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Andrew Y. Ng: [Publications] [Author Rank by year] [Co-authors] [Prefers] [Cites] [Cited by]

Publications of Author

Scott Davies, Andrew Y. Ng, Andrew Moore
Applying Online Search Techniques to Continuous-State Reinforcement Learning. [Citation Graph (0, 0)][DBLP]
AAAI/IAAI, 1998, pp:753-760 [Conf]
Su-In Lee, Honglak Lee, Pieter Abbeel, Andrew Y. Ng
Efficient L1 Regularized Logistic Regression. [Citation Graph (0, 0)][DBLP]
AAAI, 2006, pp:- [Conf]
Rajat Raina, Andrew Y. Ng, Christopher D. Manning
Robust Textual Inference Via Learning and Abductive Reasoning. [Citation Graph (0, 0)][DBLP]
AAAI, 2005, pp:1099-1105 [Conf]
Rion Snow, Daniel Jurafsky, Andrew Y. Ng
Semantic Taxonomy Induction from Heterogenous Evidence. [Citation Graph (0, 0)][DBLP]
ACL, 2006, pp:- [Conf]
Andrew Y. Ng
Reinforcement Learning and Apprenticeship Learning for Robotic Control. [Citation Graph (0, 0)][DBLP]
ALT, 2006, pp:29-31 [Conf]
Honglak Lee, Andrew Y. Ng
Spam Deobfuscation using a Hidden Markov Model. [Citation Graph (0, 0)][DBLP]
CEAS, 2005, pp:- [Conf]
Mike Brzozowski, Kendra Carattini, Scott R. Klemmer, Patrick Mihelich, Jiang Hu, Andrew Y. Ng
groupTime: preference based group scheduling. [Citation Graph (0, 0)][DBLP]
CHI, 2006, pp:1047-1056 [Conf]
Michael J. Kearns, Yishay Mansour, Andrew Y. Ng, Dana Ron
An Experimental and Theoretical Comparison of Model Selection Methods. [Citation Graph (0, 0)][DBLP]
COLT, 1995, pp:21-30 [Conf]
Dragomir Anguelov, Benjamin Taskar, Vassil Chatalbashev, Daphne Koller, Dinkar Gupta, Geremy Heitz, Andrew Y. Ng
Discriminative Learning of Markov Random Fields for Segmentation of 3D Scan Data. [Citation Graph (0, 0)][DBLP]
CVPR (2), 2005, pp:169-176 [Conf]
Erick Delage, Honglak Lee, Andrew Y. Ng
A Dynamic Bayesian Network Model for Autonomous 3D Reconstruction from a Single Indoor Image. [Citation Graph (0, 0)][DBLP]
CVPR (2), 2006, pp:2418-2428 [Conf]
Andrew Ng
Reinforcement Learning and Apprenticeship Learning for Robotic Control. [Citation Graph (0, 0)][DBLP]
Discovery Science, 2006, pp:14- [Conf]
Pieter Abbeel, Andrew Y. Ng
Exploration and apprenticeship learning in reinforcement learning. [Citation Graph (0, 0)][DBLP]
ICML, 2005, pp:1-8 [Conf]
Pieter Abbeel, Morgan Quigley, Andrew Y. Ng
Using inaccurate models in reinforcement learning. [Citation Graph (0, 0)][DBLP]
ICML, 2006, pp:1-8 [Conf]
Andrew Y. Ng
Preventing "Overfitting" of Cross-Validation Data. [Citation Graph (0, 0)][DBLP]
ICML, 1997, pp:245-253 [Conf]
Andrew McCallum, Ronald Rosenfeld, Tom M. Mitchell, Andrew Y. Ng
Improving Text Classification by Shrinkage in a Hierarchy of Classes. [Citation Graph (0, 0)][DBLP]
ICML, 1998, pp:359-367 [Conf]
Andrew Y. Ng
On Feature Selection: Learning with Exponentially Many Irrelevant Features as Training Examples. [Citation Graph (0, 0)][DBLP]
ICML, 1998, pp:404-412 [Conf]
Jeff Michels, Ashutosh Saxena, Andrew Y. Ng
High speed obstacle avoidance using monocular vision and reinforcement learning. [Citation Graph (0, 0)][DBLP]
ICML, 2005, pp:593-600 [Conf]
Andrew Y. Ng, Daishi Harada, Stuart J. Russell
Policy Invariance Under Reward Transformations: Theory and Application to Reward Shaping. [Citation Graph (0, 0)][DBLP]
