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[pdf] One full day jam-packed with data stories that will entertain, educate and inspire you. 3D Representation for Recognition (3dRR-07), 2007. in Artificial Intelligence, 1997. In Proceedings of the 7th USENIX Symposium on Operating Systems Design and Implementation (OSDI) pdf], Bayesian estimation for autonomous object manipulation based on tactile sensors, Jeff Michels, Ashutosh Saxena and Andrew Y. Ng. supplementary material], Apprenticeship Learning for Motion Planning with Application to Parking Lot Navigation, In Proceedings of EMNLP 2008. Pieter Abbeel, Daphne Koller, Andrew Y. Ng ISBN 978-981-15-83773-3, Springer Singapore, 2021. videos], Grasping Novel Objects with Depth Segmentation, Other reinforcement learning videos: High-speed obstacle avoidance, snake robot, etc. [ps, pdf], Online learning of pseudo-metrics, Einat Minkov, William Cohen and Andrew Y. Ng. 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In International Conference on Robotics and Automation (ICRA), 2009. [ps, pdf], Learning Depth from Single Monocular Images, Marius Meissner, Gary Bradski, Paul Baumstarck, Sukwon Chung Adam Coates, Pieter Abbeel and Andrew Y. Ng. [ps, pdf], On Discriminative vs. Generative Classifiers: A comparison Co-Founder. in Proceedings of the Thirteenth Annual Conference on Uncertainty In Proceedings of the Twentieth National Conference on Artificial Intelligence (AAAI), 2005. Andrew Y. Ng, Alice X. Zheng and Michael Jordan. Stephen Gould, Paul Baumstarck, Morgan Quigley, Andrew Y. Ng and Daphne Koller. [pdf], Scalable Learning for Object Detection with GPU Hardware, supplementary material] In Journal of Machine Learning Research, 7:1743-1788, 2006. In Robotics Science and Systems (RSS) In Proceedings of the International Conference on Intellegent Robots and Systems (IROS), 2008. In ICML 2012 Representation Learning Workshop. [ps, Rion Snow, Dan Jurafsky and Andrew Y. Ng. J. 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Pieter Abbeel, Adam Coates, Mike Montemerlo, Andrew Y. Ng and Sebastian Thrun. Rajat Raina, Andrew Y. Ng and Chris Manning. Rajat Raina, Alexis Battle, Honglak Lee, Benjamin Packer and Andrew Y. Ng. In Proceedings of the 44th Annual Meeting of the Association for Computational Linguistics (ACL), 2006. Preventing "Overfitting" of Cross-Validation data, Andrew Y. Ng, in Proceedings of the Fourteenth International Conference on Machine Learning, 1997. Honglak Lee, Yirong Shen, Chih-Han Yu, Gurjeet Singh, and Andrew Y. Ng. In NIPS 14, 2002. [ps, Andrew Ng: „Just as the Industrial Revolution freed up a lot of humanity from physical drudgery I think AI has the potential to free up humanity from a lot of the mental drudgery.” (Myślę, że tak jak rewolucja przemysłowa uwolniła ludzkość od katorgi fizycznej, tak Sztuczna Inteligencja może uwolnić ludzkość od katorgi umysłowej”. Andrew Y. Ng and Michael Jordan. SIGIR Conference on Research and Development in Information Retrieval, 2001. The importance of encoding versus training with sparse coding and vector quantization, [pdf] In Proceedings of the 7th USENIX Symposium on Operating Systems Design and Implementation (OSDI) Rion Snow, Sushant Prakash, Dan Jurafsky and Andrew Y. Ng. [ps, For more information, check out our privacy policy. ICCV workshop on Virtual Representations and Modeling of Large-scale environments (VRML), In NIPS 19, 2007. Andrew Y. Ng, Ronald Parr and Daphne Koller. [pdf] [ps, pdf] Adam Coates, Pieter Abbeel and Andrew Y. Ng. [pdf]. pdf], Fast Gaussian Process Regression using KD-trees, In NIPS 14, 2002. [ps, pdf] Anya Petrovskaya, Oussama Khatib, Sebastian Thrun, and Andrew Y. Ng. Also a book chapter pdf] [ps, Cheng-Tao Chu, Sang Kyun Kim, Yi-An Lin, YuanYuan Yu, Adam Coates, Machine Learning, 1998. 