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Probabilistic Mobile Manipulation in Dynamic Environments, with Application to Opening Doors, [pdf] [ps, pdf], Stable adaptive control with online learning, [ps, Stephen Gould, Joakim Arfvidsson, Adrian Kaehler, Benjamin Sapp, Ashutosh Saxena, Sung H. Chung, and Andrew Y. Ng. [ps, Michael Kearns, Yishay Mansour, Andrew Y. Ng and Dana Ron, [pdf], Low-cost Accelerometers for Robotic Manipulator Perception In Institute of Navigation (ION) GNSS Conference, 2007. [pdf], Learning to Open New Doors, CS229: Machine Learning, Autumn 2008. Make3D: Learning 3-D Scene Structure from a Single Still Image, Improving Text Classification by Shrinkage in a Hierarchy of Classes, In NIPS 12, 2000. [ps, pdf]. In Proceedings of the Twenty-second International Conference on Machine Learning, 2005. Richard Socher, Christopher Manning and Andrew Ng. [ps, Stephen Gould, Paul Baumstarck, Morgan Quigley, Andrew Y. Ng and Daphne Koller. In NIPS 12, 2000. Andrew Y. Ng. 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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. in Proceedings of the Fifteenth International Conference on Pieter Abbeel and Andrew Y. Ng. Rajat Raina, Yirong Shen, Andrew Y. Ng and Andrew McCallum, In Proceedings of the International Symposium on Robotics Research (ISRR), 2005. In International Journal of Robotics Research (IJRR), 2008. In Proceedings of In ICCV workshop on Department of Electrical Engineering (by courtesy) Kaijen Hsiao, Paul Nangeroni, Manfred Huber, Ashutosh Saxena and Andrew Y. Ng. (You can [ps, pdf]. Andrew Y. Ng and Stuart Russell. Seventeenth International Conference on Machine Learning, 2000. Pieter Abbeel, (IJCAI-99), 1999. In ECCV workshop on Multi-camera and Multi-modal Sensor Fusion Algorithms and Applications (M2SFA2), In Proceedings of the [ps, on Artificial Intelligence (IJCAI-07), 2007. In ECCV workshop on Multi-camera and Multi-modal Sensor Fusion Algorithms and Applications (M2SFA2), 2008. J. Andrew Bagnell and Andrew Y. Ng. In Proceedings of the Twentieth International Joint Conference ICCV workshop on Virtual Representations and Modeling of Large-scale environments (VRML), [ps, pdf] pdf], High-speed obstacle avoidance using monocular vision and reinforcement learning, pdf] Andrew Ng: Deep learning has created a sea change in robotics. In Proceedings of the International Conference on Intellegent Robots and Systems (IROS), 2008. Chuong Do and Andrew Y. Ng. A Vision-based System for Grasping Novel Objects in Cluttered Environments, In CVPR 2006. of logistic regression and Naive Bayes, CS294A: STAIR (STanford AI Robot) project, CS221: Artificial Intelligence: Principles and Techniques. pdf], Hierarchical Apprenticeship Learning with Applications to Quadruped Locomotion, Morgan Quigley, Pieter Abbeel, [ps, pdf], Learning first order Markov models for control, [ps, pdf], On Spectral Clustering: Analysis and an algorithm, An Experimental Marius Meissner, Gary Bradski, Paul Baumstarck, Sukwon Chung Gary Bradski, Andrew Y. Ng and Kunle Olukotun. In International Journal of Robotics Research (IJRR), 2010. In Proceedings of the Twentieth International Joint Conference In International Symposium on Experimental Robotics, 2004. [ps, In NIPS 12, 2000. Convergence rates of the Voting Gibbs classifier, with In Proceedings of [ps, pdf] It’s everything you’ve ever wanted to know about data, told by the people who know it best. [ps, pdf], Latent Dirichlet Allocation, pdf] [pdf], Learning grasp strategies with partial shape information, Stephen Gould, Paul Baumstarck, Morgan Quigley, Andrew Y. Ng and Daphne Koller. Rated 4.9 out of five stars. Best paper award. Su-In Lee, Honglak Lee, Pieter Abbeel and Andrew Y. Ng. [pdf] In NIPS 16, 2004. [pdf] In Proceedings of the International Conference on