ICML, 1999, pp:278-287 [Conf]
Andrew Y. Ng, Michael I. Jordan
Convergence rates of the Voting Gibbs classifier, with application to Bayesian feature selection. [Citation Graph (0, 0)][DBLP]
ICML, 2001, pp:377-384 [Conf]
Andrew Y. Ng, Stuart J. Russell
Algorithms for Inverse Reinforcement Learning. [Citation Graph (0, 0)][DBLP]
ICML, 2000, pp:663-670 [Conf]
Pieter Abbeel, Andrew Y. Ng
Apprenticeship learning via inverse reinforcement learning. [Citation Graph (0, 0)][DBLP]
ICML, 2004, pp:- [Conf]
Rajat Raina, Andrew Y. Ng, Daphne Koller
Constructing informative priors using transfer learning. [Citation Graph (0, 0)][DBLP]
ICML, 2006, pp:713-720 [Conf]
Shai Shalev-Shwartz, Yoram Singer, Andrew Y. Ng
Online and batch learning of pseudo-metrics. [Citation Graph (0, 0)][DBLP]
ICML, 2004, pp:- [Conf]
Kristina Toutanova, Christopher D. Manning, Andrew Y. Ng
Learning random walk models for inducing word dependency distributions. [Citation Graph (0, 0)][DBLP]
ICML, 2004, pp:- [Conf]
Michael J. Kearns, Yishay Mansour, Andrew Y. Ng
A Sparse Sampling Algorithm for Near-Optimal Planning in Large Markov Decision Processes. [Citation Graph (0, 0)][DBLP]
IJCAI, 1999, pp:1324-1231 [Conf]
Andrew Y. Ng, Alice X. Zheng, Michael I. Jordan
Link Analysis, Eigenvectors and Stability. [Citation Graph (0, 0)][DBLP]
IJCAI, 2001, pp:903-910 [Conf]
Ashutosh Saxena, Jamie Schulte, Andrew Y. Ng
Depth Estimation Using Monocular and Stereo Cues. [Citation Graph (0, 0)][DBLP]
IJCAI, 2007, pp:2197-2203 [Conf]
Anna Petrovskaya, Andrew Y. Ng
Probabilistic Mobile Manipulation in Dynamic Environments, with Application to Opening Doors. [Citation Graph (0, 0)][DBLP]
IJCAI, 2007, pp:2178-2184 [Conf]
Ted Kremenek, Andrew Y. Ng, Dawson R. Engler
A Factor Graph Model for Software Bug Finding. [Citation Graph (0, 0)][DBLP]
IJCAI, 2007, pp:2510-2516 [Conf]
Stephen Gould, Joakim Arfvidsson, Adrian Kaehler, Benjamin Sapp, Marius Messner, Gary R. Bradski, Paul Baumstarck, Sukwon Chung, Andrew Y. Ng
Peripheral-Foveal Vision for Real-time Object Recognition and Tracking in Video. [Citation Graph (0, 0)][DBLP]
IJCAI, 2007, pp:2115-2121 [Conf]
Aria Haghighi, Andrew Y. Ng, Christopher D. Manning
Robust Textual Inference via Graph Matching. [Citation Graph (0, 0)][DBLP]
HLT/EMNLP, 2005, pp:- [Conf]
Pieter Abbeel, Varun Ganapathi, Andrew Y. Ng
Learning vehicular dynamics, with application to modeling helicopters. [Citation Graph (0, 0)][DBLP]
NIPS, 2005, pp:- [Conf]
Pieter Abbeel, Andrew Y. Ng
Learning first-order Markov models for control. [Citation Graph (0, 0)][DBLP]
NIPS, 2004, pp:- [Conf]
Chuong Do, Andrew Y. Ng
Transfer learning for text classification. [Citation Graph (0, 0)][DBLP]
NIPS, 2005, pp:- [Conf]
J. Andrew Bagnell, Sham Kakade, Andrew Y. Ng, Jeff G. Schneider
Policy Search by Dynamic Programming. [Citation Graph (0, 0)][DBLP]
NIPS, 2003, pp:- [Conf]
Drew Bagnell, Andrew Y. Ng
On Local Rewards and Scaling Distributed Reinforcement Learning. [Citation Graph (0, 0)][DBLP]
NIPS, 2005, pp:- [Conf]
David M. Blei, Andrew Y. Ng, Michael I. Jordan
Latent Dirichlet Allocation. [Citation Graph (0, 0)][DBLP]
NIPS, 2001, pp:601-608 [Conf]
Michael J. Kearns, Yishay Mansour, Andrew Y. Ng
Approximate Planning in Large POMDPs via Reusable Trajectories. [Citation Graph (0, 0)][DBLP]
