Meet ML@GT: Ian Stewart Encourages People to Make Mistakes When Studying Natural Language Processing

The Machine Learning Center at Georgia Tech (ML@GT) is home to many talented students from across campus, representing all six of Georgia Tech’s colleges and the Georgia Tech Research Institute (GTRI). These students have diverse backgrounds and a wide variety of interests both inside and outside of the classroom. Today, we’d like you to meet Ian Stewart, a … Continue reading Meet ML@GT: Ian Stewart Encourages People to Make Mistakes When Studying Natural Language Processing

Georgia Tech Researchers Presenting Work Virtually at Top AI Conference Due to COVID-19

Due to the rapid spread of coronavirus (COVID-19) and resulting travel restrictions, Georgia Tech students and faculty will now be presenting their research virtually at the International Conference on Learning Representations (ICLR), one of the biggest artificial intelligence (AI) conferences in the world, April 25 through 30. With 17 papers to present, researchers will create a … Continue reading Georgia Tech Researchers Presenting Work Virtually at Top AI Conference Due to COVID-19

Meet ML@GT: Lara J. Martin Trains AI Agents to Become Storytellers

The Machine Learning Center at Georgia Tech (ML@GT) is home to many talented students from across campus, representing all six of Georgia Tech’s colleges and the Georgia Tech Research Institute (GTRI). These students have diverse backgrounds and a wide variety of interests both inside and outside of the classroom. Today, we’d like you to meet Lara Martin, … Continue reading Meet ML@GT: Lara J. Martin Trains AI Agents to Become Storytellers

Working Towards Explainable and Data-efficient Machine Learning Models via Symbolic Reasoning

By Yuan Yang In recent years, we have experienced the success of modern machine learning (ML) models. Many of them have led to unprecedented breakthroughs in a wide range of applications, such as AlphaGo beating a world champion human player or the introduction of autonomous vehicles. There has been a continuous effort, both from industry … Continue reading Working Towards Explainable and Data-efficient Machine Learning Models via Symbolic Reasoning

Explaining Machine Learning Models for Natural Language

By Sarah Wiegreffe and Yuval Pinter Natural language processing (NLP) is the study of how computers learn to represent and make decisions about human communication in the form of written text. This encompasses many tasks, including automatically classifying documents, using machines to translate between languages, or designing algorithms for writing creative stories.  Many state-of-the-art systems … Continue reading Explaining Machine Learning Models for Natural Language

Meet ML@GT: Cusuh Ham, a World Traveler Focused on Understanding Uncertainty in Machine Learning

The Machine Learning Center at Georgia Tech (ML@GT) is home to many talented students from across campus, representing all six of Georgia Tech’s colleges and the Georgia Tech Research Institute (GTRI). These students have diverse backgrounds and a wide variety of interests both inside and outside of the classroom. Today, we’d like you to meet Cusuh Ham, … Continue reading Meet ML@GT: Cusuh Ham, a World Traveler Focused on Understanding Uncertainty in Machine Learning

Escaping Saddle Points Faster with Stochastic Momentum

By Jun-Kun Wang, Chi-Heng Lin, and Jacob Abernethy SGD with stochastic momentum (see Figure 1 below) has been the de facto training algorithm in nonconvex optimization and deep learning. It has been widely adopted for training neural nets in various applications. Modern techniques in computer vision (e.g.[1,2]), speech recognition (e.g. [3]), natural language processing (e.g. … Continue reading Escaping Saddle Points Faster with Stochastic Momentum