Robotics and Automation (ICRA), 2008. In NIPS 12, 2000. In Conference on Empirical Methods in Natural Language Processing (EMNLP), 2012. [ps, [ps, as Training Examples, [ps, pdf], Latent Dirichlet Allocation, In Neural Networks: Tricks of the Trade, Reloaded, Springer LNCS, 2012. In Proceedings of the Ninth International Conference on Spoken Language Processing (InterSpeech--ICSLP), 2006. Roger Grosse, Rajat Raina, Helen Kwong and Andrew Y. Ng. Gary Bradski, Andrew Y. Ng and Kunle Olukotun. J. Zico Kolter and Andrew Y. Ng. Ellen Klingbeil, Ashutosh Saxena, Andrew Y. Ng. Shai Shalev-Shwartz, Yoram Singer and Andrew Y. Ng. In AAAI, 2008. In Proceedings of the Seventeenth International Joint Conference [ps, In CHI 2006. [ps, In Proceedings of the International Conference on Robotics and Automation (ICRA), 2006. in Machine Learning 27(1), pp. He is an associate professor at the University of Stanford. [ps, pdf], Policy search via density estimation, Chuong Do (Tom), Together the couple has welcomed a baby da… Latent Dirichlet Allocation, [ps, pdf], Algorithms for inverse reinforcement learning, The keynote was delivered by computer scientist Andrew Ng who was the former Director of the Stanford University AI Lab and the co-founder of the Google Brain project. Make3d: Building 3d models from a single still image. On Feature Selection: Learning with Exponentially many Irrelevant Features 4.9 (151,487) 3.8m students. In NIPS 14,, 2002. In NIPS 14, 2002. In Proceedings of the Seventeenth International Joint Conference In International Journal of Robotics Research (IJRR), 2008. Ashutosh Saxena, Sung Chung, and Andrew Y. Ng. In Journal of Machine Learning Research, 7:1743-1788, 2006. In Proceedings of the International Conference on Robotics and Automation (ICRA), 2006. [ps, pdf] In Proceedings of the International Conference on Intelligent Robots and Systems (IROS), 2010. In Proceedings of the 44th Annual Meeting of the Association for Computational Linguistics (ACL), 2006. large Markov decision processes, Ashutosh Saxena, Min Sun, and Andrew Y. Ng. see most of the lectures Pieter Abbeel, Dmitri Dolgov, Andrew Y. Ng and Sebastian Thrun. Ashutosh Saxena, Lawson Wong, and Andrew Y. Ng. broad competence artificial intelligence, In the same year, the pair wedded in an intimate ceremony. [ps, pdf], Online learning of pseudo-metrics, Honglak Lee and and Andrew Y. Ng. In Proceedings of the Twenty-first Conference on Uncertainty in Artificial Intelligence, 2005. In Proceedings of the Open-Source Software workshop at the International Conference on Robotics and Automation (ICRA), 2009. In Proceedings of the Twentieth International Joint Conference Rion Snow, Dan Jurafsky and Andrew Y. Ng. Pieter Abbeel, Morgan Quigley and Andrew Y. Ng. Honglak Lee, Yirong Shen, Chih-Han Yu, Gurjeet Singh, and Andrew Y. Ng. [ps, Ted Kremenek, Paul Twohey, Godmar Back, Andrew Y. Ng and Dawson Engler. [ps, pdf] Honglak Lee, Alexis Battle, Raina Rajat and Andrew Y. Ng. Distance metric learning, with application to clustering with side-information, Eric Xing, Andrew Y. Ng, Michael Jordan, and Stuart Russell. [ps, on Artificial Intelligence (IJCAI-01), 2001. broad competence artificial intelligence, [ps, pdf] the Sixteenth International Joint Conference on Artificial Intelligence pdf] Other reinforcement learning videos: High-speed obstacle avoidance, snake robot, etc. 151487 reviews. AI is coming. Honglak Lee, STAIR (STanford AI Robot) project: Integrating tools from all the diverse areas Honglak Lee, Ekanadham Chaitanya, and Andrew Y. Ng. [ps, and Theoretical Comparison of Model Selection Methods, pdf] In Proceedings of EMNLP 2007. J. Zico Kolter, Pieter Abbeel, and Andrew Y. Ng. [pdf], A Probabilistic Approach to Mixed Open-loop and Closed-loop Control, with Application to Extreme Autonomous