In AAAI, 2008. In NIPS 17, 2005. Senior, P. Tucker, K. Yang, A. Y. Ng. Approximate inference algorithms for two-layer Bayesian networks, [ps, Andrew Y. Ng, in Proceedings of the Thirteenth Annual Conference on Uncertainty pdf], Learning Factor Graphs in Polynomial Time and Sample Complexity, [pdf]. Ted Kremenek, Andrew Y. Ng and Dawson Engler. Learning for Control from Multiple Demonstrations, [ps, In Proceedings of the 44th Annual Meeting of the Association for Computational Linguistics (ACL), 2006. In NIPS 14,, 2002. pdf], Robust Textual Inference via Graph Matching, Ted Kremenek, Paul Twohey, Godmar Back, Andrew Y. Ng and Dawson Engler. Michael Kearns, Yishay Mansour and Andrew Y. Ng. pdf], Self-taught learning: Transfer learning from unlabeled data, Recurrent Neural Networks for Noise Reduction in Robust ASR. Andrew Y. Ng, Alice X. Zheng and Michael Jordan. (IJCAI-99), 1999. pdf] Stephen Gould, Joakim Arfvidsson, Adrian Kaehler, Benjamin Sapp, Honglak Lee, Michael Kearns, Yishay Mansour and Andrew Y. Ng. [ps, In NIPS*2010 Workshop on Deep Learning and Unsupervised Feature Learning. In NIPS 19, 2007. [ps, pdf], Stable adaptive control with online learning, Distinguished application paper award. In NIPS 14,, 2002. Ashutosh Saxena, Min Sun, and Andrew Y. Ng. Shai Shalev-Shwartz, Yoram Singer and Andrew Y. Ng. [ps, [ps, Michael Kearns, Yishay Mansour and Andrew Y. Ng. and Andrew Y. Ng. Honglak Lee and and Andrew Y. Ng. Stanford, CA 94305-9010 A preliminary version had also appeared in the NIPS*2010 Workshop on Deep Learning and Unsupervised Feature Learning. [ps, pdf] [ps, pdf] Improving Word Representations via Global Context and Multiple Word Prototypes. [ps, pdf], Probabilistic Mobile Manipulation in Dynamic Environments, with Application to Opening Doors, Yirong Shen, Andrew Y. Ng and Matthias Seeger. J. Zico Kolter and Andrew Y. Ng. pdf] J. Zico Kolter, Mike Rodgers and Andrew Y. Ng. Seventeenth International Conference on Machine Learning, 2000. pdf], An Application of Reinforcement Learning to Aerobatic Helicopter Flight, J. Andrew Bagnell and Andrew Y. Ng. [ps, Roger Grosse, Rajat Raina, Helen Kwong and Andrew Y. Ng. pdf] Michael Kearns, Yishay Mansour, Andrew Y. Ng and Dana Ron, [pdf], Make3D: Learning 3-D Scene Structure from a Single Still Image, in Proceedings of the Thirteenth Annual Conference on Uncertainty In Andrew Y. Ng, Alice X. Zheng and Michael Jordan. Masa Matsuoka, Surya Singh, Alan Chen, Adam Coates, Andrew Y. Ng and Sebastian Thrun. In NIPS 17, 2005. pdf], Learning Factor Graphs in Polynomial Time and Sample Complexity, pdf], Shift-Invariant Sparse Coding for Audio Classification, In ECCV workshop on Multi-camera and Multi-modal Sensor Fusion Algorithms and Applications (M2SFA2), 2008. In International Symposium on Experimental Robotics, 2004. From uncertainty to belief: Inferring the specification within, [ps, pdf], PEGASUS: A policy search method for large MDPs and POMDPs, Honglak Lee, Yan Largman, Peter Pham and Andrew Y. Ng. [ps, pdf]. Ashutosh Saxena, Sung Chung, and Andrew Y. Ng. pdf] Learning omnidirectional path following using dimensionality reduction, Ashutosh Saxena, Jamie Schulte and Andrew Y. Ng. [ps, pdf] In International Conference on Robotics and Automation (ICRA), 2011. [ps, 2007. Pieter Abbeel, Dmitri Dolgov, Andrew Y. Ng and Sebastian Thrun. [pdf], Unsupervised feature learning for audio classification using convolutional [ps, pdf] Jeff Michels, Ashutosh Saxena and Andrew Y. Ng. [pdf]. [pdf], Learning Sound Location from a Single Microphone, Stephen Gould, Paul Baumstarck, Morgan Quigley, Andrew Y. Ng and Daphne Koller. Machine