Since its birth in 1956, the AI dream has been to build systems that exhibit "broad spectrum" intelligence. A long version is also available. In Proceedings of the Twenty-fourth International Conference on Machine Learning, 2007. [ps, In Proceedings of the Twenty-third International Conference on Machine Learning, 2006. pdf], High-speed obstacle avoidance using monocular vision and reinforcement learning, In Proceedings of the Twenty-third International Conference on Machine Learning, 2006. [ps, Discriminative Learning of Markov Random Fields for Segmentation of 3D Range Data, and Andrew Y. Ng. Also a book chapter Best paper award: Best application paper. [ps, pdf]. Jeff Michels, Ashutosh Saxena and Andrew Y. Ng. and Theoretical Comparison of Model Selection Methods, In NIPS 16, 2004. Twenty-first International Conference on Machine Learning, 2004. [ps, pdf] In Proceedings of the [ps, pdf]. CS229: Machine Learning, Autumn 2008. Map-Reduce for Machine Learning on Multicore. Long version to appear in Machine Learning. In Proceedings of the [ps, pdf] pdf] Make3d: Building 3d models from a single still image. Convergence rates of the Voting Gibbs classifier, with and Andrew Y. Ng. Honglak Lee and and Andrew Y. Ng. Rion Snow, Brendan O'Connor, Daniel Jurafsky and Andrew Y. Ng. Andrew Ng's research is in machine learning and in statistical AI algorithms for data mining, pattern recognition, and control. Selected Papers: In Proceedings of the pdf], Depth Estimation using Monocular and Stereo Cues, Learning factor graphs in polynomial time & sample complexity, Michael Jordan, 1998. videos] In Proceedings of the Twentieth International Joint Conference pdf] Quadruped robot: Learning algorithms to enable a four-legged robot to climb over obstacles and negotiate rugged terrain. Accepted to Machine Learning. [ps, pdf], Robust textual inference via learning and abductive reasoning, Gary Bradski, Andrew Y. Ng and Kunle Olukotun. Andrew Ng: Deep learning has created a sea change in robotics. Machine Learning, 1998. Bayesian inference for linguistic annotation pipelines, In CVPR 2006. Machine Learning Deep Learning AI. workshop on Robot Manipulation, 2008. In Proceedings of the Conference on Computer Vision and Pattern Recognition (CVPR), 2005. Einat Minkov, William Cohen and Andrew Y. Ng. [ps, [ps, Ashutosh Saxena, Lawson Wong, and Andrew Y. Ng. broad competence artificial intelligence, [ps, pdf] [ps, pdf], Policy search via density estimation, Michael Kearns, Yishay Mansour and Andrew Y. Ng. Scott Davies, Andrew Y. Ng and Andrew Moore. He is a Chinese English compu t er scientist, executive, investor, and entrepreneur. pdf, Click here to see solutions for all Machine Learning Coursera Assignments. Chuong Do (Tom), Masa Matsuoka, Surya Singh, Alan Chen, Adam Coates, Andrew Y. Ng and Sebastian Thrun. Honglak Lee, Yirong Shen, Chih-Han Yu, Gurjeet Singh, and Andrew Y. Ng. Pieter Abbeel and Andrew Y. Ng. Ashutosh Saxena, Min Sun, Andrew Y. Ng. In Proceedings of the Ashutosh Saxena, Min Sun, and Andrew Y. Ng. The course will also discuss recent applications of machine learning, such as to robotic control, data mining, autonomous navigation, bioinformatics, speech recognition, and text and web data processing. Archived. Ted Kremenek, Andrew Y. Ng and Dawson Engler. pdf, Now Andrew Ng's research is in machine learning and in statistical AI algorithms for data mining, pattern recognition, and control. Click here to see more codes for NodeMCU ESP8266 and similar Family. in Proceedings of the Thirteenth Annual Conference on Uncertainty In Proceedings of the Sixteenth International Conference on Machine Learning, 1999. Automatic single-image 3d reconstructions of indoor Manhattan world scenes, of AI, to build a useful, general purpose home assistant robot. PhD Student. Andrew Y. Ng, Daishi Harada and Stuart Russell. [ps, pdf], Exploration and apprenticeship learning in reinforcement learning, In AAAI (Nectar Track), 2008. Shai Shalev-Shwartz, Yoram Singer and Andrew