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Deep Learning of Invariant Features via Simulated Fixations in Video. pdf], Transfer learning for text classification, [ps, In NIPS 17, 2005. Marius Meissner, Gary Bradski, Paul Baumstarck, Sukwon Chung [ps, pdf], Data-Intensive Question Answering. Self-taught learning: Transfer learning from unlabeled data, Evaluating Non-Expert Annotations for Natural Language Tasks, Ashutosh Saxena, Justin Driemeyer, and Andrew Y. Ng. Best paper award. In Proceedings of the Twentieth International Joint Conference Drago Anguelov, Ben Taskar, Vasco Chatalbashev, Daphne Koller, Dinkar Gupta, Geremy Heitz and Andrew Y. Ng. [pdf]. in Proceedings of the Thirteenth Annual Conference on Uncertainty A sparse sampling algorithm for near-optimal planning in pdf] A Fast Data Collection and Augmentation Procedure for Object Recognition, Adam Coates, Pieter Abbeel and Andrew Y. Ng. pdf], Sparse deep belief net model for visual area V2, Rion Snow, Dan Jurafsky and Andrew Y. Ng. Mao, M.A. In NIPS*2009. David Blei, Andrew Y. Ng, and Michael Jordan. Jiquan Ngiam, Zhenghao Chen, Pangwei Koh and Andrew Y. Ng. In NIPS 12, 2000. In Proceedings of the In Proceedings of the Ninth International Conference on Spoken Language Processing (InterSpeech--ICSLP), 2006. Ashutosh Saxena, Justin Driemeyer, Justin Kearns and Andrew Y. Ng. Cheng-Tao Chu, Sang Kyun Kim, Yi-An Lin, YuanYuan Yu, CS221: Artificial Intelligence: Principles and Techniques, Winter 2009. Latent Dirichlet Allocation, In IEEE Transactions on Pattern Analysis and Machine Intelligence (PAMI), 2008. Pieter Abbeel, Daphne Koller, Andrew Y. Ng [ps, pdf], Preventing "Overfitting" of Cross-Validation data, In NIPS 2012. and Andrew Y. Ng. pdf] In Proceedings of the Fifteenth International Conference on In CHI 2006. In International Conference on Robotics and Automation (ICRA), 2009. pdf], Learning Factor Graphs in Polynomial Time and Sample Complexity, in Machine Learning 27(1), pp. Stable adaptive control with online learning, [ps, [ps, Adam Coates and Andrew Y. Ng. Semantic Compositionality through Recursive Matrix-Vector Spaces. [ps, pdf] In Proceedings of the pdf] J. Zico Kolter, Pieter Abbeel, and Andrew Y. Ng. Twenty-first International Conference on Machine Learning, 2004. Morgan Quigley, Pieter Abbeel, 5. Machine Learning, 1998. [ps, [ps, pdf], Discriminative Learning of Markov Random Fields for Segmentation of 3D Range Data, FAX: (650)725-1449 Andrew Y. Ng and Michael Jordan. From uncertainty to belief: Inferring the specification within, A Factor Graph Model for Software Bug Finding, Rajat Raina, Andrew Y. Ng and Daphne Koller. In International Conference on Robotics and Automation (ICRA), 2010. Ashutosh Saxena, Justin Driemeyer, Justin Kearns, Chioma Osondu, Using inaccurate models in reinforcement learning, Aria Haghighi, Andrew Y. Ng and Chris Manning. Machine Learning, 1998. Rajat Raina, Alexis Battle, Honglak Lee, Benjamin Packer and Andrew Y. Ng. Rajat Raina, Andrew Y. Ng and Daphne Koller. Andrew McCallum, Roni Rosenfeld, Tom Mitchell and Andrew Y. Ng Ashutosh Saxena, Lawson Wong, and Andrew Y. Ng. 2007. [ps, [ps, pdf] Ashutosh Saxena, Sung H. Chung, and Andrew Y. Ng. Quadruped robot: Learning algorithms to enable a four-legged robot to climb over obstacles and negotiate rugged terrain. Rajat Raina, Yirong Shen, Andrew Y. Ng and Andrew McCallum, [pdf], Unsupervised feature learning for audio classification using convolutional pdf] [pdf] In NIPS 12, 2000. Yirong Shen, Andrew Y. Ng and Matthias Seeger. Ashutosh Saxena, Justin Driemeyer, and Andrew Y. Ng. [ps, [ps, pdf], On Spectral Clustering: Analysis and an algorithm, Andrew Y. Ng and H. Jin Kim. In Proceedings of the code], Learning to merge word senses, Ashutosh Saxena, Min Sun, Andrew Y. Ng. Machine learning, In IEEE Transactions on Pattern Analysis and Machine Intelligence (PAMI), 2008. In NIPS 17, 2005. Ashutosh Saxena, Sung H. Chung, and Andrew Y. Ng. In the year 2014 March, they decided to announce their engagement on IEEE Spectrum. Ted Kremenek, Andrew Y. Ng and Dawson Engler. Adam Coates, Pieter Abbeel and Andrew Y. Ng. videos], Efficient sparse coding algorithms. on Artificial Intelligence (IJCAI-07), 2007. Andrew Y. Ng. Ashutosh Saxena, Lawson Wong, and Andrew Y. Ng. Rion Snow, Dan Jurafsky and Andrew Y. Ng. [pdf], Dynamic Pooling and Unfolding Recursive Autoencoders for Paraphrase Detection. Honglak Lee and and Andrew Y. Ng. In NIPS 19, 2007. [pdf, A preliminary version had also appeared in the NIPS*2010 Workshop on Deep Learning and Unsupervised Feature Learning. Dave S. 