learning, pdf, [ps, pdf], Learning random walk models for inducing word dependency probabilities, [ps, pdf], Improving Text Classification by Shrinkage in a Hierarchy of Classes, Learning factor graphs in polynomial time & sample complexity, Ashutosh Saxena, Lawson Wong, and Andrew Y. Ng. [ps, (2012). Gary Bradski, Andrew Y. Ng and Kunle Olukotun. SIGIR Conference on Research and Development in Information Retrieval, 2006. In CHI 2006. [ps, pdf] Kristina Toutanova, Christopher Manning and Andrew Y. Ng. Scott Davies, Andrew Y. Ng and Andrew Moore. on Artificial Intelligence (IJCAI-07), 2007. Andrew was also the … [pdf], A Fast Data Collection and Augmentation Procedure for Object Recognition, J. Zico Kolter, Mike Rodgers and Andrew Y. Ng. [ps, pdf] pdf], High-speed obstacle avoidance using monocular vision and reinforcement learning, [ps, pdf]. pdf, All Top Conferences; 7-50, 1997. [ps, Honglak Lee, Yirong Shen, Chih-Han Yu, Gurjeet Singh, and Andrew Y. Ng. In NIPS 18, 2006. in Artificial Intelligence, 1997. CS294A: STAIR (STanford AI Robot) project, Winter 2008. Quoc V. Le, Marc'Aurelio Ranzato, Rajat Monga, Matthieu Devin, Kai Chen, Greg S. Corrado, Jeffrey Dean and Andrew Y. Ng. In International Journal of Robotics Research (IJRR), 2010. supplementary material] In NIPS*2009. Integrating visual and range data for robotic object detection, In Computer Vision and Pattern Recognition (CVPR), 2011. 3D Representation for Recognition (3dRR-07), 2007. pdf] Ng was a co-founder and leader of Google Brain and a former chief scientist in Baidu and several thousand members of the company’s Artificial Intelligence Group. An earlier version had also been presented at the NIPS 2005 Workshop on Inductive Transfer. Carl Case, Bipin Suresh, Adam Coates and Andrew Y. Ng. Ellen Kling-beil, Blake Carpenter, Olga Russakovsky and Andrew Y. Ng. In AAAI (Nectar Track), 2008. in Proceedings of the Fourteenth International Conference on pdf], Portable GNSS Baseband Logging, [ps, in Proceedings of the Fifteenth International Conference on Rajat Raina, In NIPS 12, 2000. Andrew Ng. Robotic Grasping of Novel Objects, [ps, 3-D Reconstruction from Sparse Views using Monocular Vision , Rion Snow. pdf] STAIR (STanford AI Robot) project: Integrating tools from all the diverse areas In Proceedings of the Aria Haghighi, Andrew Y. Ng and Chris Manning. In Proceedings of the Project homepages: 2012. [ps, pdf], Preventing "Overfitting" of Cross-Validation data, [ps, pdf] [ps, pdf] YouTube. On Discriminative vs. Generative Classifiers: A comparison Morgan Quigley, Brian Gerkey, Ken Conley, Josh Faust, Tully Foote, Jeremy Leibs, Eric Berger, Rob Wheeler, and Andrew Y. Ng. Sham Kakade and Andrew Y. Ng. In Uncertainty in In NIPS*2010. Jenny Finkel, Chris Manning and Andrew Y. Ng. Exploration and apprenticeship learning in reinforcement learning, Twenty-first International Conference on Machine Learning, 2004. Research interests: Andrew L. Maas, Raymond E. Daly, Peter T. Pham, Dan Huang, Andrew Y. Ng, and Christopher Potts. Discriminative Learning of Markov Random Fields for Segmentation of 3D Range Data, [ps, pdf] Andrew Y. Ng, Ronald Parr and Daphne Koller. [ps, pdf]. In Proceedings of EMNLP 2006. [ps, pdf]. 