays for Medical Image Analysis. | 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 |
| 2021 | ICLR | Evaluating the Disentanglement of Deep Generative Models through Manifold Topology. | Sharon Zhou, Eric Zelikman, Fred Lu, Andrew Y. Ng, Gunnar E. Carlsson, Stefano Ermon |
| 2021 | MICCAI | GloFlow: Whole Slide Image Stitching from Video Using Optical Flow and Global Image Alignment. | Viswesh Krishna, Anirudh Joshi, Damir Vrabac, Philip L. Bulterys, Eric Yang, Sebastian Fernandez-Pol, Andrew Y. Ng, Pranav Rajpurkar |
| 2020 | CVPR | The 1st Agriculture-Vision Challenge: Methods and Results. | 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-Brre 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 | CVPR | Effective Data Fusion with Generalized Vegetation Index: Evidence from Land Cover Segmentation in Agriculture. | Hao Sheng, Xiao Chen, Jingyi Su, Ram Rajagopal, Andrew Y. Ng |
| 2020 | EMNLP | Combining Automatic Labelers and Expert Annotations for Accurate Radiology Report Labeling Using BERT. | Akshay Smit, Saahil Jain, Pranav Rajpurkar, Anuj Pareek, Andrew Y. Ng, Matthew P. Lungren |
| 2020 | ICML | NGBoost: Natural Gradient Boosting for Probabilistic Prediction. | Tony Duan, Anand Avati, Daisy Yi Ding, Khanh K. Thai, Sanjay Basu, Andrew Y. Ng, Alejandro Schuler |
| 2019 | AAAI | CheXpert: A Large Chest Radiograph Dataset with Uncertainty Labels and Expert Comparison. | 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 | KDD | Ambulatory Atrial Fibrillation Monitoring Using Wearable Photoplethysmography with Deep Learning. | Yichen Shen, Maxime Voisin, Alireza Aliamiri, Anand Avati, Awni Y. Hannun, Andrew Y. Ng |
| 2019 | UAI | Countdown Regression: Sharp and Calibrated Survival Predictions. | Anand Avati, Tony Duan, Sharon Zhou, Kenneth Jung, Nigam H. Shah, Andrew Y. Ng |
| 2018 | NAACL | Noising and Denoising Natural Language: Diverse Backtranslation for Grammar Correction. | Ziang Xie, Guillaume Genthial, Stanley Xie, Andrew Y. Ng, Dan Jurafsky |
| 2017 | ICLR | Data Noising as Smoothing in Neural Network Language Models. | Ziang Xie, Sida I. Wang, Jiwei Li, Daniel Lvy, Aiming Nie, Dan Jurafsky, Andrew Y. Ng |
| 2017 | ICML | Deep Voice: Real-time Neural Text-to-Speech. | Sercan mer 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 |
| 2016 | CVPR | End-to-End People Detection in Crowded Scenes. | Russell Stewart, Mykhaylo Andriluka, Andrew Y. Ng |
| 2016 | ICML | Deep Speech 2 : End-to-End Speech Recognition in English and Mandarin. | 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 |
| 2015 | NAACL | Lexicon-Free Conversational Speech Recognition with Neural Networks. | Andrew L. Maas, Ziang Xie, Dan Jurafsky, Andrew Y. Ng |
| 2013 | ACL | Parsing with Compositional Vector Grammars. | Richard Socher, John Bauer, Christopher D. Manning, Andrew Y. Ng |
| 2013 | CIKM | The online revolution: education for everyone. | Andrew Y. Ng |
| 2013 | EDM | Tuned Models of Peer Assessment in MOOCs. | Chris Piech, Jonathan Huang, Zhenghao Chen, Chuong B. Do, Andrew Y. Ng, Daphne Koller |
| 2013 | EMNLP | Recursive Deep Models for Semantic Compositionality Over a Sentiment Treebank. | Richard Socher, Alex Perelygin, Jean Wu, Jason Chuang, Christopher D. Manning, Andrew Y. Ng, Christopher Potts |
| 2013 | ICML | Deep learning with COTS HPC systems. | Adam Coates, Brody Huval, Tao Wang, David J. Wu, Bryan Catanzaro, Andrew Y. Ng |