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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], Space-indexed Dynamic Programming: Learning to Follow Trajectories, J. Zico Kolter and Andrew Y. Ng. Richard Socher, Cliff Lin, Andrew Y. Ng and Christopher Manning. in Proceedings of the Fifteenth International Conference on In NIPS 14, 2002. Quadruped robot obstacle negotiation via reinforcement learning, In NIPS 12, 2000. In Proceedings of the on [ps, pdf], Online learning of pseudo-metrics, STL-10 dataset] Michael Kearns, Yishay Mansour, Andrew Y. Ng and Dana Ron, [pdf, In Robotics Science and Systems (RSS) [pdf], Autonomous Helicopter Tracking and Localization Using a Self-Calibrating Camera Array, In NIPS 17, 2005. Pieter Abbeel, Daphne Koller and Andrew Y. Ng. Best student paper award. In NIPS*2007. In Journal of Machine Learning Research, 7:1743-1788, 2006. 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Ng, Daishi Harada and Stuart Russell. code, the Sixteenth International Joint Conference on Artificial Intelligence [ps, pdf], Sparse deep belief net model for visual area V2, Workshop on Reinforcement Learning at ICML97, 1997. pdf, [pdf], Near-Bayesian Exploration in Polynomial Time, Inverted autonomous helicopter flight via reinforcement learning, workshop on Robot Manipulation, 2008. In NIPS 14,, 2002. Quoc Le, David Kamm and Andrew Y. Ng. Andrew Y. Ng, Daishi Harada and Stuart Russell. [ps, Exploration and apprenticeship learning in reinforcement learning, Learning omnidirectional path following using dimensionality reduction, on Artificial Intelligence (IJCAI-07), 2007. Honglak Lee, Alexis Battle, Raina Rajat and Andrew Y. Ng. In Proceedings of the Fifteenth National Conference on Artificial Intelligence (AAAI-98), 1998. Machine Learning, 1998. In NIPS 18, 2006. In Gary Bradski, Andrew Y. Ng and Kunle Olukotun. Quoc Le and Andrew Y. Ng. pdf], Efficient multiple hyperparameter learning for log-linear models, PhD students: Ashutosh Saxena, Justin Driemeyer and Andrew Y. Ng. Chuong Do, Chuan-Sheng Foo, Andrew Y. Ng. [ps, pdf] Ashutosh Saxena, Justin Driemeyer, Justin Kearns, Chioma Osondu, Using inaccurate models in reinforcement learning, In Proceedings of STAIR (STanford AI Robot) project: Integrating tools from all the diverse areas Rajat Raina, Alexis Battle, Honglak Lee, Benjamin Packer and Andrew Y. Ng. In Proceedings of the International Conference on Robotics and Automation (ICRA), 2006. Morgan Quigley, Pieter Abbeel, pdf], Efficient L1 Regularized Logistic Regression. [ps, pdf], Portable GNSS Baseband Logging, pdf], Portable GNSS Baseband Logging, ... 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], Learning vehicular dynamics, with application to modeling helicopters, ±åº¦å­¦ä¹ ã€‹ç³»åˆ—课程笔记及代码 | Notes in Chinese for Andrew Ng Deep Learning Course. In Proceedings of the International Conference on Robotics and Automation (ICRA), 2008. In CVPR 2006. Stephen Gould, Joakim Arfvidsson, Adrian Kaehler, Benjamin Sapp, David Blei, Andrew Y. Ng, and Michael Jordan. pdf], On Local Rewards and the Scalability of Distributed Reinforcement Learning, [ps, His wife is also a famous American Computer scientist. [pdf], Text Detection and Character Recognition in Scene Images with Unsupervised Feature Learning, application to Bayesian feature selection, [pdf], Make3D: Depth Perception from a Single Still Image, In Proceedings of the In Proceedings of the Sixteenth International Conference on Machine Learning, 1999. Learning, 2007. [ps, In Proceedings of the International Conference on Robotics and Automation (ICRA), 2006. Jeff Michels, Ashutosh Saxena and Andrew Y. Ng. [ps, pdf]. Evaluating Non-Expert Annotations for Natural Language Tasks, Andrew Y. Ng, Michael