3-D Reconstruction from Sparse Views using Monocular Vision , Large Scale Distributed Deep Networks. [ps, pdf] [ps, pdf], Online bounds for Bayesian algorithms, Ashutosh Saxena, Sung Chung, and Andrew Y. Ng. Ashutosh Saxena, Min Sun, and Andrew Y. Ng. Jenny Finkel, Chris Manning and Andrew Y. Ng. [ps, pdf] In Proceedings of EMNLP 2006. The 43 years old, Andrew Ng is a happily married man. Rajat Raina, Yirong Shen, Andrew Y. Ng and Andrew McCallum, In Proceedings of EMNLP 2007. Andrew Ng, founder & CEO of Landing AI and founder of deeplearning.ai, discusses key challenges facing AI deployments and possible solutions, ranging from techniques for working with small data to improving algorithms' robustness and generalizability to systematically planning out the full cycle of machine learning projects. In AAAI (Nectar Track), 2008. PhD students: [pdf], Space-indexed Dynamic Programming: Learning to Follow Trajectories, In International Conference on Robotics and Automation (ICRA), 2011. [pdf] on Artificial Intelligence (IJCAI-07), 2007. Latent Dirichlet Allocation, [ps, pdf], Preventing "Overfitting" of Cross-Validation data, In NIPS 15, 2003. In AAAI, 2008. [ps, Eric H. Huang, Richard Socher, Christopher D. Manning and Andrew Y. Ng In Proceedings of the Fifteenth National Conference on Artificial Intelligence (AAAI-98), 1998. [ps, Andrew Y. Ng and H. Jin Kim. In Proceedings of the Twenty-First National Conference on Artificial Intelligence (AAAI-06), 2006. [ps, SIGIR Conference on Research and Development in Information Retrieval, 2006. Scott Davies, Andrew Y. Ng and Andrew Moore. In Proceedings of EMNLP 2008. A.L. Michael Kearns, Yishay Mansour and Andrew Y. Ng. [pdf], Scalable Learning for Object Detection with GPU Hardware, In CHI 2006. Andrew Y. Ng. pdf], On Local Rewards and the Scalability of Distributed Reinforcement Learning, In NIPS 19, 2007. Hard and Soft Assignment Methods for Clustering, In NIPS*2010. A preliminary version had also appeared in the NIPS*2010 Workshop on Deep Learning and Unsupervised Feature Learning. Ashutosh Saxena, Sung H. Chung, and Andrew Y. Ng. [ps, pdf], Inverted autonomous helicopter flight via reinforcement learning, Andrew Ng, Chief Scientist at Baidu 1. [ps, In NIPS 19, 2007. Ted Kremenek, Paul Twohey, Godmar Back, Andrew Y. Ng and Dawson Engler. pdf], A Factor Graph Model for Software Bug Finding, Pieter Abbeel, Varun Ganapathi and Andrew Y. Ng. SIGIR Conference on Research and Development in Information Retrieval, 2006. [ps, pdf] In NIPS 12, 2000. In Proceedings of the 11th International Conference on Document Analysis and Recognition (ICDAR 2011), 2011. ICCV workshop on Virtual Representations and Modeling of Large-scale environments (VRML), [ps, pdf], Learning first order Markov models for control, Proceedings of Andrew Y. Ng Computer Science Department Stanford University Room 156, Gates Building Stanford, CA 94305-9010 . [ps, pdf]. (Online demo available.) In Uncertainty in [ps, pdf], Discriminative Learning of Markov Random Fields for Segmentation of 3D Range Data, Make3d: Building 3d models from a single still image. supplementary material], Apprenticeship Learning for Motion Planning with Application to Parking Lot Navigation, [ps, CS221: Artificial Intelligence: Principles and Techniques, Winter 2009. David Blei, Andrew Y. Ng and Michael Jordan. An Information-Theoretic Analysis of Rajat Raina, Andrew Y. Ng and Daphne Koller. Chuong Do, Chuan-Sheng Foo, Andrew Y. Ng. Andrew Y. Ng and Michael Jordan. It’s everything you’ve ever wanted to know about data, told by the people who know it best. Rajat Raina, Andrew Y. Ng and Chris Manning. [pdf] Benjaminn Sapp, Ashutosh Saxena, and Andrew Y. Ng. Morgan Quigley, 3-D Reconstruction from Sparse Views using Monocular Vision , In NIPS*2007. In Proceedings of the Conference on Computer Vision and Pattern Recognition (CVPR), 2005. Algorithms for inverse reinforcement learning, [ps, pdf] He is an associate professor at the University of Stanford. Semantic taxonomy induction from heterogenous evidence, Hard and Soft Assignment Methods for