| 2013 | KDD | The online revolution: education for everyone. | Andrew Y. Ng, Daphne Koller |
| 2012 | ACL | Improving Word Representations via Global Context and Multiple Word Prototypes. | Eric H. Huang, Richard Socher, Christopher D. Manning, Andrew Y. Ng |
| 2012 | EMNLP | Semantic Compositionality through Recursive Matrix-Vector Spaces. | Richard Socher, Brody Huval, Christopher D. Manning, Andrew Y. Ng |
| 2012 | ICML | Building high-level features using large scale unsupervised learning. | Quoc V. Le, Marc'Aurelio Ranzato, Rajat Monga, Matthieu Devin, Greg Corrado, Kai Chen, Jeffrey Dean, Andrew Y. Ng |
| 2012 | ICPR | End-to-end text recognition with convolutional neural networks. | Tao Wang, David J. Wu, Adam Coates, Andrew Y. Ng |
| 2012 | Interspeech | Recurrent Neural Networks for Noise Reduction in Robust ASR. | Andrew L. Maas, Quoc V. Le, Tyler M. O'Neil, Oriol Vinyals, Patrick Nguyen, Andrew Y. Ng |
| 2011 | ACL | Learning Word Vectors for Sentiment Analysis. | Andrew L. Maas, Raymond E. Daly, Peter T. Pham, Dan Huang, Andrew Y. Ng, Christopher Potts |
| 2011 | CVPR | Learning hierarchical invariant spatio-temporal features for action recognition with independent subspace analysis. | Quoc V. Le, Will Y. Zou, Serena Y. Yeung, Andrew Y. Ng |
| 2011 | EMNLP | Semi-Supervised Recursive Autoencoders for Predicting Sentiment Distributions. | Richard Socher, Jeffrey Pennington, Eric H. Huang, Andrew Y. Ng, Christopher D. Manning |
| 2011 | ICDAR | Text Detection and Character Recognition in Scene Images with Unsupervised Feature Learning. | Adam Coates, Blake Carpenter, Carl Case, Sanjeev Satheesh, Bipin Suresh, Tao Wang, David J. Wu, Andrew Y. Ng |
| 2011 | ICML | The Importance of Encoding Versus Training with Sparse Coding and Vector Quantization. | Adam Coates, Andrew Y. Ng |
| 2011 | ICML | On optimization methods for deep learning. | Quoc V. Le, Jiquan Ngiam, Adam Coates, Ahbik Lahiri, Bobby Prochnow, Andrew Y. Ng |
| 2011 | ICML | Learning Deep Energy Models. | Jiquan Ngiam, Zhenghao Chen, Pang Wei Koh, Andrew Y. Ng |
| 2011 | ICML | Multimodal Deep Learning. | Jiquan Ngiam, Aditya Khosla, Mingyu Kim, Juhan Nam, Honglak Lee, Andrew Y. Ng |
| 2011 | ICML | On Random Weights and Unsupervised Feature Learning. | Andrew M. Saxe, Pang Wei Koh, Zhenghao Chen, Maneesh Bhand, Bipin Suresh, Andrew Y. Ng |
| 2011 | ICML | Parsing Natural Scenes and Natural Language with Recursive Neural Networks. | Richard Socher, Cliff Chiung-Yu Lin, Andrew Y. Ng, Christopher D. Manning |
| 2011 | ICRA | Autonomous sign reading for semantic mapping. | Carl Case, Bipin Suresh, Adam Coates, Andrew Y. Ng |
| 2011 | ICRA | Grasping with application to an autonomous checkout robot. | Ellen Klingbeil, Deepak Rao, Blake Carpenter, Varun Ganapathi, Andrew Y. Ng, Oussama Khatib |
| 2011 | ICRA | A low-cost compliant 7-DOF robotic manipulator. | Morgan Quigley, Alan T. Asbeck, Andrew Y. Ng |
| 2010 | AAAI | Low-Cost Manipulation Powered by ROS. | Morgan Quigley, Alan T. Asbeck, Andrew Y. Ng |
| 2010 | CVPR | A Steiner tree approach to efficient object detection. | Olga Russakovsky, Andrew Y. Ng |
| 2010 | ICRA | Multi-camera object detection for robotics. | Adam Coates, Andrew Y. Ng |
| 2010 | ICRA | Autonomous operation of novel elevators for robot navigation. | Ellen Klingbeil, Blake Carpenter, Olga Russakovsky, Andrew Y. Ng |
| 2010 | ICRA | A probabilistic approach to mixed open-loop and closed-loop control, with application to extreme autonomous driving. | J. Zico Kolter, Christian Plagemann, David T. Jackson, Andrew Y. Ng, Sebastian Thrun |