Y. Ng. Course Description. It may be the most well-known course on machine learning on the web. [ps, pdf], Discriminative Learning of Markov Random Fields for Segmentation of 3D Range Data, In NIPS*2007. pdf], Learning Factor Graphs in Polynomial Time and Sample Complexity, pdf], Map-Reduce for Machine Learning on Multicore. Ashutosh Saxena, [ps, Robotic Grasping of Novel Objects using Vision, Best paper award. [ps, [ps, Try to solve all the assignments by yourself first, but if you get stuck somewhere then feel free to browse the code. Ashutosh Saxena, Min Sun, and Andrew Y. Ng. Seventeenth International Conference on Machine Learning, 2000. SIGIR Conference on Research and Development in Information Retrieval, 2001. [ps, Adam Coates, Twenty-first International Conference on Machine Learning, 2004. in Artificial Intelligence, 1997. [ps, pdf], Approximate planning in large POMDPs via reusable trajectories, as Training Examples, In NIPS 18, 2006. J. Zico Kolter, Mike Rodgers and Andrew Y. Ng. Andrew Y. Ng and Stuart Russell. In NIPS*2007. This course will be also available next quarter.Computers are becoming smarter, as artificial i… CS229: Machine Learning, Autumn 2008. In Proceedings of the Twenty-second International Conference on Machine Learning, 2005. Pieter Abbeel, Dmitri Dolgov, Andrew Y. Ng and Sebastian Thrun. [ps, pdf], A Vision-based System for Grasping Novel Objects in Cluttered Environments, [ps, Stephen Gould, Paul Baumstarck, Morgan Quigley, Andrew Y. Ng and Daphne Koller. [ps, [ps, In NIPS 14,, 2002. In NIPS 19, 2007. Feature selection, L1 vs. L2 regularization, and rotational invariance, Andrew Ng is Co-founder of Coursera, and an Adjunct Professor of Computer Science at Stanford University. pdf] [ps, [ps, Exercise 5: Regularization. Transfer learning for text classification, ... For example, besides developing machine learning algorithms, you may also need to work on data acquisition, conduct user interviews, or do frontend engineering. Honglak Lee, Ekanadham Chaitanya, and Andrew Y. Ng. Pieter Abbeel, Varun Ganapathi and Andrew Y. Ng. [ps, pdf] pdf], Fast Gaussian Process Regression using KD-trees, Learning to Open New Doors, [ps, pdf], Improving Text Classification by Shrinkage in a Hierarchy of Classes, [ps, [ps, pdf] I will try my best to answer it. [ps, [ps, Have we met? [ ps , pdf ] A dynamic Bayesian network model for autonomous 3d reconstruction from a single indoor image , Erick Delage, Honglak Lee and Andrew Y. Ng. on Artificial Intelligence (IJCAI-07), 2007. Using inaccurate models in reinforcement learning, [ps, on Artificial Intelligence (IJCAI-07), 2007. PEGASUS: A policy search method for large MDPs and POMDPs, Ashutosh Saxena, Justin Driemeyer, Justin Kearns, Chioma Osondu, Michael Kearns, Yishay Mansour, Andrew Y. Ng and Dana Ron, [ps, pdf], Cheap and Fast - But is it Good? SIGIR Conference on Research and Development in Information Retrieval, 2001. Spam deobfuscation using a hidden Markov model, Michael Kearns, Yishay Mansour and Andrew Y. Ng. pdf, Stephen Gould, Paul Baumstarck, Morgan Quigley, Andrew Y. Ng and Daphne Koller. Course Description You will learn to implement and apply machine learning algorithms.This course emphasizes practical skills, and focuses on giving you skills to make these algorithms work. An extended version of the paper is also available. Space-indexed Dynamic Programming: Learning to Follow Trajectories, Ashutosh Saxena, Min Sun, Andrew Y. Ng. Scott Davies, Andrew Y. Ng and Andrew Moore. on pdf] In Proceedings of the Seventeenth International Joint Conference Rion Snow, Dan Jurafsky and Andrew Y. Ng. Mike Brzozowski, Kendra Carattini, Scott R. Klemmer, Patrick Mihelich, Jiang Hu, Andrew Y. Ng. In Proceedings of the International Symposium on Robotics Research (ISRR), 2007. - Familiarity with the basic linear algebra (any one of Math 51, Math 103, Math 113, or CS 205 would be much more than necessary.). [pdf], Make3D: Learning 3-D Scene Structure from a Single Still Image, Andrew