Clustering, In Proceedings of the Ninth International Conference on Spoken Language Processing (InterSpeech--ICSLP), 2006. [ps, In AAAI, 2008. In the International Journal of Computer Vision (IJCV), 2007. In ECCV workshop on Multi-camera and Multi-modal Sensor Fusion Algorithms and Applications (M2SFA2), [ps, In 11th International Symposium on Experimental Robotics (ISER), 2008. In Proceedings of the Twenty-third Conference on Uncertainty in Artificial Intelligence, 2007. [pdf], Learning grasp strategies with partial shape information, Andrew Y. Ng and Michael Jordan. The importance of encoding versus training with sparse coding and vector quantization, pdf] Ashutosh Saxena, Min Sun, and Andrew Y. Ng. pdf], Robust Textual Inference via Graph Matching, In NIPS 18, 2006. Teaching: In Proceedings of the International Conference on Intelligent Robots and Systems (IROS), 2009. in Learning in Graphical Models, Ed. In Proceedings of the International Symposium on Robotics Research (ISRR), 2005. Andrew Y. Ng, Adam Coates, Mark Diel, Varun Ganapathi, Jamie Schulte, An earlier version had also been presented at the NIPS 2005 Workshop on Inductive Transfer. In Proceedings of the Twenty-third International Conference on Machine Learning, 2006. as Training Examples, Ashutosh Saxena, Min Sun, and Andrew Y. Ng. In Proceedings of the Twenty-ninth Annual International ACM In Proceedings of the International Conference on Robotics and Automation (ICRA), 2006. In NIPS 17, 2005. [pdf], A Complete Control Architecture for Quadruped Locomotion Over Rough Terrain, SIGIR Conference on Research and Development in Information Retrieval, 2001. [pdf], Quadruped robot obstacle negotiation via reinforcement learning, Honglak Lee and and Andrew Y. Ng. [ps, Also a book chapter In Robotics Science and Systems (RSS) Pieter Abbeel, Adam Coates, Timothy Hunter and Andrew Y. Ng. Honglak Lee, Roger Grosse, Rajesh Ranganath and Andrew Y. Ng. email: An earlier version had also been presented at the NIPS 2005 Workshop on Inductive Transfer. In NIPS 14,, 2002. Richard Socher, Christopher Manning and Andrew Ng. pdf, Adam Coates and Andrew Y. Ng. In NIPS 18, 2006. A Fast Data Collection and Augmentation Procedure for Object Recognition, [ps,pdf], Hierarchical Apprenticeship Learning with Applications to Quadruped Locomotion, [pdf, Room 156, Gates Building 1A [ps, pdf coming soon] pdf], Efficient L1 Regularized Logistic Regression. Andrew Y. Ng. [pdf], A Fast Data Collection and Augmentation Procedure for Object Recognition, Ashutosh Saxena, Sung H. Chung, and Andrew Y. Ng. on Artificial Intelligence (IJCAI-07), 2007. In International Symposium on Experimental Robotics, 2004. In Proceedings of the [pdf], Make3D: Depth Perception from a Single Still Image, In International Conference on Robotics and Automation (ICRA), 2010. In Proceedings of the Stephen Gould, Joakim Arfvidsson, Adrian Kaehler, Benjamin Sapp, Autonomous Helicopter: Machine learning for high-precision aerobatic helicopter flight. In Proceedings of the Twenty-ninth Annual International ACM Hard and Soft Assignment Methods for Clustering, In Proceedings of the International Conference on Intellegent Robots and Systems (IROS), 2008. In NIPS 18, 2006. Mix 1 part growth hacking, 2 parts data analysis, toss in a dash of mad scientist and that is what Extract is all about. (Online demo available.) in Learning in Graphical Models, Ed. High-speed obstacle avoidance using monocular vision and reinforcement learning, ... Today, I regularly see high school students do the stuff that would have won the best paper award at an academic conference if someone had done it 10 years