Learning Multi-Modal Biomarker Representations via Globally Aligned Longitudinal Enrichments
نویسندگان
چکیده
منابع مشابه
High-order Deep Neural Networks for Learning Multi-Modal Representations
In multi-modal learning, data consists of multiple modalities, which need to be represented jointly to capture the real-world ’concept’ that the data corresponds to (Srivastava & Salakhutdinov, 2012). However, it is not easy to obtain the joint representations reflecting the structure of multi-modal data with machine learning algorithms, especially with conventional neural networks. This is bec...
متن کاملMulti-Modal Representations for Improved Bilingual Lexicon Learning
Recent work has revealed the potential of using visual representations for bilingual lexicon learning (BLL). Such image-based BLL methods, however, still fall short of linguistic approaches. In this paper, we propose a simple yet effective multimodal approach that learns bilingual semantic representations that fuse linguistic and visual input. These new bilingual multi-modal embeddings display ...
متن کاملLearning Multi-modal Similarity
In many applications involving multi-media data, the definition of similarity between items is integral to several key tasks, e.g., nearest-neighbor retrieval, classification, and recommendation. Data in such regimes typically exhibits multiple modalities, such as acoustic and visual content of video. Integrating such heterogeneous data to form a holistic similarity space is therefore a key cha...
متن کاملLearning Multi-modal Control Programs
Multi-modal control is a commonly used design tool for breaking up complex control tasks into sequences of simpler tasks. In this paper, we show that by viewing the control space as a set of such tokenized instructions rather than as real-valued signals, reinforcement learning becomes applicable to continuous-time control systems. In fact, we show how a combination of state-space exploration an...
متن کاملMulti-Modal Distance Metric Learning
Multi-modal data is dramatically increasing with the fast growth of social media. Learning a good distance measure for data with multiple modalities is of vital importance for many applications, including retrieval, clustering, classification and recommendation. In this paper, we propose an effective and scalable multi-modal distance metric learning framework. Based on the multi-wing harmonium ...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Proceedings of the AAAI Conference on Artificial Intelligence
سال: 2020
ISSN: 2374-3468,2159-5399
DOI: 10.1609/aaai.v34i01.5426