Y. Ng, Alice X. Zheng and Michael Jordan. Yirong Shen, Andrew Y. Ng and Matthias Seeger. [pdf], Quadruped robot obstacle negotiation via reinforcement learning, [ps, pdf] Ashutosh Saxena, Sung Chung, and Andrew Y. Ng. In NIPS 12, 2000. In ECCV workshop on Multi-camera and Multi-modal Sensor Fusion Algorithms and Applications (M2SFA2), Teaching: Morgan Quigley, Pieter Abbeel, Sham Kakade and Andrew Y. Ng. Pieter Abbeel, Morgan Quigley and Andrew Y. Ng. Machine Learning, 1998. Ashutosh Saxena, Justin Driemeyer, and Andrew Y. Ng. In NIPS 18, 2006. David Blei, Andrew Y. Ng, and Michael Jordan. pdf] In Proceedings of EMNLP 2007. [ps, pdf]. pdf] [ps, pdf], A Factor Graph Model for Software Bug Finding, [ps, pdf] [ps, pdf] Learning factor graphs in polynomial time & sample complexity, In Proceedings of the In Proceedings of the Fifteenth International Conference on [ps, pdf], Learning syntactic patterns for automatic hypernym discovery, [ps, pdf], Online bounds for Bayesian algorithms, pdf] Integrating visual and range data for robotic object detection, To be considered for enrollment, join the wait list and be sure to complete your NDO application. [ps, pdf] Inverted autonomous helicopter flight via reinforcement learning, Ted Kremenek, Paul Twohey, Godmar Back, Andrew Y. Ng and Dawson Engler. Depth Estimation using Monocular and Stereo Cues, pdf], Probabilistic Mobile Manipulation in Dynamic Environments, with Application to Opening Doors, pdf], Learning to grasp novel objects using vision, Augmented WordNets: Automatically enlarging WordNet, using machine learning. Andrew Ng’s Machine Learning Stanford course is one of the most well-known and comprehensive introduction courses on data science. Preventing "Overfitting" of Cross-Validation data, , 2006. Program Manager. Bayesian estimation for autonomous object manipulation based on tactile sensors, Twenty-first International Conference on Machine Learning, 2004. [ps, [ps, Only applicants with completed NDO applications will be admitted should a seat become available. Ellen Klingbeil, Ashutosh Saxena, Andrew Y. Ng. In Journal of Machine Learning Research, 7:1743-1788, 2006. He is interested in the analysis of such algorithms and the development of new learning methods for novel applications. [ps, pdf] In Proceedings of the Fifteenth National Conference on Artificial Intelligence (AAAI-98), 1998. In Proceedings of the International Symposium on Robotics Research (ISRR), 2007. large Markov decision processes, in Proceedings of the Fourteenth International Conference on Hierarchical Apprenticeship Learning with Applications to Quadruped Locomotion, In Uncertainty in [ps, pdf] Jenny Finkel, Chris Manning and Andrew Y. Ng. Adam Coates, Latent Dirichlet Allocation, In Proceedings of the 44th Annual Meeting of the Association for Computational Linguistics (ACL), 2006. Andrew Y. Ng, Andrew McCallum, Roni Rosenfeld, Tom Mitchell and Andrew Y. Ng In Proceedings of the Twenty-third Conference on Uncertainty in Artificial Intelligence, 2007. [ps, pdf coming soon], A Complete Control Architecture for Quadruped Locomotion Over Rough Terrain, Workshop on Reinforcement Learning at ICML97, 1997. [ps, pdf] In Proceedings of the I began working on machine learning and computer vision and perception. In NIPS 16, 2004. on Artificial Intelligence (IJCAI-07), 2007. A shorter version had also appeard in There are a few examples of companies in the machine learning industry that are open-sourcing a lot of their tech-stack and I assume, have the goal of making a return on that technology investment. Anya Petrovskaya, Oussama Khatib, Sebastian Thrun, and Andrew Y. Ng. Rion Snow, Dan Jurafsky and Andrew Y. Ng. Project homepages: Twenty-first International Conference on Machine Learning, 2004. [ps, pdf] [pdf] Online learning of pseudo-metrics, Ashutosh Saxena, Lawson Wong, and Andrew Y. Ng. In NIPS 12, 2000. Machine Learning, 1997. In International Journal of Robotics Research (IJRR), 2008. [ps, Chuong Do and Andrew Y. Ng. Honglak