Search for tag: "ml@gt seminar series"

AI Information Session - Anna Almejo, Mason Bretan

In this talk, we will cover general info about Samsung Research America and more specifically the research and projects happening within the Artificial Intelligence team including personal…

From  Kathryn Gentilello 6 Months ago 20 views 0  

An overview of deep learning frameworks and an introduction to PyTorch - Soumith Chintala

In this talk, you will get an exposure to the various types of deep learning frameworks – declarative and imperative frameworks such as TensorFlow and PyTorch. After a broad overview of…

From  Kathryn Gentilello A year ago 288 views 0  

Asynchronous (Sub)gradient-Push - Mike Rabbat

We consider a multi-agent framework for distributed optimization where each agent in the network has access to a local convex function and the collective goal is to achieve consensus on…

From  Kathryn Gentilello 7 Months ago 4 views 0  

Bryan McCann - The Natural Language Decathlon: Multitask Learning as Question Answering

Deep learning has improved performance on many natural language processing (NLP) tasks individually. However, general NLP models cannot emerge within a paradigm that focuses on the particularities of…

From  Kathryn Gentilello 2 Months ago 62 views 0  

Data-Driven Dialogue Systems: Models, Algorithms, Evaluation, and Ethical Challenges - Joelle Pineau

The use of dialogue systems as a medium for human-machine interaction is an increasingly prevalent paradigm. A growing number of dialogue systems use conversation strategies that are learned from…

From  Kathryn Gentilello 8 Months ago 45 views 0  

Deep Learning to Learn - Pieter Abbeel

Reinforcement learning and imitation learning have seen success in many domains, including autonomous helicopter flight, Atari, simulated locomotion, Go, robotic manipulation. However, sample…

From  Kathryn Gentilello 2 Months ago 145 views 0  

Deep Networks for Pixel Level Inference with Applications to Medical Imaging - Sumit Chopra

https://mediaspace.gatech.edu/media/chopra/1_73x1u7b4

From  Kathryn Gentilello A year ago 42 views 0  

Do GANs actually learn the distribution? - Sanjeev Arora

Generative Adversarial Nets (GANs) is a framework for training deep generative models, due to Goodfellow et al'13. It involves a competition between a generator net that tries to produce…

From  Kathryn Gentilello 8 Months ago 94 views 0  

Ella Atkins - Data-to-Decisions for Safe Autonomous Flight

Traditional sensor data can be augmented with new data sources such as roadmaps and geographical information system (GIS) Lidar/video to offer emerging unmanned aircraft systems (UAS) and urban air…

From  Kathryn Gentilello 3 Days ago 9 views 0  

Extreme scale matrix factorizations in Exploration Seismology - Felix Herrmann

We will present some recent work on matrix factorizations with applications that range from full-azimuth seismic data processing w/ coil acquisition to seismic data compression & recovery w/…

From  Kathryn Gentilello 6 Months ago 15 views 0  

Gregory Diamos - Reaching Beyond Human Accuracy With AI Datacenters

Deep learning has enabled rapid progress in diverse problems in vision, speech, healthcare, and beyond. This progress has been driven by breakthroughs in algorithms that can harness massive datasets…

From  Kathryn Gentilello A month ago 6 views 0  

Hugo Larochelle - Few-shot Learning with Meta-Learning: Progress Made and Challenges Ahead

A lot of the recent progress on many AI tasks enabled in part by the availability of large quantities of labeled data. Yet, humans are able to learn concepts from as little as a handful of examples.…

From  Kathryn Gentilello 3 Weeks ago 86 views 0  

Pruning Deep Neural Networks with Net-Trim: Deep Learning and Compressed Sensing Meet - Alireza Aghasi

We introduce and analyze a new technique for model reduction in deep neural networks. Our algorithm prunes (sparsifies) a trained network layer-wise, removing connections at each layer by addressing…

From  Kathryn Gentilello 7 Months ago 267 views 0  

Sum-Product Networks: The Next Generation of Deep Models - Pedro Domingos

The two main types of deep learning are function approximation and probability estimation. Function approximators like convolutional neural networks are robust and allow for real-time inference, but…

From  Kathryn Gentilello A year ago 179 views 0  

TF-Slim: A Lightweight Library for Defining, Training and Evaluating Complex Models in TensorFlow - Nathan Silberman

TF-Slim is a TensorFlow-based library with various components. These include modules for easily defining neural network models with few lines of code, routines for training and evaluating such models…

From  Kathryn Gentilello A year ago 292 views 0  

The New Machine Learning Center at GA Tech: Plans and Aspirations - Irfan Essa

The Interdisciplinary Research Center (IRC) for Machine Learning at Georgia Tech (ML@GT) was established in Summer 2016 to foster research and academic activities in and around the discipline of…

From  Kathryn Gentilello A year ago 64 views 0