Driving, J. Zico Kolter, Mike Rodgers and Andrew Y. Ng. [ps, Pieter Abbeel, Daphne Koller and Andrew Y. Ng. In Robotics Science and Systems (RSS) For more information, check out our privacy policy. pdf], Learning Factor Graphs in Polynomial Time and Sample Complexity, [ps, [ps, pdf] [ps, Rajat Raina, Andrew Y. Ng and Daphne Koller. In Proceedings of the International Conference on Robotics and Automation (ICRA), 2006. In AAAI, 2008. In NIPS 15, 2003. Ashutosh Saxena, Min Sun, and Andrew Y. Ng. Andrew Ng. Contextual search and name disambiguation in email using graphs, Best paper award: Best application paper. pdf], groupTime: Preference-Based Group Scheduling, Transfer learning by constructing informative priors, [ps, pdf] [pdf], Near-Bayesian Exploration in Polynomial Time, In Proceedings of the Honglak Lee, Ekanadham Chaitanya, and Andrew Y. Ng. In Proceedings of the Twenty-fifth International Conference on Machine Learning, 2008. Pieter Abbeel, Adam Coates, Timothy Hunter and Andrew Y. Ng. In Proceedings of Robotics: Science and Systems, 2005. Ashutosh Saxena, Min Sun, Andrew Y. Ng. Tel: (650)725-2593 FAX: (650)725-1449 email: ang@cs.stanford.edu (if contacting me about CS229 or CS229A, please see below) pdf], Solving the problem of cascading errors: Approximate In Proceedings of the pdf] In ICCV workshop on of AI, to build a useful, general purpose home assistant robot. Andrew Yan-Tak Ng (Chinese: 吳恩達; born 1976) is a British-born American businessman, computer scientist, investor, and writer.He is focusing on machine learning and AI. pdf] Ashutosh Saxena, Lawson Wong, Morgan Quigley and Andrew Y. Ng. Approximate planning in large POMDPs via reusable trajectories, In AAAI, 2008. 3D Representation for Recognition (3dRR-07), 2007. Workshop on Reinforcement Learning at ICML97, 1997. Michael Jordan, 1998. [ps, pdf], Stable algorithms for link analysis, Best student paper award. Stephen Gould, Joakim Arfvidsson, Adrian Kaehler, Benjamin Sapp, In Proceedings of Robotics: Science and Systems, 2007. 3-D Reconstruction from Sparse Views using Monocular Vision , videos] [pdf], High-Accuracy 3D Sensing for Mobile Manipulation: Improving Object Detection and Door Opening, Adam Coates, [ps, pdf], Approximate inference algorithms for two-layer Bayesian networks, [ps, pdf], Convergence rates of the Voting Gibbs classifier, with [ps, pdf], Approximate planning in large POMDPs via reusable trajectories, The importance of encoding versus training with sparse coding and vector quantization, pdf] Also a book chapter [ps, pdf], Latent Dirichlet Allocation, [ps, pdf] [ps, pdf]. pdf], Shift-Invariant Sparse Coding for Audio Classification, In International Conference on Robotics and Automation (ICRA), 2009. Pieter Abbeel, Adam Coates, Morgan Quigley and Andrew Y. Ng. Best student paper award. Michael Kearns, Yishay Mansour and Andrew Y. Ng. In NIPS 12, 2000. [ps, pdf] Learning vehicular dynamics, with application to modeling helicopters, In Proceedings of the on Artificial Intelligence (IJCAI-07), 2007. Quote Investigator: In March 2015 a conference focused on GPU (graphics processing unit) technology was held in San Jose, California. [ps, pdf], Feature selection, L1 vs. L2 regularization, and rotational invariance, [ps, pdf], Discriminative Learning of Markov Random Fields for Segmentation of 3D Range Data, In Proceedings of the International Symposium on Robotics Research (ISRR), 2007. [ps, pdf coming soon] [ps, In International Symposium on Experimental Robotics (ISER) 2006. (You can [ps, [pdf], Learning to grasp novel objects using vision, Andrew Y. Ng and H. Jin Kim. Andrew Saxe, Maneesh Bhand, Ritvik Mudur, Bipin Suresh and Andrew Y. Ng. [pdf] In International Conference on Robotics and Automation (ICRA), 2011. In Proceedings of the Fifth International Conference on Field Service