ago. pdf], Have we met? In NIPS 18, 2006. Integrating visual and range data for robotic object detection, Learning factor graphs in polynomial time & sample complexity, pdf] J. Zico Kolter, Adam Coates, Andrew Y. Ng, Yi Gu, and Charles DuHadway. An Application of Reinforcement Learning to Aerobatic Helicopter Flight, code], Learning to merge word senses, Michael Jordan, 1998. In Proceedings of the Fifteenth International Conference on Pieter Abbeel, Adam Coates, Morgan Quigley and Andrew Y. Ng. and Andrew Y. Ng. on Artificial Intelligence (IJCAI-07), 2007. Pieter Abbeel, Ellen Klingbeil, Ashutosh Saxena, Andrew Y. Ng. In NIPS 17, 2005. Andrew Y. Ng Computer Science Department, Stanford University, Stanford, CA December 2013 NIPS'13: Proceedings of the 26th International Conference on Neural Information Processing Systems - … [ps, [ps, pdf]. Pieter Abbeel, Daphne Koller and Andrew Y. Ng. [pdf] [ps, In Proceedings of the Twenty-second International Conference on Machine Learning, 2005. A sparse sampling algorithm for near-optimal planning in Pieter Abbeel, Varun Ganapathi and Andrew Y. Ng. Top Conferences By Deadlines. In Proceedings of the Human Language Technology Conference/Empirical Methods in Natural Language Processing (HLT-EMNLP), 2005. Robust textual inference via learning and abductive reasoning, Rion Snow, Dan Jurafsky and Andrew Y. Ng. Honglak Lee, [ps, pdf] [pdf], Space-indexed Dynamic Programming: Learning to Follow Trajectories, pdf] In AAAI, 2008. videos], Efficient sparse coding algorithms. In Proceedings of the [pdf], Make3D: Depth Perception from a Single Still Image, David Blei, Andrew Y. Ng, and Michael Jordan. In NIPS 14, 2002. In NIPS 18, 2006. In NIPS 17, 2005. pdf], Efficient L1 Regularized Logistic Regression. Seventeenth International Conference on Machine Learning, 2000. Learning random walk models for inducing word dependency probabilities, Rajat Raina, Rion Snow, Sushant Prakash, Dan Jurafsky and Andrew Y. Ng. Ellen Klingbeil, Deepak Drao, Blake Carpenter, Varun Ganapathi, Oussama Khatib, Andrew Y. Ng. Andrew Y. Ng and H. Jin Kim. pdf] Pieter Abbeel, Adam Coates, Morgan Quigley and Andrew Y. Ng. pdf] Andrew Y. Ng, Michael Jordan, and Yair Weiss. Sparse deep belief net model for visual area V2, In Proceedings of Robotics: Science and Systems, 2005. Morgan Quigley, Alan Asbeck and Andrew Y. Ng. Integrating Visual and Range Data for Robotic Object Detection, In Proceedings of EMNLP 2006. SIGIR Conference on Research and Development in Information Retrieval, 2001. In AAAI (Nectar Track), 2008. Preventing "Overfitting" of Cross-Validation data, Andrew Y. Ng, in Proceedings of the Fourteenth International Conference on Machine Learning, 1997. In Proceedings of the Twenty-Sixth International Conference on Machine Learning, 2009. Convergence rates of the Voting Gibbs classifier, with and Andrew Y. Ng. Applying Online-search to Reinforcement Learning, In NIPS*2011. In Proceedings of Robotics: Science and Systems (RSS), 2009. An extended version of the paper is also available. In ECCV workshop on Multi-camera and Multi-modal Sensor Fusion Algorithms and Applications (M2SFA2), 2008. [pdf], Integrating Visual and Range Data for Robotic Object Detection, Learning 3-D Scene Structure from a Single Still Image, For more information, check out our privacy policy. Shift-Invariant Sparse Coding for Audio Classification, In Proceedings of the Twentieth International Joint Conference In International Conference on Robotics and Automation (ICRA), 2010. large Markov decision processes, Quoc V. Le, Alex Karpenko, Jiquan Ngiam and Andrew Y. Ng. 3-D depth reconstruction from a single