NIPS, 1999, pp:1001-1007 [Conf]
Sham M. Kakade, Andrew Y. Ng
Online Bounds for Bayesian Algorithms. [Citation Graph (0, 0)][DBLP]
NIPS, 2004, pp:- [Conf]
Andrew Y. Ng, Michael I. Jordan
On Discriminative vs. Generative Classifiers: A comparison of logistic regression and naive Bayes. [Citation Graph (0, 0)][DBLP]
NIPS, 2001, pp:841-848 [Conf]
Andrew Y. Ng, Michael I. Jordan, Yair Weiss
On Spectral Clustering: Analysis and an algorithm. [Citation Graph (0, 0)][DBLP]
NIPS, 2001, pp:849-856 [Conf]
Andrew Y. Ng, Michael I. Jordan
Approximate Inference A lgorithms for Two-Layer Bayesian Networks. [Citation Graph (0, 0)][DBLP]
NIPS, 1999, pp:533-539 [Conf]
Andrew Y. Ng, H. Jin Kim
Stable adaptive control with online learning. [Citation Graph (0, 0)][DBLP]
NIPS, 2004, pp:- [Conf]
Andrew Y. Ng, H. Jin Kim, Michael I. Jordan, Shankar Sastry
Autonomous Helicopter Flight via Reinforcement Learning. [Citation Graph (0, 0)][DBLP]
NIPS, 2003, pp:- [Conf]
Andrew Y. Ng, Ronald Parr, Daphne Koller
Policy Search via Density Estimation. [Citation Graph (0, 0)][DBLP]
NIPS, 1999, pp:1022-1028 [Conf]
Rajat Raina, Yirong Shen, Andrew Y. Ng, Andrew McCallum
Classification with Hybrid Generative/Discriminative Models. [Citation Graph (0, 0)][DBLP]
NIPS, 2003, pp:- [Conf]
Ashutosh Saxena, Sung H. Chung, Andrew Y. Ng
Learning Depth from Single Monocular Images. [Citation Graph (0, 0)][DBLP]
NIPS, 2005, pp:- [Conf]
Yirong Shen, Andrew Y. Ng, Matthias Seeger
Fast Gaussian Process Regression using KD-Trees. [Citation Graph (0, 0)][DBLP]
NIPS, 2005, pp:- [Conf]
Rion Snow, Daniel Jurafsky, Andrew Y. Ng
Learning Syntactic Patterns for Automatic Hypernym Discovery. [Citation Graph (0, 0)][DBLP]
NIPS, 2004, pp:- [Conf]
Eric P. Xing, Andrew Y. Ng, Michael I. Jordan, Stuart J. Russell
Distance Metric Learning with Application to Clustering with Side-Information. [Citation Graph (0, 0)][DBLP]
NIPS, 2002, pp:505-512 [Conf]
Ted Kremenek, Paul Twohey, Godmar Back, Andrew Y. Ng, Dawson R. Engler
From Uncertainty to Belief: Inferring the Specification Within. [Citation Graph (0, 0)][DBLP]
OSDI, 2006, pp:161-176 [Conf]
Susan T. Dumais, Michele Banko, Eric Brill, Jimmy J. Lin, Andrew Y. Ng
Web question answering: is more always better?. [Citation Graph (0, 0)][DBLP]
SIGIR, 2002, pp:291-298 [Conf]
Einat Minkov, William W. Cohen, Andrew Y. Ng
Contextual search and name disambiguation in email using graphs. [Citation Graph (0, 0)][DBLP]
SIGIR, 2006, pp:27-34 [Conf]
Alice X. Zheng, Andrew Y. Ng, Michael I. Jordan
Stable Algorithms for Link Analysis. [Citation Graph (0, 0)][DBLP]
SIGIR, 2001, pp:258-266 [Conf]
Eric Brill, Jimmy J. Lin, Michele Banko, Susan T. Dumais, Andrew Y. Ng
Data-Intensive Question Answering. [Citation Graph (0, 0)][DBLP]
TREC, 2001, pp:- [Conf]
Michael J. Kearns, Yishay Mansour, Andrew Y. Ng
An Information-Theoretic Analysis of Hard and Soft Assignment Methods for Clustering. [Citation Graph (0, 0)][DBLP]
UAI, 1997, pp:282-293 [Conf]
Andrew Y. Ng, Michael I. Jordan
PEGASUS: A policy search method for large MDPs and POMDPs. [Citation Graph (0, 0)][DBLP]
UAI, 2000, pp:406-415 [Conf]
Pieter Abbeel, Adam Coates, Michael Montemerlo, Andrew Y. Ng, Sebastian Thrun
Discriminative Training of Kalman Filters. [Citation Graph (0, 0)][DBLP]