Jordan, and Yair Weiss. [ps, pdf] 2007. In NIPS 19, 2007. pdf, pdf], Distance metric learning, with application to clustering with side-information, Eric Xing, Andrew Y. Ng, Michael Jordan, and Stuart Russell. In Proceedings of the Twenty-fourth International Conference on Machine Learning, 2007. In International Symposium on Experimental Robotics (ISER) 2006. Michael Kearns, Yishay Mansour and Andrew Y. Ng. Rion Snow. [ps, [pdf], Policy Search via the Signed Derivative, supplementary material], Apprenticeship Learning for Motion Planning with Application to Parking Lot Navigation, In Proceedings of the Second Conference on Email and Anti-Spam, 2005. pdf], Depth Estimation using Monocular and Stereo Cues, In Proceedings of the Fifteenth National Conference on Artificial Intelligence (AAAI-98), 1998. Pieter Abbeel, Morgan Quigley and Andrew Y. Ng. An Application of Reinforcement Learning to Aerobatic Helicopter Flight, Learning 3-D Scene Structure from a Single Still Image, on Artificial Intelligence (IJCAI-07), 2007. Feature selection, L1 vs. L2 regularization, and rotational invariance, In Proceedings of the Twenty-second International Conference on Machine Learning, 2005. Andrew Y. Ng and Michael Jordan. [ps, pdf], Learning random walk models for inducing word dependency probabilities, Yirong Shen, Andrew Y. Ng and Matthias Seeger. In NIPS 16, 2004. [ps, pdf] Chuong Do (Tom), [pdf, code] Machine Learning, 1998. (You can Machine Learning, 1998. An earlier version had also been presented at the NIPS 2005 Workshop on Inductive Transfer. Best paper award. Solving the problem of cascading errors: Approximate [pdf], Learning to grasp objects with multiple contact points, [pdf], Autonomous Autorotation of an RC Helicopter, Anya Petrovskaya and Andrew Y. Ng. Ted Kremenek, Andrew Y. Ng and Dawson Engler. in Learning in Graphical Models, Ed. Stanford University. In Proceedings of the Twentieth International Joint Conference In International Journal of Robotics Research (IJRR), 2008. PhD students: Andrew Y. Ng and Michael Jordan. In Proceedings of EMNLP 2006. In Proceedings of the International Symposium on Robotics Research (ISRR), 2007. In Proceedings of the Twentieth International Joint Conference In Proceedings of the and Theoretical Comparison of Model Selection Methods, large Markov decision processes, In Proceedings of the Twenty-third International Conference on Machine Learning, 2006. [ps, pdf], Efficient multiple hyperparameter learning for log-linear models, ISBN 978-981-15-83773-3, Springer Singapore, 2021. In NIPS 19, 2007. Augmented WordNets: Automatically enlarging WordNet, using machine learning. A long version is also available. In Proceedings of the International Conference on Intelligent Robots and Systems (IROS), 2010. [ps, In Proceedings of the Andrew Y. Ng, Alice X. Zheng and Michael Jordan. Andrew L. Maas, Stephen D. Miller, Tyler M. O'Neil, Andrew Y. Ng, and Patrick Nguyen. , 2006. In Proceedings of the Sixteenth International Conference on Machine Learning, 1999. DeepLearning.AI. In Proceedings of the 11th International Conference on Document Analysis and Recognition (ICDAR 2011), 2011. Also a book chapter In Proceedings of the Twenty-fifth International Conference on Machine Learning, 2008. In NIPS*2011. In NIPS 19, 2007. on Artificial Intelligence (IJCAI-01), 2001. [ps, pdf], Learning syntactic patterns for automatic hypernym discovery, It’s everything you’ve ever wanted to know about data, told by the people who know it best. [pdf], A Probabilistic Model for Semantic Word Vectors Pieter Abbeel, Adam Coates, Morgan Quigley and Andrew Y. Ng. Ashutosh Saxena, Jamie Schulte and Andrew Y. Ng. Ashutosh Saxena, Min Sun, Andrew Y. Ng. [ps, pdf]. [ps, [ps, pdf] Honglak Lee and and Andrew Y. Ng. see most of the lectures [ps, pdf] [ps, [pdf] Learning 3-D Scene Structure from a Single Still Image, Conference on Machine Learning, 2001. J. Zico Kolter, Youngjun Kim and Andrew Y. Ng. Discriminative Learning of Markov Random Fields for Segmentation of 3D Range Data, [ps, pdf], Applying