Understanding CNN

This is a summarization of the Explanatory Graphs for CNNs paper. A graphical model is employed to understand the hierarchial feature representation hidden inside the CNN network which facilitates the classification , localization applications in Deep learning. The feature representation pattern from each filter is extracted to understand using... Read more 15 Jan 2019 - 2 minute read

Gated Graph Sequence Neural Networks

Gated Graph Sequence Neural Networks Authors: Yujia Li & Richard Zemel Department of Computer Science, University of Toronto Toronto, Canada {yujiali,zemel}@cs.toronto.edu Marc Brockschmidt & Daniel Tarlow Microsoft Research Cambridge, UK {mabrocks,dtarlow}@microsoft.com ... Read more 01 Jan 2019 - 9 minute read

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