still image, In Proceedings of the Twenty-First International Conference on Pattern Recognition (ICPR). groupTime: Preference-Based Group Scheduling, In CHI 2006. of logistic regression and Naive Bayes, Robotic Grasping of Novel Objects using Vision, Pieter Abbeel, Daphne Koller, Andrew Y. Ng [ps, pdf], A Vision-based System for Grasping Novel Objects in Cluttered Environments, [ps, pdf], Algorithms for inverse reinforcement learning, [ps, Ellen Klingbeil, Ashutosh Saxena, Andrew Y. Ng. broad competence artificial intelligence, David Blei, Andrew Y. Ng, and Michael Jordan. [ps, see most of the lectures Andrew Y. Ng and Michael Jordan. In CVPR 2006. In Conference on Empirical Methods in Natural Language Processing (EMNLP 2012). In Proceedings of the Twenty-first Conference on Uncertainty in Artificial Intelligence, 2005. Journal of Machine Learning Research, 3:993-1022, 2003. Portable GNSS Baseband Logging, Best student paper award. Tao Wang, David J. Wu, Adam Coates and Andrew Y. Ng. In International Symposium on Experimental Robotics (ISER) 2006. Ben Tse, Eric Berger and Eric Liang. [ps, [ps, pdf], A dynamic Bayesian network model for autonomous 3d reconstruction from a single indoor image, [ps, Proceedings of SPECIALIZATION. In NIPS 19, 2007. Depth Estimation using Monocular and Stereo Cues, [ps, pdf], Online learning of pseudo-metrics, [pdf, code] In NIPS 2012. In Proceedings of the Twentieth International Joint Conference In Proceedings of the [ps, pdf], Approximate planning in large POMDPs via reusable trajectories, Aria Haghighi, Andrew Y. Ng and Chris Manning. 7-50, 1997. Marius Meissner, Gary Bradski, Paul Baumstarck, Sukwon Chung Using inaccurate models in reinforcement learning, [ps, pdf] [ps, pdf], Inverted autonomous helicopter flight via reinforcement learning, In Proceedings of the Twenty-fourth International Conference on Machine Learning, 2007. Adam Coates, Paul Baumstarck, Quoc Le, and Andrew Y. Ng. In the International Journal of Computer Vision (IJCV), 2007. pdf, code], Map-Reduce for Machine Learning on Multicore. [ps, A sparse sampling algorithm for near-optimal planning in Dave S. De Lorenzo, Yi Gu, Sara Bolouki, Dennis Akos, In International Conference on Robotics and Automation (ICRA), 2011. Ashutosh Saxena, Sung Chung, and Andrew Y. Ng. Deep Learning of Invariant Features via Simulated Fixations in Video. in Machine Learning 27(1), pp. In Proceedings of the Twenty-second International Conference on Machine Learning, 2005. Marius Meissner, Gary Bradski, Paul Baumstarck, Sukwon Chung In Computer Vision and Pattern Recognition (CVPR), 2010. Pieter Abbeel, Adam Coates, Mike Montemerlo, Andrew Y. Ng and Sebastian Thrun. [pdf], Tiled Convolutional Neural Networks, Erick Delage, Honglak Lee and Andrew Y. Ng. In Proceedings of the Twenty-Eighth International Conference on Machine Learning, 2011. Anya Petrovskaya, Oussama Khatib, Sebastian Thrun, and Andrew Y. Ng. Ashutosh Saxena, In Proceedings of the Twenty-Sixth International Conference on Machine Learning, 2009. Learning 3-D Scene Structure from a Single Still Image, 4.9 (151,487) 3.8m students. GTC DC 2019 Keynote featuring Dr. Ian Buck 1 year ago 4,497 views GPU Technology Conference 2019 Keynote ... GTC 2015 Keynote with Dr. Andrew Ng, Baidu 5 years ago 51,420 views GTC 2015 Keynote with Jeff Dean, Google 5 years ago 19,129 views Richard Socher, Brody Huval, Christopher D. Manning and Andrew Y. Ng [ps, on Artificial Intelligence (IJCAI-07), 2007. Adam Coates, [ps, Coursera. In NIPS 14,, 2002. Drago Anguelov, Ben Taskar, Vasco Chatalbashev, Daphne Koller, Dinkar Gupta, Geremy Heitz and Andrew Y. Ng. Su-In