Online-search to Reinforcement Learning, Bayesian estimation for autonomous object manipulation based on tactile sensors, In Proceedings of the Twentieth International Joint Conference Proceedings of J. Zico Kolter, Andrew Y. Ng and H. Jin Kim. Su-In Lee, Honglak Lee, Pieter Abbeel and Andrew Y. Ng. [pdf] Pieter Abbeel, Adam Coates, Timothy Hunter and Andrew Y. Ng. In Proceedings of the Twenty-second International Conference on Machine Learning, 2005. In Proceedings of EMNLP 2006. Yirong Shen, Andrew Y. Ng and Matthias Seeger. on Artificial Intelligence (IJCAI-07), 2007. Andrew Ng, Chief Scientist at Baidu 1. [ps, pdf], Stable algorithms for link analysis, In the International Journal of Computer Vision (IJCV), 2007. MDP based speaker ID for robot dialogue, Marius Meissner, Gary Bradski, Paul Baumstarck, Sukwon Chung In Proceedings of the Ninth International Conference on Spoken Language Processing (InterSpeech--ICSLP), 2006. Adam Coates, Andrej Karpathy, and Andrew Y. Ng. [pdf], PEGASUS: A policy search method for large MDPs and POMDPs, [ps, Morgan Quigley, Alan Asbeck and Andrew Y. Ng. Chuong Do and Andrew Y. Ng. In NIPS 16, 2004. Contextual search and name disambiguation in email using graphs, Word-level Acoustic Modeling with Convolutional Vector Regression. In AAAI, 2008. In NIPS 19, 2007. [ps, pdf], A dynamic Bayesian network model for autonomous 3d reconstruction from a single indoor image, Robotic Grasping of Novel Objects using Vision, (Online demo available.) Stephen Gould, Paul Baumstarck, Morgan Quigley, Andrew Y. Ng and Daphne Koller. Scott Davies, Andrew Y. Ng and Andrew Moore. Jeff Michels, Ashutosh Saxena and Andrew Y. Ng. Also a book chapter Ted Kremenek, Paul Twohey, Godmar Back, Andrew Y. Ng and Dawson Engler. pdf] [pdf]. Andrew NgAndrew Ng Computer vision: Find coffee mug 4. Twenty-first International Conference on Machine Learning, 2004. [ps, [ps, pdf] In Proceedings of the Twenty-Sixth International Conference on Machine Learning, 2009. In Proceedings of Robotics: Science and Systems, 2005. In NIPS 15, 2003. pdf] — Andrew Ng, Founder of deeplearning.ai and Coursera Deep Learning Specialization, Course 5 Erick Delage, Honglak Lee and Andrew Y. Ng. Semantic taxonomy induction from heterogenous evidence, In NIPS 14,, 2002. [ps, pdf], Learning first order Markov models for control, In International Symposium on Experimental Robotics, 2004. Tel: (650)725-2593 FAX: (650)725-1449 email: ang@cs.stanford.edu (if contacting me about CS229 or CS229A, please see below) In NIPS 14,, 2002. Andrew Y. Ng and Stuart Russell. In NIPS 19, 2007. Tiwari S, Suryani E, Ng AK, Mishra KK, and Singh N. Proceedings of International Conference on Big Data, Machine Learning and their Applications. An extended version of the paper is also available. In International Journal of Robotics Research (IJRR), 2008. Quoc Le, Michael Kearns, Yishay Mansour and Andrew Y. Ng. Journal of Machine Learning Research, 3:993-1022, 2003. pdf] [pdf]. email: In Proceedings of the Twenty-Eighth International Conference on Machine Learning, 2011. [ps, pdf], Apprenticeship learning via inverse reinforcement learning, In Proceedings of the Twenty-Sixth International Conference on Machine Learning, 2009. Michael Kearns, Yishay Mansour and Andrew Y. Ng. In Proceedings of the Twentieth National Conference on Artificial Intelligence (AAAI), 2005. Jiquan Ngiam, Pangwei Koh, Zhenghao Chen, Sonia Bhaskar and Andrew Y. Ng. [ps, pdf] [ps, Jiquan Ngiam, Aditya Khosla, Mingyu Kim, Juhan Nam, Honglak Lee and Andrew Y. Ng. Rion Snow, Dan Jurafsky and Andrew Y. Ng. [pdf], Regularization and Feature Selection in Least-Squares Temporal Difference Learning, Pieter Abbeel, Adam Coates, Morgan Quigley and Andrew Y. Ng. Pieter Abbeel, Dmitri Dolgov, Andrew Y. Ng and Sebastian Thrun. J. Zico Kolter and Andrew Y. Ng. In Proceedings of the International Conference on Robotics and Automation (ICRA), 2006. [ps, Ted Kremenek, Paul Twohey, Godmar Back, Andrew Y. Ng and Dawson Engler. [pdf], Stereo Vision and Terrain Modeling for Quadruped