Robotics: Science and Systems, 2005, pp:289-296 [Conf]
Sebastian Thrun, Yufeng Liu, Daphne Koller, Andrew Y. Ng, Zoubin Ghahramani, Hugh F. Durrant-Whyte
Simultaneous Localization and Mapping with Sparse Extended Information Filters. [Citation Graph (0, 0)][DBLP]
I. J. Robotic Res., 2004, v:23, n:7-8, pp:693-716 [Journal]
David M. Blei, Andrew Y. Ng, Michael I. Jordan
Latent Dirichlet Allocation. [Citation Graph (0, 0)][DBLP]
Journal of Machine Learning Research, 2003, v:3, n:, pp:993-1022 [Journal]
Pieter Abbeel, Daphne Koller, Andrew Y. Ng
Learning Factor Graphs in Polynomial Time and Sample Complexity. [Citation Graph (0, 0)][DBLP]
Journal of Machine Learning Research, 2006, v:7, n:, pp:1743-1788 [Journal]
Michael J. Kearns, Yishay Mansour, Andrew Y. Ng
A Sparse Sampling Algorithm for Near-Optimal Planning in Large Markov Decision Processes. [Citation Graph (0, 0)][DBLP]
Machine Learning, 2002, v:49, n:2-3, pp:193-208 [Journal]
Michael J. Kearns, Yishay Mansour, Andrew Y. Ng, Dana Ron
An Experimental and Theoretical Comparison of Model Selection Methods. [Citation Graph (0, 0)][DBLP]
Machine Learning, 1997, v:27, n:1, pp:7-50 [Journal]
Rajat Raina, Alexis Battle, Honglak Lee, Benjamin Packer, Andrew Y. Ng
Self-taught learning: transfer learning from unlabeled data. [Citation Graph (0, 0)][DBLP]
ICML, 2007, pp:759-766 [Conf]
Cheng-Tao Chu, Sang Kyun Kim, Yi-An Lin, YuanYuan Yu, Gary R. Bradski, Andrew Y. Ng, Kunle Olukotun
Map-Reduce for Machine Learning on Multicore. [Citation Graph (0, 0)][DBLP]
NIPS, 2006, pp:281-288 [Conf]
Ashutosh Saxena, Justin Driemeyer, Justin Kearns, Andrew Y. Ng
Robotic Grasping of Novel Objects. [Citation Graph (0, 0)][DBLP]
NIPS, 2006, pp:1209-1216 [Conf]
Honglak Lee, Alexis Battle, Rajat Raina, Andrew Y. Ng
Efficient sparse coding algorithms. [Citation Graph (0, 0)][DBLP]
NIPS, 2006, pp:801-808 [Conf]
Pieter Abbeel, Adam Coates, Morgan Quigley, Andrew Y. Ng
An Application of Reinforcement Learning to Aerobatic Helicopter Flight. [Citation Graph (0, 0)][DBLP]
NIPS, 2006, pp:1-8 [Conf]
Pieter Abbeel, Daphne Koller, Andrew Y. Ng
Learning Factor Graphs in Polynomial Time & Sample Complexity. [Citation Graph (0, 0)][DBLP]
UAI, 2005, pp:1-9 [Conf]
A Fast Data Collection and Augmentation Procedure for Object Recognition. [Citation Graph (, )][DBLP]
Make3D: Depth Perception from a Single Still Image. [Citation Graph (, )][DBLP]
Learning Grasp Strategies with Partial Shape Information. [Citation Graph (, )][DBLP]
Learning 3-D Scene Structure from a Single Still Image. [Citation Graph (, )][DBLP]
3-D Reconstruction from Sparse Views using Monocular Vision. [Citation Graph (, )][DBLP]
Learning for control from multiple demonstrations. [Citation Graph (, )][DBLP]
Space-indexed dynamic programming: learning to follow trajectories. [Citation Graph (, )][DBLP]
Near-Bayesian exploration in polynomial time. [Citation Graph (, )][DBLP]
Large-scale deep unsupervised learning using graphics processors. [Citation Graph (, )][DBLP]
A majorization-minimization algorithm for (multiple) hyperparameter learning. [Citation Graph (, )][DBLP]
Convolutional deep belief networks for scalable unsupervised learning of hierarchical representations. [Citation Graph (, )][DBLP]
