728 citations · 1.7k across the 39 of their papers we have counts for
9 papers · 1 filter
Image-to-GPS Verification Through A Bottom-Up Pattern Matching Network
Jiaxin Cheng, Yue Wu, Wael Abd-Almageed +1
The image-to-GPS verification problem asks whether a given image is taken at a claimed GPS location. In this paper, we treat it as an image verification problem -- whether a query…
Policy Design for Active Sequential Hypothesis Testing using Deep Learning
Dhruva Kartik, Ekraam Sabir, Urbashi Mitra +1
Information theory has been very successful in obtaining performance limits for various problems such as communication, compression and hypothesis testing. Likewise, stochastic con…
Unsupervised Adversarial Invariance
Ayush Jaiswal, Yue Wu, Wael AbdAlmageed +1
Data representations that contain all the information about target variables but are invariant to nuisance factors benefit supervised learning algorithms by preventing them from le…
A Byte-sized Approach to Named Entity Recognition
Emily Sheng, Prem Natarajan
In biomedical literature, it is common for entity boundaries to not align with word boundaries. Therefore, effective identification of entity spans requires approaches capable of c…
Deep Multimodal Image-Repurposing Detection
Ekraam Sabir, Wael AbdAlmageed, Yue Wu +1
Nefarious actors on social media and other platforms often spread rumors and falsehoods through images whose metadata (e.g., captions) have been modified to provide visual substant…
Learn to Combine Modalities in Multimodal Deep Learning
Kuan Liu, Yanen Li, Ning Xu +1
Combining complementary information from multiple modalities is intuitively appealing for improving the performance of learning-based approaches. However, it is challenging to full…
A Sequential Embedding Approach for Item Recommendation with Heterogeneous Attributes
Kuan Liu, Xing Shi, Prem Natarajan
Attributes, such as metadata and profile, carry useful information which in principle can help improve accuracy in recommender systems. However, existing approaches have difficulty…
Implicit Language Model in LSTM for OCR
Ekraam Sabir, Stephen Rawls, Prem Natarajan
Neural networks have become the technique of choice for OCR, but many aspects of how and why they deliver superior performance are still unknown. One key difference between current…
CapsuleGAN: Generative Adversarial Capsule Network
Ayush Jaiswal, Wael AbdAlmageed, Yue Wu +1
We present Generative Adversarial Capsule Network (CapsuleGAN), a framework that uses capsule networks (CapsNets) instead of the standard convolutional neural networks (CNNs) as di…