Robots, In ICCV workshop on [ps, pdf], Discriminative training of Kalman filters, [ps, pdf]. In NIPS 18, 2006. J. Zico Kolter, Adam Coates, Andrew Y. Ng, Yi Gu, and Charles DuHadway. [ps, Stanford, CA 94305-9010 In Proceedings of the Seventeenth International Joint Conference Spam deobfuscation using a hidden Markov model, Proceedings of Andrew Y. Ng. Twenty-first International Conference on Machine Learning, 2004. Learning Factor Graphs in Polynomial Time and Sample Complexity, 2008. Rion Snow, Brendan O'Connor, Daniel Jurafsky and Andrew Y. Ng. [ps, pdf]. A Vision-based System for Grasping Novel Objects in Cluttered Environments, GPU Technology Conference OFF AIR. Research interests: [pdf] Ashutosh Saxena, Justin Driemeyer, Justin Kearns, Chioma Osondu, on Artificial Intelligence (IJCAI-07), 2007. [ps, pdf], Inverted autonomous helicopter flight via reinforcement learning, Andrew Y. Ng, Alice X. Zheng and Michael Jordan. 3-D Reconstruction from Sparse Views using Monocular Vision , as Training Examples, Andrew Y. Ng and Michael Jordan. [ps, Pieter Abbeel, Varun Ganapathi and Andrew Y. Ng. In NIPS 18, 2006. [ps, pdf], Latent Dirichlet Allocation, In Proceedings of the Fifth International Conference on Field Service Robotics, 2005. In Proceedings of the International Symposium on Robotics Research (ISRR), 2005. In Proceedings of the Twentieth International Joint Conference pdf] In Proceedings of the Fifth International Conference on Field Service Robotics, 2005. In CVPR 2006. Rajat Raina, In Proceedings of the Fifteenth International Conference on Morgan Quigley, Reuben Brewer, Sai P. Soundararaj, Vijay Pradeep, Quoc V. Le and 3-D Reconstruction from Sparse Views using Monocular Vision , Quoc V. Le, Will Zou, Serena Yeung and Andrew Y. Ng. In International Symposium on Experimental Robotics, 2004. Pieter Abbeel, Varun Ganapathi and Andrew Y. Ng. [ps, [ps, [ps, pdf], Classification with Hybrid Generative/Discriminative Models, pdf], Shift-Invariant Sparse Coding for Audio Classification, pdf, From uncertainty to belief: Inferring the specification within, [pdf], Learning Sound Location from a Single Microphone, In AAAI, 2008. on Artificial Intelligence (IJCAI-09), 2009. In AISTATS 14, 2011. Roger Grosse, Rajat Raina, Helen Kwong and Andrew Y. Ng. In Proceedings of the visualizations], Energy Disaggregation via Discriminative Sparse Coding, Scott Davies, Andrew Y. Ng and Andrew Moore. Integrating visual and range data for robotic object detection, the Eighth Annual ACM Conference on Computational Learning Theory, 1995. [ps, [ps, pdf coming soon], A Complete Control Architecture for Quadruped Locomotion Over Rough Terrain, [ps, Ian J. Goodfellow, Quoc V. Le, Andrew M. Saxe, Honglak Lee and Andrew Y. Ng. In 49th Annual Meeting of the Association for Computational Linguistics (ACL), 2011. In Institute of Navigation (ION) GNSS Conference, 2007. Ben Tse, Eric Berger and Eric Liang. Hard and Soft Assignment Methods for Clustering, Ashutosh Saxena, Min Sun, Andrew Y. Ng. Adam Coates, Andrew Y. Ng Computer Science Department Stanford University Room 156, Gates Building Stanford, CA 94305-9010 . In NIPS*2007. pdf], An Application of Reinforcement Learning to Aerobatic Helicopter Flight, In NIPS 19, 2007. Andrew NgAndrew Ng Computer vision: Find coffee mug Early, poor computer vision results. [ps, Drago Anguelov, Ben Taskar, Vasco Chatalbashev, Daphne Koller, Dinkar Gupta, Geremy Heitz and Andrew Y. Ng. In Proceedings of the Sixteenth International Conference on Machine Learning, 1999. Andrew McCallum, Roni Rosenfeld, Tom Mitchell and Andrew Y. Ng Rajat Raina, Anand Madhavan and Andrew Y. Ng. [ps, So our field is evolving a lot. [ps, pdf]. in Learning in Graphical Models, Ed. Using inaccurate models in reinforcement learning, In NIPS*2007. Classification with Hybrid Generative/Discriminative Models, [ps, [ps, pdf], Policy search via density estimation, reinforcement learning and robotic control, Ted Kremenek, Paul Twohey, Godmar Back, Andrew Y. Ng and Dawson Engler. groupTime: Preference-Based Group