31![Depth Estimation using Monocular and Stereo Cues Ashutosh Saxena, Jamie Schulte and Andrew Y. Ng Computer Science Department Stanford University, Stanford, CA 94305 {asaxena,schulte,ang}@cs.stanford.edu Depth Estimation using Monocular and Stereo Cues Ashutosh Saxena, Jamie Schulte and Andrew Y. Ng Computer Science Department Stanford University, Stanford, CA 94305 {asaxena,schulte,ang}@cs.stanford.edu](https://www.pdfsearch.io/img/3876fe4c5646d928becbde7a70036b6c.jpg) | Add to Reading ListSource URL: www.cs.cornell.eduLanguage: English - Date: 2009-07-21 20:22:23
|
---|
32![CS229 Lecture notes Andrew Ng 1 The perceptron and large margin classifiers CS229 Lecture notes Andrew Ng 1 The perceptron and large margin classifiers](https://www.pdfsearch.io/img/4722a346eb9092d5304e89ddf7a39859.jpg) | Add to Reading ListSource URL: cs229.stanford.eduLanguage: English - Date: 2012-11-26 03:25:38
|
---|
33![CS229 Lecture notes Andrew Ng Mixtures of Gaussians and the EM algorithm In this set of notes, we discuss the EM (Expectation-Maximization) for density estimation. Suppose that we are given a training set {x(1) , . . . , CS229 Lecture notes Andrew Ng Mixtures of Gaussians and the EM algorithm In this set of notes, we discuss the EM (Expectation-Maximization) for density estimation. Suppose that we are given a training set {x(1) , . . . ,](https://www.pdfsearch.io/img/a27081768bf74538bbf3d37f356c7fe9.jpg) | Add to Reading ListSource URL: cs229.stanford.eduLanguage: English - Date: 2012-11-26 03:26:12
|
---|
34![CS229 Lecture notes Andrew Ng Part XIII Reinforcement Learning and CS229 Lecture notes Andrew Ng Part XIII Reinforcement Learning and](https://www.pdfsearch.io/img/35c7af0b266a2581718021baa707a0e8.jpg) | Add to Reading ListSource URL: cs229.stanford.eduLanguage: English - Date: 2012-11-26 03:35:03
|
---|
35![Optical Illusion Sara Bolouki, Roger Grosse, Honglak Lee, Andrew Ng 1. Introduction The goal of this project is to explain some of the illusory phenomena using sparse coding and whitening model. Instead of the sparse cod Optical Illusion Sara Bolouki, Roger Grosse, Honglak Lee, Andrew Ng 1. Introduction The goal of this project is to explain some of the illusory phenomena using sparse coding and whitening model. Instead of the sparse cod](https://www.pdfsearch.io/img/f0dbc7d35d8b338ead364f63223333d8.jpg) | Add to Reading ListSource URL: cs229.stanford.eduLanguage: English - Date: 2011-09-14 20:33:06
|
---|
36![CS229 Lecture notes Andrew Ng Part VII Regularization and model CS229 Lecture notes Andrew Ng Part VII Regularization and model](https://www.pdfsearch.io/img/fb8558bf9c5df82fdf6addabe1cde30e.jpg) | Add to Reading ListSource URL: cs229.stanford.eduLanguage: English - Date: 2012-11-26 03:25:12
|
---|
37![CS229 Lecture notes Andrew Ng Part XII Independent Components CS229 Lecture notes Andrew Ng Part XII Independent Components](https://www.pdfsearch.io/img/42ccc88719931c8a124aabc86c27d1ae.jpg) | Add to Reading ListSource URL: cs229.stanford.eduLanguage: English - Date: 2012-11-26 03:34:43
|
---|
38![Feature selection, L1 vs. L2 regularization, and rotational invariance Andrew Ng ICML 2004 Presented by Paul Hammon Feature selection, L1 vs. L2 regularization, and rotational invariance Andrew Ng ICML 2004 Presented by Paul Hammon](https://www.pdfsearch.io/img/62faf7760dfc726985ffffa7dbc0392f.jpg) | Add to Reading ListSource URL: cseweb.ucsd.eduLanguage: English - Date: 2007-03-06 18:56:02
|
---|
39![3-D Reconstruction from Sparse Views using Monocular Vision Ashutosh Saxena, Min Sun and Andrew Y. Ng Computer Science Department, Stanford University, Stanford, CA 94305 {asaxena,aliensun,ang}@cs.stanford.edu Abstract 3-D Reconstruction from Sparse Views using Monocular Vision Ashutosh Saxena, Min Sun and Andrew Y. Ng Computer Science Department, Stanford University, Stanford, CA 94305 {asaxena,aliensun,ang}@cs.stanford.edu Abstract](https://www.pdfsearch.io/img/c596e548464c9259deb69cece7eba839.jpg) | Add to Reading ListSource URL: ai.stanford.eduLanguage: English - Date: 2007-09-02 15:50:38
|
---|
40![High Speed Obstacle Avoidance using Monocular Vision and Reinforcement Learning Jeff Michels Ashutosh Saxena Andrew Y. Ng High Speed Obstacle Avoidance using Monocular Vision and Reinforcement Learning Jeff Michels Ashutosh Saxena Andrew Y. Ng](https://www.pdfsearch.io/img/65199ec21c4b72d25f886d301f657dd1.jpg) | Add to Reading ListSource URL: ai.stanford.eduLanguage: English - Date: 2005-06-01 18:39:04
|
---|