| 2010 | ICRA | Learning to grasp objects with multiple contact points. | Quoc V. Le, David Kamm, Arda F. Kara, Andrew Y. Ng |
| 2010 | IROS | Learning to open new doors. | Ellen Klingbeil, Ashutosh Saxena, Andrew Y. Ng |
| 2010 | IROS | Low-cost accelerometers for robotic manipulator perception. | Morgan Quigley, Reuben D. Brewer, Sai Prashanth Soundararaj, Vijay Pradeep, Quoc V. Le, Andrew Y. Ng |
| 2010 | IROS | Grasping novel objects with depth segmentation. | Deepak Rao, Quoc V. Le, Thanathorn Phoka, Morgan Quigley, Attawith Sudsang, Andrew Y. Ng |
| 2009 | ICML | A majorization-minimization algorithm for (multiple) hyperparameter learning. | Chuan-Sheng Foo, Chuong B. Do, Andrew Y. Ng |
| 2009 | ICML | Near-Bayesian exploration in polynomial time. | J. Zico Kolter, Andrew Y. Ng |
| 2009 | ICML | Regularization and feature selection in least-squares temporal difference learning. | J. Zico Kolter, Andrew Y. Ng |
| 2009 | ICML | Convolutional deep belief networks for scalable unsupervised learning of hierarchical representations. | Honglak Lee, Roger B. Grosse, Rajesh Ranganath, Andrew Y. Ng |
| 2009 | ICML | Large-scale deep unsupervised learning using graphics processors. | Rajat Raina, Anand Madhavan, Andrew Y. Ng |
| 2009 | IJCAI | Exponential Family Sparse Coding with Application to Self-taught Learning. | Honglak Lee, Rajat Raina, Alex Teichman, Andrew Y. Ng |
| 2009 | ICRA | Reactive grasping using optical proximity sensors. | Kaijen Hsiao, Paul Nangeroni, Manfred Huber, Ashutosh Saxena, Andrew Y. Ng |
| 2009 | ICRA | Stereo vision and terrain modeling for quadruped robots. | J. Zico Kolter, Youngjun Kim, Andrew Y. Ng |
| 2009 | ICRA | Task-space trajectories via cubic spline optimization. | J. Zico Kolter, Andrew Y. Ng |
| 2009 | ICRA | High-accuracy 3D sensing for mobile manipulation: Improving object detection and door opening. | Morgan Quigley, Siddharth Batra, Stephen Gould, Ellen Klingbeil, Quoc V. Le, Ashley Wellman, Andrew Y. Ng |
| 2009 | IROS | Scalable learning for object detection with GPU hardware. | Adam Coates, Paul Baumstarck, Quoc V. Le, Andrew Y. Ng |
| 2009 | IROS | Joint calibration of multiple sensors. | Quoc V. Le, Andrew Y. Ng |
| 2009 | ICRA | Learning 3-D object orientation from images. | Ashutosh Saxena, Justin Driemeyer, Andrew Y. Ng |
| 2009 | ICRA | Learning sound location from a single microphone. | Ashutosh Saxena, Andrew Y. Ng |
| 2008 | AAAI | A Fast Data Collection and Augmentation Procedure for Object Recognition. | Benjamin Sapp, Ashutosh Saxena, Andrew Y. Ng |
| 2008 | AAAI | Make3D: Depth Perception from a Single Still Image. | Ashutosh Saxena, Min Sun, Andrew Y. Ng |
| 2008 | AAAI | Learning Grasp Strategies with Partial Shape Information. | Ashutosh Saxena, Lawson L. S. Wong, Andrew Y. Ng |
| 2008 | EMNLP | Cheap and Fast - But is it Good? Evaluating Non-Expert Annotations for Natural Language Tasks. | Rion Snow, Brendan O'Connor, Daniel Jurafsky, Andrew Y. Ng |
| 2008 | ICML | Learning for control from multiple demonstrations. | Adam Coates, Pieter Abbeel, Andrew Y. Ng |
| 2008 | ICML | Space-indexed dynamic programming: learning to follow trajectories. | J. Zico Kolter, Adam Coates, Andrew Y. Ng, Yi Gu, Charles DuHadway |
| 2008 | ICRA | A control architecture for quadruped locomotion over rough terrain. | J. Zico Kolter, Mike P. Rodgers, Andrew Y. Ng |