Lee, Yirong Shen, Chih-Han Yu, Gurjeet Singh, and Andrew Y. Ng. In Proceedings of the International Conference on Intellegent Robots and Systems (IROS), 2008. code], Learning to merge word senses, In NIPS 17, 2005. Boosting algorithms and weak learning ; On critiques of ML ; Other Resources. J. Andrew Bagnell, Sham Kakade, Andrew Y. Ng and Jeff Schneider, Click here to see more codes for Raspberry Pi 3 and similar Family. and Andrew Y. Ng. In Proceedings of the Twenty-first Conference on Uncertainty in Artificial Intelligence, 2005. [ps, pdf], Preventing "Overfitting" of Cross-Validation data, Anya Petrovskaya and Andrew Y. Ng. Quadruped robot: Learning algorithms to enable a four-legged robot to climb over obstacles and negotiate rugged terrain. In Proceedings of EMNLP 2007. pdf], Distance metric learning, with application to clustering with side-information, Eric Xing, Andrew Y. Ng, Michael Jordan, and Stuart Russell. ICCV workshop on Virtual Representations and Modeling of Large-scale environments (VRML), Portable GNSS Baseband Logging, and Andrew Y. Ng. In Proceedings of EMNLP 2006. pdf], Portable GNSS Baseband Logging, [pdf], A Fast Data Collection and Augmentation Procedure for Object Recognition, [ps, pdf], Classification with Hybrid Generative/Discriminative Models, [ps, [ps, A sparse sampling algorithm for near-optimal planning in Workshop on Reinforcement Learning at ICML97, 1997. On Feature Selection: Learning with Exponentially many Irrelevant Features In Proceedings of the In ECCV workshop on Multi-camera and Multi-modal Sensor Fusion Algorithms and Applications (M2SFA2), 2008. To realize its vision of a home assistant robot, STAIR will unify into a single platform tools drawn from all of these AI subfields. (IJCAI-99), 1999. In Proceedings of the Twentieth International Joint Conference Rion Snow, Sushant Prakash, Dan Jurafsky and Andrew Y. Ng. pdf], Shift-Invariant Sparse Coding for Audio Classification, the Sixteenth International Joint Conference on Artificial Intelligence Andrew Y. Ng and Michael Jordan. pdf] 7-50, 1997. [ps, Peripheral-Foveal Vision for Real-time Object Recognition and Tracking in Video In this course, you'll learn about some of the most widely used and successful machine learning techniques. Pieter Abbeel, Daphne Koller, Andrew Y. Ng Professor Andrew Ng is Director of the Stanford Artificial Intelligence Lab, the main AI research organization at Stanford, with 20 professors and about 150 students/post docs. Andrew McCallum, Roni Rosenfeld, Tom Mitchell and Andrew Y. Ng Andrew Y. Ng and Michael Jordan. In Robotics Science and Systems (RSS) Dave S. De Lorenzo, Yi Gu, Sara Bolouki, Dennis Akos, [ps, pdf] In NIPS 17, 2005. [ps, pdf] Ng's research is in the areas of machine learning and artificial intelligence. YouTube. [ps, pdf] (Stat 116 is sufficient but not necessary.) Topics include: supervised learning (generative/discriminative learning, parametric/non-parametric learning, neural networks, support vector machines); unsupervised learning (clustering, Twenty-first International Conference on Machine Learning, 2004. in Machine Learning 27(1), pp. (You can Pieter Abbeel and Andrew Y. Ng. Students are expected to have the following background: Artificial Intelligence, Proceedings of the Sixteenth Conference, 2000. In 11th International Symposium on Experimental Robotics (ISER), 2008. 3D Representation for Recognition (3dRR-07), 2007. In Proceedings of the Twenty-second International Conference on Machine Learning, 2005. Journal of Machine Learning Research, 3:993-1022, 2003. Spam deobfuscation using a hidden Markov model, Apprenticeship learning via inverse reinforcement learning, [ps, Previous projects: A list of last quarter's final projects can be found here. Learning 3-D Scene Structure from a Single Still Image, in Machine Learning 27(1), pp. [pdf] Anya Petrovskaya and Andrew Y. Ng. pdf] Robust textual inference via learning and abductive reasoning, [ps, Feel free to ask doubts in the comment section. Autonomous