Scheduling, PEGASUS: A policy search method for large MDPs and POMDPs, 2007. [ps, pdf], Learning random walk models for inducing word dependency probabilities, Jenny Finkel, Chris Manning and Andrew Y. Ng. [ps, pdf], Robust textual inference via learning and abductive reasoning, [pdf], On random weights and unsupervised feature learning, Semantic taxonomy induction from heterogenous evidence, Integrating visual and range data for robotic object detection, Twenty-first International Conference on Machine Learning, 2004. Andrew Ng Stanford University United States: ... Subscibe to Newsletter & Conference Alerts. [ps, pdf], Exploration and apprenticeship learning in reinforcement learning, pdf] (IJCAI-99), 1999. Efficient L1 Regularized Logistic Regression. In NIPS*2010. Richard Socher, Christopher Manning and Andrew Ng. Learning first order Markov models for control, J. Andrew Bagnell and Andrew Y. Ng. In International Conference on Robotics and Automation (ICRA), 2010. Michael Jordan, 1998. [ps, pdf coming soon], Robotic Grasping of Novel Objects, In CVPR 2006. In Proceedings of the International Conference on Intellegent Robots and Systems (IROS), 2008. Dave S. De Lorenzo, Yi Gu, Sara Bolouki, Dennis Akos, pdf], Contextual search and name disambiguation in email using graphs, (Online demo available.) the Sixteenth International Joint Conference on Artificial Intelligence J. Zico Kolter, Mike Rodgers and Andrew Y. Ng. In Proceedings of the Twentieth International Joint Conference pdf], Learning Factor Graphs in Polynomial Time and Sample Complexity, Aria Haghighi, Andrew Y. Ng and Chris Manning. Augmented WordNets: Automatically enlarging WordNet, using machine learning. In Proceedings of the Fifth International Conference on Field Service Robotics, 2005. In NIPS 17, 2005. Andrew Y. Ng, Andrew L. Maas, Raymond E. Daly, Peter T. Pham, Dan Huang, Andrew Y. Ng, and Christopher Potts. Make3d: Building 3d models from a single still image. In Proceedings of the Twenty-Eighth International Conference on Machine Learning, 2011. (2012). Emergence of Object-Selective Features in Unsupervised Feature Learning. [ps, Pieter Abbeel and Andrew Y. Ng. Kristina Toutanova, Christopher Manning and Andrew Y. Ng. Building High-Level Features using Large Scale Unsupervised Learning. [ps, pdf] in Proceedings of the Fourteenth International Conference on An extended version of the paper is also available. In Proceedings of the International Conference on Robotics and Automation (ICRA), 2006. [ps, pdf]. [ps, Ellen Kling-beil, Blake Carpenter, Olga Russakovsky and Andrew Y. Ng. In Proceedings of the 7th USENIX Symposium on Operating Systems Design and Implementation (OSDI) pdf], Bayesian estimation for autonomous object manipulation based on tactile sensors, Seventeenth International Conference on Machine Learning, 2000. Chuong Do (Tom), In Association for Computational Linguistics Conference (ACL), 2012. [ps, [ps, Peripheral-Foveal Vision for Real-time Object Recognition and Tracking in Video Learning Depth from Single Monocular Images, Andrew Y. Ng. 2012. Sham Kakade and Andrew Y. Ng. Learning grasp strategies with partial shape information, In Conference on Empirical Methods in Natural Language Processing (EMNLP 2011). In Proceedings of the Eighteenth International [ps, Selected Papers: pdf, code], Map-Reduce for Machine Learning on Multicore. Probabilistic Mobile Manipulation in Dynamic Environments, with Application to Opening Doors, In ECCV workshop on Multi-camera and Multi-modal Sensor Fusion Algorithms and Applications (M2SFA2), 2008. In AAAI, 2008. [ps, pdf] [ps, pdf], Feature selection, L1 vs. L2 regularization, and rotational invariance, pdf], Depth Estimation using Monocular and Stereo Cues, and Andrew Y. Ng. [ps, pdf] [pdf], Autonomous Sign Reading for Semantic Mapping. In Proceedings of the Second Conference on Email and Anti-Spam, 2005. Richard Socher, Brody Huval, Christopher D. Manning and Andrew Y. Ng. Depth Estimation using Monocular and Stereo Cues, Online bounds for Bayesian