Search for tag: "learning"

Bolei Zhou - Interpretable latent space and inverse problem in deep generative models

Recent progress in deep generative models such as Generative Adversarial Networks (GANs) has enabled synthesizing photo-realistic images, such as faces and scenes. However, it remains much less…

From  Katie Gentilello on February 10th, 2021 4 plays 0  

Jia-Bin Huang - Bringing Visual Memories to Life

Photography allows us to capture and share memorable moments of our lives. However, 2D images appear flat due to the lack of depth perception and may suffer from poor imaging conditions such as…

From  Katie Gentilello on December 9th, 2020 9 plays 0  


Labs affiliated with the Machine Learning Center at Georgia Tech (ML@GT) will have the opportunity to share their research interests, work, and unique aspects of their lab in three minutes or less to…

From  Katie Gentilello on December 9th, 2020 13 plays 0  

Let's Talk About Bias and Diversity in Data, Software, and Institutions

Bias and lack of diversity have long been deep-rooted problems across industries. We discuss how these issues impact data, software, and institutions, and how we can improve moving forward.The panel…

From  Katie Gentilello on November 30th, 2020 8 plays 0  

Ankur Parikh - Towards High Precision Text Generation

Despite large advances in neural text generation in terms of fluency, existing generation techniques are prone to hallucination and often produce output that is unfaithful or irrelevant to the source…

From  Katie Gentilello on November 18th, 2020 11 plays 0  

Applying Emerging Technologies In Service of Journalism at The New York Times

Emerging technologies, particularly within computer vision, photogrammetry, and spatial computing, are unlocking new forms of storytelling for journalists to help people understand the world around…

From  Katie Gentilello on November 5th, 2020 13 plays 0  

Adriana Kovashka - Reasoning about Complex Media from Weak Multi-modal Supervision

In a world of abundant information targeting multiple senses, and increasingly powerful media, we need new mechanisms to model content. Techniques for representing individual channels, such as visual…

From  Katie Gentilello on October 30th, 2020 4 plays 0  

Robert Nowak - Active Learning: From Linear Classifiers to Overparameterized Neural Networks

The field of Machine Learning (ML) has advanced considerably in recent years, but mostly in well-defined domains using huge amounts of human-labeled training data. Machines can recognize objects in…

From  Katie Gentilello on October 12th, 2020 13 plays 0  

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  Katie Gentilello on September 10th, 2020 4 plays 0  

How to Configure DANTE Network on Netgear 4300 Series Managed Switch

A quick demonstration on how to configure DANTE traffic to flow correctly in Netgear 4300 Switch. By default DANTE is not configured.

From  Chris Robinson on June 3rd, 2020 6 plays 0  

Parlé Beamtracking Microphones with Marco Hendel

Tips and Understanding for designing rooms with Beam Tracking microphones.

From  Chris Robinson on May 26th, 2020 2 plays 0  

Biamp Lecture - Room Acoustics for Designers

For Room Designers, Installers, and Audio technicians

From  Chris Robinson on May 26th, 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  Katie Gentilello on March 13th, 2020 19 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  Katie Gentilello on February 18th, 2020 34 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  Katie Gentilello on January 21st, 2020 8 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  Katie Gentilello on December 4th, 2019 16 plays 0