Helicopter: Machine learning for high-precision aerobatic helicopter flight. Room 156, Gates Building 1A In International Symposium on Experimental Robotics, 2004. Mike Brzozowski, Kendra Carattini, Scott R. Klemmer, Patrick Mihelich, Jiang Hu, Andrew Y. Ng. On Discriminative vs. Generative Classifiers: A comparison [ps, pdf]. He ha pdf], Learning vehicular dynamics, with application to modeling helicopters, In Proceedings of the Conference on Computer Vision and Pattern Recognition (CVPR), 2005. Tel: (650)725-2593 [ps, pdf] [ps, Link analysis, eigenvectors, and stability, Publication date 2008 Topics machine learning, statistics, Regression Publisher Academic Torrents Contributor Academic Torrents. A shorter version had also appeard in In Proceedings of the Seventeenth International Joint Conference In Proceedings of the Fifteenth National Conference on Artificial Intelligence (AAAI-98), 1998. # Machine Learning (Coursera) This is my solution to all the programming assignments and quizzes of Machine-Learning (Coursera) taught by Andrew Ng. [ps, pdf] An Information-Theoretic Analysis of pdf], Automatic single-image 3d reconstructions of indoor Manhattan world scenes, Erick Delage, Honglak Lee and Andrew Y. Ng. Dave S. De Lorenzo, Yi Gu, Sara Bolouki, Dennis Akos, Best student paper award. Note: One of my favorite ML courses of all time! [ps, pdf] [ps, pdf], Stable algorithms for link analysis, broad competence artificial intelligence, [ps, pdf], Algorithms for inverse reinforcement learning, Twenty-first International Conference on Machine Learning, 2004. In Also a pioneer in online education, Ng co-founded Coursera and deeplearning.ai. in Proceedings of the Fifteenth International Conference on Artificial Intelligence, Proceedings of the Sixteenth Conference, 2000. Bayesian inference for linguistic annotation pipelines, In Proceedings of the Twentieth International Joint Conference In Proceedings of the Fifth International Conference on Field Service Robotics, 2005. [ps, Cheap and Fast - But is it Good? supplementary material] Pieter Abbeel, Quadruped robot obstacle negotiation via reinforcement learning, You'll have the opportunity to implement these algorithms yourself, and gain practice with them. Twenty-first International Conference on Machine Learning, 2004. In NIPS*2007. In NIPS 19, 2007. [ps, Michael Kearns, Yishay Mansour, Andrew Y. Ng and Dana Ron, In Proceedings of the 44th Annual Meeting of the Association for Computational Linguistics (ACL), 2006. Rajat Raina, Andrew Y. Ng and Daphne Koller. Online bounds for Bayesian algorithms, Transfer learning by constructing informative priors, However, AI has since splintered into many different subfields, such as machine learning, vision, navigation, reasoning, planning, and natural language processing. Honglak Lee and and Andrew Y. Ng. Conference on Machine Learning, 2001. Proceedings of In Proceedings of the International Symposium on Robotics Research (ISRR), 2005. [ps, pdf]. [ps, pdf] In NIPS 18, 2006. Olga Russakovsky, Stephen Gould, Joakim Arfvidsson, Adrian Kaehler, Benjamin Sapp, In NIPS 14,, 2002. Rajat Raina, Erick Delage, Honglak Lee and Andrew Y. Ng. Twenty-first International Conference on Machine Learning, 2004. In AAAI (Nectar Track), 2008. Exploration and apprenticeship learning in reinforcement learning, Pieter Abbeel, Varun Ganapathi and Andrew Y. Ng. [ps, by Stanford and Andrew Ng. In NIPS 19, 2007. Gary Bradski, Andrew Y. Ng and Kunle Olukotun. Semantic taxonomy induction from heterogenous evidence, To begin, download ex5Data.zip and extract the files from the zip file. supplementary material] Andrew Y. Ng and Michael Jordan. dimensionality reduction, kernel methods); learning theory (bias/variance tradeoffs; VC theory; large margins); reinforcement learning and adaptive control. Benjaminn Sapp, Ashutosh Saxena, and Andrew Y. Ng. pdf], Solving the problem of cascading errors: Approximate SIGIR Conference on Research and Development in Information Retrieval, 2006. 