algorithms, Seventeenth International Conference on Machine Learning, 2000. in Artificial Intelligence, 1997. Benjaminn Sapp, Ashutosh Saxena, and Andrew Y. Ng. Automatic single-image 3d reconstructions of indoor Manhattan world scenes, Robust Textual Inference via Graph Matching, In Proceedings of the Human Language Technology Conference/Empirical Methods in Natural Language Processing (HLT-EMNLP), 2005. In Proceedings of the Seventeenth International Joint Conference [ps, pdf], Learning first order Markov models for control, Morgan Quigley, In International Conference on Robotics and Automation (ICRA), 2010. J. In Proceedings of the Twenty-second International Conference on Machine Learning, 2005. In ECCV workshop on Multi-camera and Multi-modal Sensor Fusion Algorithms and Applications (M2SFA2), Quoc V. Le, Marc'Aurelio Ranzato, Rajat Monga, Matthieu Devin, Kai Chen, Greg S. Corrado, Jeffrey Dean and Andrew Y. Ng. [ps, pdf] Project homepages: Andrew Y. Ng, Alice X. Zheng and Michael Jordan. [pdf], Learning Word Vectors for Sentiment Analysis, Stephen Gould, Paul Baumstarck, Morgan Quigley, Andrew Y. Ng and Daphne Koller. SPECIALIZATION. [ps, pdf]. [pdf], Autonomous Helicopter Aerobatics through Apprenticeship Learning, Erick Delage, Honglak Lee and Andrew Y. Ng. Chuong Do and Andrew Y. Ng. In Proceedings of the Twenty-third Conference on Uncertainty in Artificial Intelligence, 2007. Deep Learning. Andrew Y. Ng and Michael Jordan. O'Neil, O. Vinyals, P. Nguyen, and A.Y. [pdf, supplementary material], Learning hierarchical spatio-temporal features for action recognition with independent subspace analysis, SIGIR Conference on Research and Development in Information Retrieval, 2001. In NIPS 12, 2000. A preliminary version had also appeared in the NIPS*2010 Workshop on Deep Learning and Unsupervised Feature Learning. [ps, pdf], Discriminative training of Kalman filters, In Proceedings of the Ninth International Conference on Spoken Language Processing (InterSpeech--ICSLP), 2006. algorithms for text and web data processing. J. Zico Kolter, Pieter Abbeel, and Andrew Y. Ng. and Andrew Y. Ng. YouTube.) More Photos. Proceedings of Michael Kearns, Yishay Mansour and Andrew Y. Ng. [ps, pdf], On Spectral Clustering: Analysis and an algorithm, In NIPS*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 Proceedings of the Twenty-Sixth International Conference on Machine Learning, 2009. deep belief networks, In Proceedings of the Twenty-third Conference on Uncertainty in Artificial Intelligence, 2007. 3D Representation for Recognition (3dRR-07), 2007. Michael Kearns, Yishay Mansour and Andrew Y. Ng, pdf], Robust Textual Inference via Graph Matching, pdf], groupTime: Preference-Based Group Scheduling, 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 In Proceedings of the In Proceedings of the Twenty-first Conference on Uncertainty in Artificial Intelligence, 2005. Best paper award: Best application paper. 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. Learning to Open New Doors, In NIPS 19, 2007. [ps, pdf] Ashutosh Saxena, Roger Grosse, Rajat Raina, Helen Kwong and Andrew Y. Ng. He tied the knot with longtime girlfriend-turned-wife, Carol Reiley. In Uncertainty in [ps, pdf coming soon], Robotic Grasping of Novel Objects, Artificial Intelligence, Proceedings of the Sixteenth Conference, 2000. In Proceedings of the Twenty-second International Conference on Machine Learning, 2005. In Proceedings of the Twenty-First International Conference on Pattern Recognition (ICPR). Chuong Do and Andrew Y. Ng. [pdf], Learning Continuous Phrase Representations and Syntactic Parsing with Recursive Neural Networks [pdf]. Amazon’s re:MARS conference will feature Andrew Ng, iRobot CEO Colin Angle, and Robert Downey Jr. Kyle Wiggers @Kyle_L_Wiggers March … Stephen Gould, Paul Baumstarck, Morgan Quigley, Andrew Y. Ng and Daphne Koller. [ps, pdf]. [ps, pdf], Inverted autonomous helicopter flight via reinforcement learning, [ps, pdf] Portable GNSS Baseband Logging,

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