Multi Target Prediction

In this blog, lets talk about multi target variables. In a generic machine learning model prediction scenario, where we will have input features and single target variable. Input Feature Output Feature x1 , x2 , x3 , x4… y Assigning multiple target variables would throw an error on line... Read more 26 Dec 2018 - 3 minute read

Neural Network without Math

Let’s cover the fundamentals. What is Convolution? Convolution uses kernels/filter to extract information from images. Different kernels can extract different representations from images. For different tasks such as sharpening , edge detection , blurring different kernels can be employed. Kernel is matrix which slides upon the image to extrac... Read more 12 Dec 2018 - 3 minute read

Summary - SGDR

SGDR: STOCHASTIC GRADIENT DESCENT WITH WARM RESTARTS Restart techniques are common in gradient-free optimization to deal with multimodal functions. Partial warm restarts are also gaining popularity in gradientbased optimization to improve the rate of convergence in accelerated gradient schemes to deal with ill-conditioned functions. In ... Read more 28 Nov 2018 - 3 minute read

AI @ Cornell

Research Group Machine Learning Robotics Vision Projects Vision Recognition, Image Matching and Image Databases Object Recognition using the Hausdorff Distance Spatially Coherent Matching and Bayesian Recognition Flexible Object Recognition Motion, Stereo and Segmentation Image Segmentation using Local Variation Ma... Read more 18 Nov 2018 - less than 1 minute read

List of AI Research Projects at Stanford.MIT.CMU

Stanford Intelligent wearable Robotics Safe feedback interactions in human autonomous vehicle systems Detailed understanding of human actions and behavior for smart vehicles Human centric autonomous and assistive driving Understanding driver state in laboratory and naturalistic environments ... Read more 16 Nov 2018 - 1 minute read

Summary - Gradient Descent Finds Global Minimum

Gradient Descent Finds Global Minima of Deep Neural Networks Simon S. Du Jason D. Lee Haochuan Li Liwei Wang Xiyu Zhai Abstract Gradient descent finds a global minimum in training deep neural networks despite the objective function being non-convex. The current paper proves gradient descent achieves zero training loss in polyn... Read more 14 Nov 2018 - 7 minute read

Summary - Mask RCNN

MASK R-CNN Facebook AI Research (FAIR) Kaiming He Georgia Gkioxari Piotr Dollar Ross Girshick What does Mask R-CNN do We present a conceptually simple, flexible, and general framework for object instance segmentation. Our approach efficiently detects objects in an image while simultaneously generating a high-quality segmentation... Read more 10 Nov 2018 - 11 minute read

Interesting projects at Microsoft Research AI

Project Frigatebird. Link Github Code Taking instantaneous decisions during an uncertain situation is near impossible for machines even when considering multi-level observations and their striving ability to learn complex policies. This progress is facilitated by the availability of abundant data, simulators such as games. These projects ... Read more 10 Nov 2018 - 2 minute read

Summary - Google BERT

BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding Jacob Devlin Ming-Wei Chang Kenton Lee Kristina Toutanova Abstract What’s BERT BERT stands for Bidirectional Encoder Representations from Transformers. How BERT is unique BERT is designed to pre-train deep bidirectional representations by jointl... Read more 06 Nov 2018 - 9 minute read