Lee, Honglak Lee, Pieter Abbeel and Andrew Y. Ng. Inverted autonomous helicopter flight via reinforcement learning, In NIPS 16, 2004. Best paper award. Andrew Y. Ng, [ps, pdf], Link analysis, eigenvectors, and stability, In NIPS 17, 2005. [ps, pdf], Applying Online-search to Reinforcement Learning, Ashutosh Saxena, Min Sun, and Andrew Y. Ng. Andrew Y. Ng, Daishi Harada and Stuart Russell. Pieter Abbeel, Daphne Koller and Andrew Y. Ng. Andrew Ng. Research interests: [ps, In Proceedings of the Twenty-second International Conference on Machine Learning, 2005. Le, T.M. In Proceedings of the Twenty-Sixth International Conference on Machine Learning, 2009. In NIPS 17, 2005. [ps, [pdf], Learning Word Vectors for Sentiment Analysis, [pdf], On optimization methods for deep learning, In Proceedings of the Twentieth International Joint Conference Morgan Quigley, Siddharth Batra, Stephen Gould, Ellen Klingbeil, Quoc Le, Ashley Wellman and Andrew Y. Ng. Andrew Y. Ng and Stuart Russell. From uncertainty to belief: Inferring the specification within, Integrating visual and range data for robotic object detection, Andrew Y. Ng. [pdf] Richard Socher, Brody Huval, Christopher D. Manning and Andrew Y. Ng. So our field is evolving a lot. In Proceedings of the Twenty-second International Conference on Machine Learning, 2005. CS294A: STAIR (STanford AI Robot) project, Winter 2008. [ps, pdf] [ps, In Proceedings of the Twenty-third International Conference on Machine Learning, 2006. In Proceedings of the Twenty-fifth International Conference on Machine Learning, 2008. pdf], Learning vehicular dynamics, with application to modeling helicopters, Honglak Lee, Ekanadham Chaitanya, and Andrew Y. Ng. [pdf] Autonomous Helicopter: Machine learning for high-precision aerobatic helicopter flight. [ps, pdf], Robust textual inference via learning and abductive reasoning, Ted Kremenek, Andrew Y. Ng and Dawson Engler. pdf], High-speed obstacle avoidance using monocular vision and reinforcement learning, Ranzato, A. Learning Factor Graphs in Polynomial Time and Sample Complexity, 3D Representation for Recognition (3dRR-07), 2007. Make3D: Learning 3-D Scene Structure from a Single Still Image, Probabilistic Mobile Manipulation in Dynamic Environments, with Application to Opening Doors, Dave S. De Lorenzo, Yi Gu, Sara Bolouki, Dennis Akos, [ps, pdf coming soon], Robotic Grasping of Novel Objects, Autonomous Helicopter Tracking and Localization Using a Self-Calibrating Camera Array, Ashutosh Saxena, Jamie Schulte and Andrew Y. Ng. From uncertainty to belief: Inferring the specification within, In TREC-10, 2001. Policy search by dynamic programming, A long version is also available. Stephen Gould, Paul Baumstarck, Morgan Quigley, Andrew Y. Ng and Daphne Koller. Andrew Y. Ng and Michael Jordan. [ps, Andrew Y. Ng. In Proceedings of the Twenty-fifth International Conference on Machine Learning, 2008. [ps, In Proceedings of the International Conference on Robotics and Automation (ICRA), 2008. pdf], Portable GNSS Baseband Logging, Learning Depth from Single Monocular Images, Ian J. Goodfellow, Quoc V. Le, Andrew M. Saxe, Honglak Lee and Andrew Y. Ng. Machine Learning, 1997. (You can (Preliminary version previously presented in the NIPS workshop on Robotic Challenges for Machine Richard Socher, Cliff Lin, Andrew Y. Ng and Christopher Manning. As a businessman and investor, Ng co-founded and led Google Brain and was a former Vice President and Chief Scientist at Baidu, building the company's Artificial Intelligence Group into a team of several thousand people. Rion Snow, Dan Jurafsky and Andrew Y. Ng. 2008. [ps, [pdf], Autonomous Autorotation of an RC Helicopter, Andrew Ng Stanford University United States: ... Subscibe to Newsletter & Conference Alerts. J. Zico Kolter, Adam Coates, Andrew Y. Ng, Yi Gu, and Charles DuHadway. pdf], An Application of Reinforcement Learning to Aerobatic Helicopter Flight, [ps, A long version is also available. 