Robotics, 2005. Will Y. Zou, Shenghuo Zhu, Andrew Y. Ng, Kai Yu. In Corrado, R. Monga, K. Chen, M. Devin, Q.V. Honglak Lee, Roger Grosse, Rajesh Ranganath and Andrew Y. Ng. Integrating visual and range data for robotic object detection, pdf] [ps, pdf], Portable GNSS Baseband Logging, Evaluating Non-Expert Annotations for Natural Language Tasks, Preventing "Overfitting" of Cross-Validation data, [ps, pdf], Learning random walk models for inducing word dependency probabilities, [pdf], On random weights and unsupervised feature learning, Learning for Control from Muliple Demonstrations, In Proceedings of the Twenty-Sixth International Conference on Machine Learning, 2009. Rajat Raina, Andrew Y. Ng and Chris Manning. 2007. Find out more. Seventeenth International Conference on Machine Learning, 2000. [ps, Pieter Abbeel, Morgan Quigley and Andrew Y. Ng. In Proceedings of the Sixteenth International Conference on Machine Learning, 1999. An extended version of the paper is also available. Robust Textual Inference via Graph Matching, Quoc Le, [14] Learning to grasp objects with multiple contact points. reinforcement learning and robotic control, Refereed Conference Papers [13] Autonomous Operation of Novel Elevators for Robot Navigation. Artificial Intelligence, Proceedings of the Sixteenth Conference, 2000. [pdf], A Complete Control Architecture for Quadruped Locomotion Over Rough Terrain, Andrew L. Maas, Stephen D. Miller, Tyler M. O'Neil, Andrew Y. Ng, and Patrick Nguyen. Rajat Raina, Andrew Y. Ng and Chris Manning. [ps, pdf] Michael Kearns, Yishay Mansour and Andrew Y. Ng, — Andrew Ng, Founder of deeplearning.ai and Coursera Deep Learning Specialization, Course 5 [ps, In Proceedings of the Eighteenth International [ps, pdf], Policy search by dynamic programming, An extended version of the paper is also available. In NIPS*2007. Mix 1 part growth hacking, 2 parts data analysis, toss in a dash of mad scientist and that is what Extract is all about. Best student paper award. Chuong Do, Chuan-Sheng Foo, Andrew Y. Ng. Andrew Y. Ng and Stuart Russell. pdf], Fast Gaussian Process Regression using KD-trees, Jenny Finkel, Chris Manning and Andrew Y. Ng. Integrating visual and range data for robotic object detection, Scott Davies, Andrew Y. Ng and Andrew Moore. Andrew Ng Stanford University United States: ... Subscibe to Newsletter & Conference Alerts. In International Symposium on Experimental Robotics, 2004. Ashutosh Saxena, Sung H. Chung, and Andrew Y. Ng. In NIPS 18, 2006. Andrew Maas and Andrew Ng. Benjaminn Sapp, Ashutosh Saxena, and Andrew Y. Ng. Pieter Abbeel, Varun Ganapathi and Andrew Y. Ng. GPU Technology Conference OFF AIR. pdf], Fast Gaussian Process Regression using KD-trees, pdf], Efficient L1 Regularized Logistic Regression. Adam Coates and Andrew Y. Ng. [ps, [ps, pdf] [ps, pdf], Robust textual inference via learning and abductive reasoning, In NIPS*2007. In CHI 2006. Rion Snow, Dan Jurafsky and Andrew Y. Ng. Yirong Shen, Andrew Y. Ng and Matthias Seeger. Ashutosh Saxena, Min Sun, and Andrew Y. Ng. Have we met? [ps, pdf] Journal of Machine Learning Research, 3:993-1022, 2003. Project homepages: In Proceedings of the International Conference on Intellegent Robots and Systems (IROS), 2008. CS294A: STAIR (STanford AI Robot) project, Winter 2008. pdf] A dynamic Bayesian network model for autonomous 3d reconstruction from a single indoor image, [pdf], Regularization and Feature Selection in Least-Squares Temporal Difference Learning, code], Solving the problem of cascading errors: Approximate pdf], Depth Estimation using Monocular and Stereo Cues, Morgan Quigley, Reuben Brewer, Sai P. Soundararaj, Vijay Pradeep, Quoc V. Le and Olga Russakovsky, In IEEE Transactions on Pattern Analysis and Machine Intelligence (PAMI), 2008. [pdf, supplementary material], Learning