Dong Wang A machine learning blog

Machine Learning for Relevance

In this blog, we will look at several practical machine learning algorithms and their industrial appliations. SVM XGBoost Conditional Random Fields Neural Collaborative Filtering Yahoo! Learning to Rank Metrics Google Ads CTR Bing Sponsored Search CTR Facebook Ads CTR Google Play Recommender: Wide and Deep Didi ETA: Wide, Deep and...

3D Object Detection

Autonomous driving uses sensors to perceive the world around it. This blog considers two papers for 3d object detections using either Lidar or camera images. Lidar has depth information, but it is sparse. This makes 3d convolution inefficient. Image has dense semantics information, but it has occlusion issues, and depth...

Behavioral Planning

Planning for self-driving vehicles consists of route planning, behavioral planning and motion planning. Route planning picks sequence of road segments. Behavorial planner generates discrete motion goals (location, speed) adherence to rules of road. It specifies desired lane and speed. One local goal can be driving down this lane reaching location...

Probabilistic Robotics

Probabilistic Robotis by Sebastian Thrun, Wolfram Burgard and Dieter Fox is a great book. I decied to read it after taking the Artificial Intelligence for Robotics Udacity class. Here I am going to summary the main things I learnt from the book. All the included figures are blatantly copied from...

Machine Learning A Probabilistic Perspective

Machine Learning: A Probabilistic Perspective by Kevin P. Murphy is a comprehensive book covering many topics on machine learning. In this blog, I will try to summarize things that I find important. Preliminaries Probabilities Discrete Generative Models Gaussian Bayesian statistics EM Linear Models Linear regression Logistic regression GLM Latent Linear...