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Semantic representation learning for discourse processing
(Georgia Institute of Technology, 2016-07-21)
Discourse processing is to identify coherent relations, such as contrast and causal relation, from well-organized texts. The outcomes from discourse processing can benefit both research and applications in natural language ...
Doctor AI: Interpretable deep learning for modeling electronic health records
(Georgia Institute of Technology, 2018-05-23)
Deep learning recently has been showing superior performance in complex domains such as computer vision, audio processing and natural language processing compared to traditional statistical methods. Naturally, deep learning ...
Manipulating state space distributions for sample-efficient imitation-learning
(Georgia Institute of Technology, 2020-03-16)
Imitation learning has emerged as one of the most effective approaches to train agents to act intelligently in unstructured and unknown domains. On its own or in combination with reinforcement learning, it enables agents ...
Large scale machine learning for geospatial problems in computational sustainability
(Georgia Institute of Technology, 2020-05-14)
The UN laid out 17 Sustainable Development Goals as part of the “The 2030 Agenda for Sustainable Development”. Each goal consists of broad targets - such as increasing the percentage of forested land (indicator 15.1.1) - ...
Deep representation learning on hypersphere
(Georgia Institute of Technology, 2020-07-27)
How to efficiently learn discriminative deep features is arguably one of the core problems in deep learning, since it can benefit a lot of downstream tasks such as visual recognition, object detection, semantic segmentation, ...
Learning dynamic processes over graphs
(Georgia Institute of Technology, 2020-07-09)
Graphs appear as a versatile representation of information across domains spanning social networks, biological networks, transportation networks, molecular structures, knowledge networks, web information network and many ...
Deep-learning for automated diatom detection and identification for the ecological diagnosis of fresh-water environments
(Georgia Institute of Technology, 2020-07-29)
Diatoms are a type of unicellular microalgae found in all aquatic environments. Their great diversity and ubiquity make these organisms recognized bio-indicators for monitoring the ecological status of watercourses, notably ...
Algorithms and analysis for non-convex optimization problems in machine learning
(Georgia Institute of Technology, 2017-05-10)
In this thesis, we propose efficient algorithms and provide theoretical analysis through the angle of spectral methods for some important non-convex optimization problems in machine learning. Specifically, we focus on two ...
Learning neural algorithms with graph structures
(Georgia Institute of Technology, 2020-01-13)
Graph structures, like syntax trees, social networks, and programs, are ubiquitous in many real world applications including knowledge graph inference, chemistry and social network analysis. Over the past several decades, ...
Visually grounded language understanding and generation
(Georgia Institute of Technology, 2020-01-13)
The world around us involves multiple modalities -- we see objects, feel texture, hear sounds, smell odors and so on. In order for Artificial Intelligence (AI) to make progress in understanding the world around us, it needs ...