2007. Probabilistic Mobile Manipulation in Dynamic Environments, with Application to Opening Doors, Evaluating Non-Expert Annotations for Natural Language Tasks, Seventeenth International Conference on Machine Learning, 2000. In NIPS 18, 2006. [ps, pdf] [ps, pdf] J. Zico Kolter, Adam Coates, Andrew Y. Ng, Yi Gu, and Charles DuHadway. Self-taught learning: Transfer learning from unlabeled data, Using inaccurate models in reinforcement learning, A sparse sampling algorithm for near-optimal planning in pdf], An Application of Reinforcement Learning to Aerobatic Helicopter Flight, J. Zico Kolter, Pieter Abbeel, and Andrew Y. Ng. reinforcement learning and robotic control, pdf, [ps, pdf], Online learning of pseudo-metrics, In NIPS*2007. [pdf], Autonomous Helicopter Tracking and Localization Using a Self-Calibrating Camera Array, In Proceedings of the Twentieth National Conference on Artificial Intelligence (AAAI), 2005. email: Stanford, CA 94305-9010 pdf] Learning to grasp novel objects using vision, [ps, [ps, Erick Delage, Honglak Lee and Andrew Y. Ng. Masa Matsuoka, Surya Singh, Alan Chen, Adam Coates, Andrew Y. Ng and Sebastian Thrun. Research interests: pdf], Contextual search and name disambiguation in email using graphs, [ps, pdf coming soon], Robotic Grasping of Novel Objects, [ps, [ps, pdf], Policy invariance under reward transformations: Theory and application to reward shaping, In Proceedings of the Human Language Technology Conference/Empirical Methods in Natural Language Processing (HLT-EMNLP), 2005. [ps, pdf] [ps, pdf coming soon] Prerequisites: workshop on Robot Manipulation, 2008. Machine learning, [ps, pdf] Integrating visual and range data for robotic object detection, In NIPS 17, 2005. In ICCV workshop on [ps, pdf], Approximate inference algorithms for two-layer Bayesian networks, Rajat Raina, Yirong Shen, Andrew Y. Ng and Andrew McCallum, Rion Snow, Brendan O'Connor, Daniel Jurafsky and Andrew Y. Ng. Andrew Y. Ng, Alice X. Zheng and Michael Jordan. [ps, Andrew Y. Ng, Michael Jordan, and Yair Weiss. pdf, [ps, Journal of machine Learning research 3 (Jan), 993-1022, 2003. © Stanford University, Stanford, California 94305, Stanford Center for Professional Development, Linear Regression, Classification and logistic regression, Generalized Linear Models, The perceptron and large margin classifiers, Mixtures of Gaussians and the EM algorithm. Title. [ps, pdf] Andrew Y. Ng and H. Jin Kim. (IJCAI-99), 1999. in Proceedings of the Thirteenth Annual Conference on Uncertainty and Andrew Y. Ng. [ps, Stanford CS229: Machine Learning. In International Symposium on Experimental Robotics (ISER) 2006. Journal of Machine Learning Research, 3:993-1022, 2003. Pieter Abbeel, Adam Coates, Timothy Hunter and Andrew Y. Ng. as Training Examples, Andrew Y. Ng. In NIPS 12, 2000. In International Symposium on Experimental Robotics, 2004. In NIPS 18, 2006. In NIPS 16, 2004. [pdf], Space-indexed Dynamic Programming: Learning to Follow Trajectories, In Proceedings of the Ninth International Conference on Spoken Language Processing (InterSpeech--ICSLP), 2006. In Proceedings of the Eighteenth International Pieter Abbeel, Daphne Koller, Andrew Y. Ng Ashutosh Saxena, Lawson Wong, Morgan Quigley and Andrew Y. Ng. pdf], Transfer learning for text classification, [ps, pdf] In ECCV workshop on Multi-camera and Multi-modal Sensor Fusion Algorithms and Applications (M2SFA2), Andrew Y. Ng and Michael Jordan. Pieter Abbeel, Adam Coates, Morgan Quigley and Andrew Y. Ng. Ashutosh Saxena, Jamie Schulte and Andrew Y. Ng. [pdf] [ps, pdf] pdf], Have we met? PhD Student. In Proceedings of the Twenty-third Conference on Uncertainty in Artificial Intelligence, 2007. Rajat Raina, Approximate planning in large POMDPs via reusable trajectories, Robotic Grasping of Novel Objects, Hard and Soft Assignment Methods for Clustering, Rajat Raina, Andrew Y. Ng and Chris Manning. J. Zico Kolter, Adam Coates, Pieter Abbeel and Andrew Y. Ng.

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