| 2008 | IROS | Apprenticeship learning for motion planning with application to parking lot navigation. | Pieter Abbeel, Dmitri Dolgov, Andrew Y. Ng, Sebastian Thrun |
| 2007 | EMNLP | Learning to Merge Word Senses. | Rion Snow, Sushant Prakash, Daniel Jurafsky, Andrew Y. Ng |
| 2007 | ICCV | Learning 3-D Scene Structure from a Single Still Image. | Ashutosh Saxena, Min Sun, Andrew Y. Ng |
| 2007 | ICCV | 3-D Reconstruction from Sparse Views using Monocular Vision. | Ashutosh Saxena, Min Sun, Andrew Y. Ng |
| 2007 | ICML | Self-taught learning: transfer learning from unlabeled data. | Rajat Raina, Alexis J. Battle, Honglak Lee, Benjamin Packer, Andrew Y. Ng |
| 2007 | IJCAI | Peripheral-Foveal Vision for Real-time Object Recognition and Tracking in Video. | Stephen Gould, Joakim Arfvidsson, Adrian Kaehler, Benjamin Sapp, Marius Messner, Gary R. Bradski, Paul Baumstarck, Sukwon Chung, Andrew Y. Ng |
| 2007 | IJCAI | A Factor Graph Model for Software Bug Finding. | Ted Kremenek, Andrew Y. Ng, Dawson R. Engler |
| 2007 | IJCAI | Probabilistic Mobile Manipulation in Dynamic Environments, with Application to Opening Doors. | Anna Petrovskaya, Andrew Y. Ng |
| 2007 | IJCAI | Depth Estimation Using Monocular and Stereo Cues. | Ashutosh Saxena, Jamie Schulte, Andrew Y. Ng |
| 2007 | ISRR | A Vision-Based System for Grasping Novel Objects in Cluttered Environments. | Ashutosh Saxena, Lawson L. S. Wong, Morgan Quigley, Andrew Y. Ng |
| 2007 | UAI | Shift-Invariance Sparse Coding for Audio Classification. | Roger B. Grosse, Rajat Raina, Helen Kwong, Andrew Y. Ng |
| 2006 | AAAI | Efficient L1 Regularized Logistic Regression. | Su-In Lee, Honglak Lee, Pieter Abbeel, Andrew Y. Ng |
| 2006 | ACL | Semantic Taxonomy Induction from Heterogenous Evidence. | Rion Snow, Daniel Jurafsky, Andrew Y. Ng |
| 2006 | ALT | Reinforcement Learning and Apprenticeship Learning for Robotic Control. | Andrew Y. Ng |
| 2006 | CHI | groupTime: preference based group scheduling. | Mike Brzozowski, Kendra Carattini, Scott R. Klemmer, Patrick Mihelich, Jiang Hu, Andrew Y. Ng |
| 2006 | CVPR | A Dynamic Bayesian Network Model for Autonomous 3D Reconstruction from a Single Indoor Image. | Erick Delage, Honglak Lee, Andrew Y. Ng |
| 2006 | DIS | Reinforcement Learning and Apprenticeship Learning for Robotic Control. | Andrew Y. Ng |
| 2006 | EMNLP | Solving the Problem of Cascading Errors: Approximate Bayesian Inference for Linguistic Annotation Pipelines. | Jenny Rose Finkel, Christopher D. Manning, Andrew Y. Ng |
| 2006 | ICML | Using inaccurate models in reinforcement learning. | Pieter Abbeel, Morgan Quigley, Andrew Y. Ng |
| 2006 | ICML | Constructing informative priors using transfer learning. | Rajat Raina, Andrew Y. Ng, Daphne Koller |
| 2006 | ICRA | Quadruped Robot Obstacle Negotiation via Reinforcement Learning. | Honglak Lee, Yirong Shen, Chih-Han Yu, Gurjeet Singh, Andrew Y. Ng |
| 2006 | ICRA | Bayesian Estimation for Autonomous Object Manipulation based on Tactile Sensors. | Anna Petrovskaya, Oussama Khatib, Sebastian Thrun, Andrew Y. Ng |
| 2006 | Interspeech | Have we met? MDP based speaker ID for robot dialogue. | Filip Krsmanovic, Curtis Spencer, Daniel Jurafsky, Andrew Y. Ng |
| 2006 | OSDI | From Uncertainty to Belief: Inferring the Specification Within. | Ted Kremenek, Paul Twohey, Godmar Back, Andrew Y. Ng, Dawson R. Engler |
| 2006 | SIGIR | Contextual search and name disambiguation in email using graphs. | Einat Minkov, William W. Cohen, Andrew Y. Ng |
