1. A method for classifying display ads automatically into a taxonomy of categories, the method comprising: using a processor device, causing a computer to perform steps of: extracting first text features from an ad image of a display ad using optical character recognition (OCR) techniques; identifying objects of interest from the ad image using object detection and recognition techniques in computer vision; extracting second text features from a title, keywords, and content of a landing page (a web-page of an advertiser that a user is redirected to when clicking an ad) associated with the display ad; generating bag-of-words ad features using the extracted first and second text features, as well as attributes of the advertiser; using the generated bag-of-words ad features to categorize the display ad; training statistical models using the generated bag-of-words ad features on a historical dataset of ads labeled by human editors; and determining relevant categories of unlabeled ads using the trained statistical models to classify the display ads.