9 citations · 17 across the 5 of their papers we have counts for
10 papers
Supervised Homogeneity Fusion: a Combinatorial Approach
Wen Wang, Shihao Wu, Ziwei Zhu +2
Fusing regression coefficients into homogenous groups can unveil those coefficients that share a common value within each group. Such groupwise homogeneity reduces the intrinsic di…
Parallel-and-stream accelerator for computationally fast supervised learning
Emily C. Hector, Lan Luo, Peter X. -K. Song
Two dominant distributed computing strategies have emerged to overcome the computational bottleneck of supervised learning with big data: parallel data processing in the MapReduce…
Data Discovery Using Lossless Compression-Based Sparse Representation
Elyas Sabeti, Peter X. K. Song, Alfred O. Hero
Sparse representation has been widely used in data compression, signal and image denoising, dimensionality reduction and computer vision. While overcomplete dictionaries are requir…
Adaptive multi-channel event segmentation and feature extraction for monitoring health outcomes
Xichen She, Yaya Zhai, Ricardo Henao +5
: To develop a multi-channel device event segmentation and feature extraction algorithm that is robust to changes in data distribution. : We i…
Doubly Distributed Supervised Learning and Inference with High-Dimensional Correlated Outcomes
Emily C. Hector, Peter X. -K. Song
This paper presents a unified framework for supervised learning and inference procedures using the divide-and-conquer approach for high-dimensional correlated outcomes. We propose…
Pattern-Based Analysis of Time Series: Estimation
Elyas Sabeti, Peter X. K. Song, Alfred O. Hero
While Internet of Things (IoT) devices and sensors create continuous streams of information, Big Data infrastructures are deemed to handle the influx of data in real-time. One type…