| 2005 | AAAI | Robust Textual Inference Via Learning and Abductive Reasoning. | Rajat Raina, Andrew Y. Ng, Christopher D. Manning |
| 2005 | CVPR | Discriminative Learning of Markov Random Fields for Segmentation of 3D Scan Data. | Dragomir Anguelov, Benjamin Taskar, Vassil Chatalbashev, Daphne Koller, Dinkar Gupta, Geremy Heitz, Andrew Y. Ng |
| 2005 | ICML | Exploration and apprenticeship learning in reinforcement learning. | Pieter Abbeel, Andrew Y. Ng |
| 2005 | ICML | High speed obstacle avoidance using monocular vision and reinforcement learning. | Jeff Michels, Ashutosh Saxena, Andrew Y. Ng |
| 2005 | ISRR | Automatic Single-Image 3d Reconstructions of Indoor Manhattan World Scenes. | Erick Delage, Honglak Lee, Andrew Y. Ng |
| 2005 | NAACL | Robust Textual Inference via Graph Matching. | Aria Haghighi, Andrew Y. Ng, Christopher D. Manning |
| 2005 | UAI | Learning Factor Graphs in Polynomial Time & Sample Complexity. | Pieter Abbeel, Daphne Koller, Andrew Y. Ng |
| 2004 | ICML | Apprenticeship learning via inverse reinforcement learning. | Pieter Abbeel, Andrew Y. Ng |
| 2004 | ICML | Online and batch learning of pseudo-metrics. | Shai Shalev-Shwartz, Yoram Singer, Andrew Y. Ng |
| 2004 | ICML | Learning random walk models for inducing word dependency distributions. | Kristina Toutanova, Christopher D. Manning, Andrew Y. Ng |
| 2002 | SIGIR | Web question answering: is more always better?. | Susan T. Dumais, Michele Banko, Eric Brill, Jimmy Lin, Andrew Y. Ng |
| 2002 | WAFR | Simultaneous Mapping and Localization with Sparse Extended Information Filters: Theory and Initial Results. | Sebastian Thrun, Daphne Koller, Zoubin Ghahramani, Hugh F. Durrant-Whyte, Andrew Y. Ng |
| 2001 | ICML | Convergence rates of the Voting Gibbs classifier, with application to Bayesian feature selection. | Andrew Y. Ng, Michael I. Jordan |
| 2001 | IJCAI | Link Analysis, Eigenvectors and Stability. | Andrew Y. Ng, Alice X. Zheng, Michael I. Jordan |
| 2001 | SIGIR | Stable Algorithms for Link Analysis. | Alice X. Zheng, Andrew Y. Ng, Michael I. Jordan |
| 2000 | ICML | Algorithms for Inverse Reinforcement Learning. | Andrew Y. Ng, Stuart Russell |
| 2000 | UAI | PEGASUS: A policy search method for large MDPs and POMDPs. | Andrew Y. Ng, Michael I. Jordan |
| 1999 | ICML | Policy Invariance Under Reward Transformations: Theory and Application to Reward Shaping. | Andrew Y. Ng, Daishi Harada, Stuart Russell |
| 1999 | IJCAI | A Sparse Sampling Algorithm for Near-Optimal Planning in Large Markov Decision Processes. | Michael J. Kearns, Yishay Mansour, Andrew Y. Ng |
| 1998 | AAAI | Applying Online Search Techniques to Continuous-State Reinforcement Learning. | Scott Davies, Andrew Y. Ng, Andrew W. Moore |
| 1998 | ICML | Improving Text Classification by Shrinkage in a Hierarchy of Classes. | Andrew McCallum, Ronald Rosenfeld, Tom M. Mitchell, Andrew Y. Ng |
| 1998 | ICML | On Feature Selection: Learning with Exponentially Many Irrelevant Features as Training Examples. | Andrew Y. Ng |
| 1997 | ICML | Preventing "Overfitting" of Cross-Validation Data. | Andrew Y. Ng |
| 1997 | UAI | An Information-Theoretic Analysis of Hard and Soft Assignment Methods for Clustering. | Michael J. Kearns, Yishay Mansour, Andrew Y. Ng |
| 1995 | COLT | An Experimental and Theoretical Comparison of Model Selection Methods. | Michael J. Kearns, Yishay Mansour, Andrew Y. Ng, Dana Ron |