Search for tag: "machine"

Byron Wallace - Using rationales and influential training examples to (attempt to) explain neural predictions in NLP

Modern deep learning models for natural language processing (NLP) achieve state-of-the-art predictive performance but are notoriously opaque. I will discuss recent work looking to address this…

From  Kathryn Gentilello on September 10th, 2020 0 plays 0  

Daniel Russo - Global Optimality Guarantees for Policy Gradient Methods

Policy gradients methods are perhaps the most widely used class of reinforcement learning algorithms. These methods apply to complex, poorly understood, control problems by performing stochastic…

From  Kathryn Gentilello on March 13th, 2020 16 plays 0  

Ganesh Sundaramoorthi - Solving the Flickering Problem in Modern Convolutional Neural Networks

Deep Learning has revolutionized the AI field. Despite this, there is much progress needed to deploy deep learning in safety critical applications (such as autonomous aircraft). This is because…

From  Kathryn Gentilello on February 18th, 2020 23 plays 0  

Niranjan Balasubramanian - Question Answering, Event Knowledge, and other NLP Stuff: Forays into Reuse, Decomposition, and Control in Neural NLP Models

In this three-part talk, I will present some of our recent efforts that aim to control and adapt neural models to work more effectively in target applications. The first part will focus on how to…

From  Kathryn Gentilello on January 21st, 2020 0 plays 0  

Zhangyang Wang - Learning Augmented Optimization: Faster, Better and Guaranteed

Learning and optimization are closely related: state-of-the-art learning problems hinge on the sophisticated design of optimizers. On the other hand, the optimization cannot be considered as…

From  Kathryn Gentilello on December 4th, 2019 12 plays 0  

David Bamman - The Data-Driven Analysis of Literature

Literary novels push the limits of natural language processing. While much work in NLP has been heavily optimized toward the narrow domains of news and Wikipedia, literary novels are an entirely…

From  Kathryn Gentilello on November 22nd, 2019 0 plays 0  

Rachel Cummings, Swati Gupta, Judy Hoffman, Devan Desai - A Discussion on Fairness in Machine Learning with Georgia Tech Faculty

Fairness in machine learning and artificial intelligence is a hot, and important topic in tech today. Join Georgia Tech faculty members Judy Hoffman, Rachel Cummings, Deven Desai, and Swati Gupta for…

From  Kathryn Gentilello on November 14th, 2019 45 plays 0  

Muhammed Ahmed - NLP Approaches to Campaign Classification

Mailchimp is the world's largest marketing automation platform. Over a billion emails are sent by it every day, which raises the question: what exactly are users sending? We'll do a deep…

From  Kathryn Gentilello on October 30th, 2019 10 plays 0  

Athanassios Economou, Tzu-Chieh Kurt Hong - Interactive Introduction to Shape Machine

The talk presents the current state-of-the-art of the Shape Machine, a new computational, visual and disruptive technology, to leading experts in various fields including AI, engineering, computer…

From  Kathryn Gentilello on May 6th, 2019 0 plays 0  

Ashwin Swaminathan - Perception at Magic Leap

This talk presents the importance of Computer Vision and Deep learning techniques in making Magic Leap an effective spatial computing platform. The four fundamental modalities are introduced: head…

From  Kathryn Gentilello on May 1st, 2019 53 plays 0  

Nancey Green Leigh, Scott Marble - Shape Machine Symposium Welcome Remarks

This symposium presents the current state-of-the-art of the Shape Machine, a new computational, visual and disruptive technology, to leading experts in various fields including AI, engineering,…

From  Kathryn Gentilello on April 29th, 2019 0 plays 0