hierarchical spatio-temporal features for action recognition with independent subspace analysis, In Proceedings of the International Conference on Robotics and Automation (ICRA), 2006. in Learning in Graphical Models, Ed. In Proceedings of the Twentieth International Joint Conference In NIPS 12, 2000. [ps, [ps, pdf] Stephen Gould, Paul Baumstarck, Morgan Quigley, Andrew Y. Ng and Daphne Koller. Hierarchical Apprenticeship Learning with Applications to Quadruped Locomotion, in Machine Learning 27(1), pp. In Proceedings of the International Symposium on Robotics Research (ISRR), 2005. In NIPS*2011. [ps, pdf], Inverted autonomous helicopter flight via reinforcement learning, Adam Coates, Blake Carpenter, Carl Case, Sanjeev Satheesh, Bipin Suresh, Tao Wang, David Wu and Andrew Y. Ng [ps, pdf], Discriminative training of Kalman filters, [ps, pdf]. [ps, pdf], PEGASUS: A policy search method for large MDPs and POMDPs, David Blei, Andrew Y. Ng, and Michael Jordan. SIGIR Conference on Research and Development in Information Retrieval, 2001. pdf] Scott Davies, Andrew Y. Ng and Andrew Moore. In Proceedings of the Human Language Technology Conference/Empirical Methods in Natural Language Processing (HLT-EMNLP), 2005. Ashutosh Saxena, pdf] More Photos. Space-indexed Dynamic Programming: Learning to Follow Trajectories, [pdf], On optimization methods for deep learning, pdf] Rion Snow, Dan Jurafsky and Andrew Y. Ng. Twenty-first International Conference on Machine Learning, 2004. [ps,pdf], 3-D depth reconstruction from a single still image, In Proceedings of the Twenty-fourth Annual International ACM One full day jam-packed with data stories that will entertain, educate and inspire you. and Andrew Y. Ng. In Proceedings of the Twentieth International Joint Conference In International Conference on Robotics and Automation (ICRA), 2011. Andrew L. Maas, Raymond E. Daly, Peter T. Pham, Dan Huang, Andrew Y. Ng, and Christopher Potts. Pieter Abbeel, Dmitri Dolgov, Andrew Y. Ng and Sebastian Thrun. [ps, pdf], Bayesian estimation for autonomous object manipulation based on tactile sensors, Learning 3-D Scene Structure from a Single Still Image, Andrew Y. Ng, Alice X. Zheng and Michael Jordan. In NIPS 14,, 2002. [ps, pdf], Probabilistic Mobile Manipulation in Dynamic Environments, with Application to Opening Doors, Ellen Klingbeil, Deepak Drao, Blake Carpenter, Varun Ganapathi, Oussama Khatib, Andrew Y. Ng. on Artificial Intelligence (IJCAI-07), 2007. In NIPS 19, 2007. In Proceedings of the In Journal of Machine Learning Research, 7:1743-1788, 2006. Conference on Machine Learning, 2001. 7-50, 1997. In Conference on Empirical Methods in Natural Language Processing (EMNLP 2011). (Preliminary version previously presented in the NIPS workshop on Robotic Challenges for Machine [pdf] Ben Tse, Eric Berger and Eric Liang. [ps, pdf] A sparse sampling algorithm for near-optimal planning in Approximate inference algorithms for two-layer Bayesian networks, In Proceedings of the Fifteenth International Conference on videos], Grasping Novel Objects with Depth Segmentation, pdf], On Local Rewards and the Scalability of Distributed Reinforcement Learning, pdf] [ps, pdf], Learning syntactic patterns for automatic hypernym discovery, Twenty-first International Conference on Machine Learning, 2004. Honglak Lee, Rajat Raina, Alex Teichman and Andrew Y. Ng. Rajat Raina, Yirong Shen, Andrew Y. Ng and Andrew McCallum, ISBN 978-981-15-83773-3, Springer Singapore, 2021. [ps, pdf] A.L. Assistant Professor [pdf], Space-indexed Dynamic Programming: Learning to Follow Trajectories, and Andrew Y. Ng. Computer Science Department [ps, Top Conferences By Deadlines. pdf] Ashutosh Saxena, Justin Driemeyer, and Andrew Y. Ng. [pdf], Learning Continuous Phrase Representations and Syntactic Parsing with Recursive Neural Networks [ps, pdf] ±åº¦å­¦ä¹ ã€‹ç³»åˆ—课程笔记及代码 | Notes in Chinese for Andrew Ng Deep Learning Course. [ps, pdf] Andrew Y. Ng, Alice X. Zheng and Michael Jordan. In NIPS*2007. [ps, In Proceedings of the Twenty-First National Conference on Artificial Intelligence (AAAI-06), 2006. [ps, pdf], On Discriminative vs. Generative Classifiers: A comparison Andrew McCallum, Roni Rosenfeld, Tom Mitchell and Andrew Y. Ng Coursera. [pdf], A Steiner tree approach to object detection, [pdf], A majorization-minimization algorithm for (multiple) hyperparameter learning, In NIPS 18, 2006. Andrew Y. Ng, Alice X. Zheng and Michael Jordan. [pdf]. [pdf]. [ps, Amazon’s re:MARS conference will feature Andrew Ng, iRobot CEO Colin Angle, and Robert Downey Jr. Kyle Wiggers @Kyle_L_Wiggers March … pdf], Efficient multiple hyperparameter learning for log-linear models, Twenty-first International Conference on Machine Learning, 2004. Feature selection, L1 vs. L2 regularization, and rotational invariance, [ps, pdf], Policy search via density estimation, Convolutional deep belief networks for scalable unsupervised learning of hierarchical representations, Using inaccurate models in reinforcement learning, [ps, In Proceedings of the Twenty-first Conference on Uncertainty in Artificial Intelligence, 2005. Proceedings of Distinguished application paper award. [pdf] In Proceedings of the Twenty-fourth International Conference on Machine Learning, 2007. pdf] [ps, pdf], Applying Online-search to Reinforcement Learning, Ashutosh Saxena, Justin Driemeyer, Justin Kearns and Andrew Y. Ng. [pdf], Autonomous Sign Reading for Semantic Mapping. pdf], A Vision-based System for Grasping Novel Objects in Cluttered Environments, Benjaminn Sapp, Ashutosh Saxena, and Andrew Y. Ng. Proceedings of Ashutosh Saxena, Justin Driemeyer, Justin Kearns and Andrew Y. Ng. 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 - … Andrew Y. Ng. supplementary material], Apprenticeship Learning for Motion Planning with Application to Parking Lot Navigation, Ranzato, A. Machine Learning, 1998. Evaluating Non-Expert Annotations for Natural Language Tasks, [pdf], Autonomous Autorotation of an RC Helicopter, In Proceedings of the Fifteenth National Conference on Artificial Intelligence (AAAI-98), 1998. [ps, pdf] [pdf] In Proceedings of the Twenty-Sixth International Conference on Machine Learning, 2009. Filip Krsmanovic, Curtis Spencer, Daniel Jurafsky and Andrew Y. Ng. In Proceedings of the Twenty-Eighth International Conference on Machine Learning, 2011. J. Zico Kolter, Youngjun Kim and Andrew Y. Ng. In Proceedings of the International Conference on Intelligent Robots and Systems (IROS), 2009. J. Zico Kolter, Pieter Abbeel, and Andrew Y. Ng. 2007. [ps, [ps, An extended version of the paper is also available. in Proceedings of the Fourteenth International Conference on In Proceedings of the 44th Annual Meeting of the Association for Computational Linguistics (ACL), 2006. pdf], Portable GNSS Baseband Logging, The 43 years old, Andrew Ng is a happily married man. Pieter Abbeel, [pdf] The entrepreneur couple met for the first time in 2009 in Kobe, Japan, at the IEEE International Conference on Robotics and Automation. Ashutosh Saxena, Justin Driemeyer, Justin Kearns, Chioma Osondu, Hire your chief AI officer. Make3d: Building 3d models from a single still image. [ps, pdf] Sham Kakade and Andrew Y. Ng. In Proceedings of the Twentieth International Joint Conference In Proceedings of the Twenty-Eighth International Conference on Machine Learning, 2011. 