Regularization and feature selection in least-squares temporal difference learning. [Citation Graph (, )][DBLP]
Bayesian Estimation for Autonomous Object Manipulation based on Tactile Sensors. [Citation Graph (, )][DBLP]
Quadruped Robot Obstacle Negotiation via Reinforcement Learning. [Citation Graph (, )][DBLP]
A control architecture for quadruped locomotion over rough terrain. [Citation Graph (, )][DBLP]
Learning 3-D object orientation from images. [Citation Graph (, )][DBLP]
Learning sound location from a single microphone. [Citation Graph (, )][DBLP]
Task-space trajectories via cubic spline optimization. [Citation Graph (, )][DBLP]
High-accuracy 3D sensing for mobile manipulation: Improving object detection and door opening. [Citation Graph (, )][DBLP]
Reactive grasping using optical proximity sensors. [Citation Graph (, )][DBLP]
Stereo vision and terrain modeling for quadruped robots. [Citation Graph (, )][DBLP]
Autonomous operation of novel elevators for robot navigation. [Citation Graph (, )][DBLP]
A probabilistic approach to mixed open-loop and closed-loop control, with application to extreme autonomous driving. [Citation Graph (, )][DBLP]
Learning to grasp objects with multiple contact points. [Citation Graph (, )][DBLP]
Multi-camera object detection for robotics. [Citation Graph (, )][DBLP]
Exponential Family Sparse Coding with Application to Self-taught Learning. [Citation Graph (, )][DBLP]
Autonomous Inverted Helicopter Flight via Reinforcement Learning. [Citation Graph (, )][DBLP]
Learning to Grasp Novel Objects Using Vision. [Citation Graph (, )][DBLP]
Autonomous Autorotation of an RC Helicopter. [Citation Graph (, )][DBLP]
Hierarchical Apprenticeship Learning with Application to Quadruped Locomotion. [Citation Graph (, )][DBLP]
Efficient multiple hyperparameter learning for log-linear models. [Citation Graph (, )][DBLP]
Sparse deep belief net model for visual area V2. [Citation Graph (, )][DBLP]
i23 - Rapid Interactive 3D Reconstruction from a Single Image. [Citation Graph (, )][DBLP]
Learning omnidirectional path following using dimensionality reduction. [Citation Graph (, )][DBLP]
Automatic Single-Image 3d Reconstructions of Indoor Manhattan World Scenes. [Citation Graph (, )][DBLP]
Autonomous Helicopter Tracking and Localization Using a Self-Surveying Camera Array. [Citation Graph (, )][DBLP]
Apprenticeship learning for motion planning with application to parking lot navigation. [Citation Graph (, )][DBLP]
Joint calibration of multiple sensors. [Citation Graph (, )][DBLP]
Scalable learning for object detection with GPU hardware. [Citation Graph (, )][DBLP]
Cheap and Fast - But is it Good? Evaluating Non-Expert Annotations for Natural Language Tasks. [Citation Graph (, )][DBLP]
Learning to Merge Word Senses. [Citation Graph (, )][DBLP]
Solving the Problem of Cascading Errors: Approximate Bayesian Inference for Linguistic Annotation Pipelines. [Citation Graph (, )][DBLP]
Guest editorial: Special issue on robot learning, Part A. [Citation Graph (, )][DBLP]
Guest editorial: Special issue on robot learning, Part B. [Citation Graph (, )][DBLP]
Apprenticeship learning for helicopter control. [Citation Graph (, )][DBLP]

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