406 citations · 3.1k across the 87 of their papers we have counts for
8 papers · 1 filter
CDSA: Cross-Dimensional Self-Attention for Multivariate, Geo-tagged Time Series Imputation
Jiawei Ma, Zheng Shou, Alireza Zareian +3
Many real-world applications involve multivariate, geo-tagged time series data: at each location, multiple sensors record corresponding measurements. For example, air quality monit…
Low-shot Learning via Covariance-Preserving Adversarial Augmentation Networks
Hang Gao, Zheng Shou, Alireza Zareian +2
Deep neural networks suffer from over-fitting and catastrophic forgetting when trained with small data. One natural remedy for this problem is data augmentation, which has been rec…
Heated-Up Softmax Embedding
Xu Zhang, Felix Xinnan Yu, Svebor Karaman +2
Metric learning aims at learning a distance which is consistent with the semantic meaning of the samples. The problem is generally solved by learning an embedding for each sample s…
Multimodal Social Media Analysis for Gang Violence Prevention
Philipp Blandfort, Desmond Patton, William R. Frey +9
Gang violence is a severe issue in major cities across the U.S. and recent studies [Patton et al. 2017] have found evidence of social media communications that can be linked to suc…
Learning to Hash for Indexing Big Data - A Survey
Jun Wang, Wei Liu, Sanjiv Kumar +1
The explosive growth in big data has attracted much attention in designing efficient indexing and search methods recently. In many critical applications such as large-scale search…
SVM for learning with label proportions
Felix X. Yu, Dong Liu, Sanjiv Kumar +2
We study the problem of learning with label proportions in which the training data is provided in groups and only the proportion of each class in each group is known. We propose a…
On the Difficulty of Nearest Neighbor Search
Junfeng He, Sanjiv Kumar, Shih-Fu Chang
Fast approximate nearest neighbor (NN) search in large databases is becoming popular. Several powerful learning-based formulations have been proposed recently. However, not much at…
Compact Hyperplane Hashing with Bilinear Functions
Wei Liu, Jun Wang, Yadong Mu +2
Hyperplane hashing aims at rapidly searching nearest points to a hyperplane, and has shown practical impact in scaling up active learning with SVMs. Unfortunately, the existing ran…