7-50, 1997. [ps, pdf], Learning first order Markov models for control, Robust textual inference via learning and abductive reasoning, Learning first order Markov models for control, [ps, pdf], Learning Depth from Single Monocular Images, Andrew Y. Ng. STAIR (STanford AI Robot) project: Integrating tools from all the diverse areas CS294A: STAIR (STanford AI Robot) project, Winter 2008. In Proceedings of the Ninth International Conference on Spoken Language Processing (InterSpeech--ICSLP), 2006. Machine Learning, 1998. Andrew Y. Ng. Anya Petrovskaya and Andrew Y. Ng. [pdf], Unsupervised learning models of primary cortical receptive fields and receptive field plasticity, pdf], groupTime: Preference-Based Group Scheduling, Journal of Machine Learning Research, 3:993-1022, 2003. Jeff Michels, Ashutosh Saxena and Andrew Y. Ng. pdf] Efficient sparse coding algorithms. J. Zico Kolter, Mike Rodgers and Andrew Y. Ng. In Proceedings of the Twenty-second International Conference on Machine Learning, 2005. Adam Coates and Andrew Y. Ng. Aria Haghighi, Andrew Y. Ng and Chris Manning. Ashutosh Saxena, Min Sun, and Andrew Y. Ng. Ben Tse, Eric Berger and Eric Liang. [pdf]. [ps, pdf], Learning random walk models for inducing word dependency probabilities, Bayesian estimation for autonomous object manipulation based on tactile sensors, [ps, pdf], Algorithms for inverse reinforcement learning, and Andrew Y. Ng. In Proceedings of the Twenty-third International Conference on Machine Learning, 2006. In Proceedings of the International Symposium on Robotics Research (ISRR), 2005. Integrating visual and range data for robotic object detection, Semantic taxonomy induction from heterogenous evidence, Improving Word Representations via Global Context and Multiple Word Prototypes. [ps, In Proceedings of EMNLP 2007. deep belief networks, [pdf] pdf], Have we met? Chuong Do and Andrew Y. Ng. pdf], Robust Textual Inference via Graph Matching, Also a book chapter Erick Delage, Honglak Lee and Andrew Y. Ng. pdf] [pdf] Best paper award. In Institute of Navigation (ION) GNSS Conference, 2007. Morgan Quigley, Alan Asbeck and Andrew Y. Ng. In Proceedings of the International Conference on Robotics and Automation (ICRA), 2008. Pieter Abbeel and Andrew Y. Ng. Using inaccurate models in reinforcement learning, as Training Examples, [ps, pdf]. In NIPS 17, 2005. [ps, pdf] Dave S. De Lorenzo, Yi Gu, Sara Bolouki, Dennis Akos, In NIPS*2010 Workshop on Deep Learning and Unsupervised Feature Learning. In Proceedings of the Ninth International Conference on Spoken Language Processing (InterSpeech--ICSLP), 2006. Ted Kremenek, Andrew Y. Ng and Dawson Engler. Twenty-first International Conference on Machine Learning, 2004. In a recent Forbes interview, Andrew Ng was asked where he sees his career going forward following his departure from Baidu, a world leader in artificial intelligence (ai). Cheng-Tao Chu, Sang Kyun Kim, Yi-An Lin, YuanYuan Yu, [ps, Learning Feature Representations with K-means. Andrew Y. Ng Computer Science Department Stanford University Room 156, Gates Building Stanford, CA 94305-9010 . [pdf], Make3D: Learning 3-D Scene Structure from a Single Still Image, [ps, Ashutosh Saxena, Min Sun, and Andrew Y. Ng. YouTube.) pdf], Have we met? Semantic Compositionality through Recursive Matrix-Vector Spaces. In NIPS 12, 2000. [pdf, Andrew Y. Ng, Alice X. Zheng and Michael Jordan. Twenty-first International Conference on Machine Learning, 2004. [ps, Andrew Y. Ng, Ronald Parr and Daphne Koller. [pdf]. groupTime: Preference-Based Group Scheduling, Adam Coates, Pieter Abbeel and Andrew Y. Ng. An earlier version had also been presented at the Stanford University. on [ps, pdf] 3D Representation for Recognition (3dRR-07), 2007. [ps, In NIPS 18, 2006. Transfer learning for text classification, [ps, pdf] Policy search by dynamic programming, In NIPS*2011. Learning syntactic patterns for automatic hypernym discovery, pdf, Applying Online-search to Reinforcement Learning, (IJCAI-99), 1999. Ashutosh Saxena, Justin Driemeyer, Justin Kearns and Andrew Y. Ng. [ps, Autonomous Helicopter: Machine learning for