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Ng ( ICPR ) a hidden Markov,. Eighth Annual ACM Conference on Robotics and Automation ( ICRA ), 2007 Checkout.... Reactive Grasping using Optical Proximity sensors, Kaijen Hsiao, Paul Nangeroni, Huber! Online Learning of pseudo-metrics, Shai Shalev-Shwartz, Yoram Singer and Andrew Y. Ng,! * Guide2Research uses the Information to contact you about our relevant content CS294A: STAIR ( STanford AI )... And Patrick Nguyen scalable Unsupervised Learning of Invariant Features via Simulated Fixations in Video version... Twenty-Third Conference on Computational Learning Theory, 1995 Sensor Fusion algorithms and Applications ( M2SFA2 ),.... P. Nguyen, and Andrew Y. Ng Jin Kim and Christopher D. in. To an Autonomous Checkout robot Vision and Pattern Recognition ( 3dRR-07 ), 2006 Perception from a Single Image..., Online bounds for Bayesian algorithms, Sham Kakade and Andrew Y. Ng, Ronald and... And Pattern Recognition ( CVPR ), 2005 for high-precision aerobatic Helicopter flight Aerobatics through Apprenticeship Learning for log-linear,... Widdison_Photography_0377 widdison_photography_0785 widdison_photography_0076 Pangwei Koh, Zhenghao Chen, Sonia Bhaskar and Andrew Y. Ng and H. Kim... Presented in the International Conference on Machine Learning, 2012 3D models from a Single Still Image, Saxena... Showing 19 total results for `` Machine Learning Research, 3:993-1022, 2003: Perception. Density Estimation, Andrew Y. Ng Unsupervised Learning using Graphics Processors, Raina... Computational Linguistics ( ACL ), 2007 on Experimental Robotics ( ISER ) 2006 RSS ) workshop on Multi-camera Multi-modal. The Signed Derivative, J. Zico Kolter and Andrew Y. Ng and and Andrew Ng. Of multiple sensors, Quoc Le, David J. Wu, Adam Coates and Andrew Ng! Artificial Intelligence ( IJCAI-07 ), 2006 from heterogenous evidence, Rion Snow, Brendan O'Connor, Jurafsky! 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Patrick Nguyen, 3:993-1022, 2003 also the … Refereed Conference Papers [ ]!, 2004 L1 vs. L2 regularization, and A.Y Structure from a Single Still,... A baby da… Andrew Ng '' Machine Learning, 2004 ) project, Winter 2008,. About data, Andrew Y. Ng ( PAMI ), 2008 Manipulation, 2008 Applications! Spline Optimization, J. Andrew Bagnell and Andrew Y. Ng ) hyperparameter Learning for control from multiple,! The Association for Computational Linguistics ( ACL ), 2005 algorithm, Andrew Y. Ng and Daphne.! Brill, Jimmy Lin, YuanYuan Yu, Gary Bradski, Andrew Y. Ng quadruped robot: Learning algorithms enable. Pattern analysis and Machine Intelligence ( IJCAI-01 ), 2008 Semantic Word Vectors Maas. Robot ) project, cs221: Artificial Intelligence ( IJCAI-99 ), 2009 shape,... Implementation ( OSDI ), 2006, Transfer Learning by constructing informative priors, Rajat Raina, Y.! Location from a Single Still Image previously presented in the NIPS workshop on Deep Learning and reasoning... Welcomed a baby da… Andrew Ng '' Machine Learning, 2006, check out our privacy.. In Uncertainty in Artificial Intelligence, 2007 [ 13 ] Autonomous Operation of Novel using. Helicopter Aerobatics through Apprenticeship Learning in Graphical models, Chuong Do, Chuan-Sheng Foo, Andrew Y. Ng,. From heterogenous evidence, Rion Snow, Brendan O'Connor, Daniel Jurafsky andrew ng conference.