high-precision aerobatic helicopter flight. Cheap and Fast - But is it Good? Su-In Lee, Honglak Lee, Pieter Abbeel and Andrew Y. Ng. Marius Meissner, Gary Bradski, Paul Baumstarck, Sukwon Chung Ashutosh Saxena, Min Sun, and Andrew Y. Ng. A preliminary version had also appeared in the NIPS*2010 Workshop on Deep Learning and Unsupervised Feature Learning. Andrew Y. Ng, [pdf], Autonomous Operation of Novel Elevators for Robot Navigation, Self-taught learning: Transfer learning from unlabeled data, Jiquan Ngiam, Pangwei Koh, Zhenghao Chen, Sonia Bhaskar and Andrew Y. Ng. pdf], Map-Reduce for Machine Learning on Multicore. In Proceedings of the pdf, In Journal of Machine Learning Research, 7:1743-1788, 2006. Best paper award. J. Zico Kolter and Andrew Y. Ng. Ashutosh Saxena, Justin Driemeyer and Andrew Y. Ng. [ps, pdf] [ps, pdf coming soon], Robotic Grasping of Novel Objects, [ps, pdf]. [pdf], Learning grasp strategies with partial shape information, Rion Snow, Brendan O'Connor, Daniel Jurafsky and Andrew Y. Ng. Best student paper award. Eric H. Huang, Richard Socher, Christopher D. Manning and Andrew Y. Ng Eric Brill, Jimmy Lin, Michele Banko, Susan Dumais, and Andrew Y. Ng. Andrew Y. Ng, Michael Jordan, and Yair Weiss. In Robotics Science and Systems (RSS) Honglak Lee and and Andrew Y. Ng. In Proceedings of the Twentieth International Joint Conference In Proceedings of the Twenty-third Conference on Uncertainty in Artificial Intelligence, 2007. Bayesian inference for linguistic annotation pipelines, Benjaminn Sapp, Ashutosh Saxena, and Andrew Y. Ng. Preventing "Overfitting" of Cross-Validation data, Andrew Y. Ng, in Proceedings of the Fourteenth International Conference on Machine Learning, 1997. An extended version of the paper is also available. [pdf] Machine Learning, 1998. Preventing "Overfitting" of Cross-Validation data, Andrew Y. Ng, in Proceedings of the Fourteenth International Conference on Machine Learning, 1997. Andrew Y. Ng and Michael Jordan. on in Artificial Intelligence, 1997. J. Zico Kolter and Andrew Y. Ng. [pdf], Semantic Compositionality through Recursive Matrix-Vector Spaces, Bayesian inference for linguistic annotation pipelines, pdf], Depth Estimation using Monocular and Stereo Cues, and Theoretical Comparison of Model Selection Methods, Learning omnidirectional path following using dimensionality reduction, Ben Tse, Eric Berger and Eric Liang. Andrew NgAndrew Ng Images Speech Behavior Applications of Deep Learning 3. Stable algorithms for link analysis, Machine Learning, 1997. [ps, pdf], Inverted autonomous helicopter flight via reinforcement learning, In International Conference on Robotics and Automation (ICRA), 2009. Cheng-Tao Chu, Sang Kyun Kim, Yi-An Lin, YuanYuan Yu, In International Conference on Robotics and Automation (ICRA), 2009. Highlights from recent AI Conference include the inevitable merger of IQ and EQ in computing, Deep learning to fight cancer, AI as the new electricity and advice from Andrew Ng, Deep reinforcement learning advances and frontiers, and Tim O’Reilly analysis of concerns that AI is the single biggest threat to the survival of humanity. ICCV workshop on Virtual Representations and Modeling of Large-scale environments (VRML), on Artificial Intelligence (IJCAI-07), 2007. MDP based speaker ID for robot dialogue, In IEEE Transactions on Pattern Analysis and Machine Intelligence (PAMI), 2008. Rajat Raina, Anand Madhavan and Andrew Y. Ng. [ps, pdf] In NIPS 16, 2004. Long version to appear in Machine Learning. From uncertainty to belief: Inferring the specification within, [pdf], A Probabilistic Model for Semantic Word Vectors O'Neil, O. Vinyals, P. Nguyen, and A.Y. [ps, [ps, pdf], Online learning of pseudo-metrics, pdf], Sparse deep belief net model for visual area V2,

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