67 citations · 238 across the 29 of their papers we have counts for
7 papers · 1 filter
Location Estimation and Detection in Wireless Sensor Networks in the Presence of Fading
Xue Zhang, Cihan Tepedelenlioglu, Mahesh K. Banavar +2
In this paper, localization using narrowband communication signals are considered in the presence of fading channels with time of arrival measurements. When narrowband signals are…
Designing an Effective Metric Learning Pipeline for Speaker Diarization
Vivek Sivaraman Narayanaswamy, Jayaraman J. Thiagarajan, Huan Song +1
State-of-the-art speaker diarization systems utilize knowledge from external data, in the form of a pre-trained distance metric, to effectively determine relative speaker identitie…
A Regularized Attention Mechanism for Graph Attention Networks
Uday Shankar Shanthamallu, Jayaraman J. Thiagarajan, Andreas Spanias
Machine learning models that can exploit the inherent structure in data have gained prominence. In particular, there is a surge in deep learning solutions for graph-structured data…
GrAMME: Semi-Supervised Learning using Multi-layered Graph Attention Models
Uday Shankar Shanthamallu, Jayaraman J. Thiagarajan, Huan Song +1
Modern data analysis pipelines are becoming increasingly complex due to the presence of multi-view information sources. While graphs are effective in modeling complex relationships…
Coverage-Based Designs Improve Sample Mining and Hyper-Parameter Optimization
Gowtham Muniraju, Bhavya Kailkhura, Jayaraman J. Thiagarajan +3
Sampling one or more effective solutions from large search spaces is a recurring idea in machine learning, and sequential optimization has become a popular solution. Typical exampl…
Triplet Network with Attention for Speaker Diarization
Huan Song, Megan Willi, Jayaraman J. Thiagarajan +2
In automatic speech processing systems, speaker diarization is a crucial front-end component to separate segments from different speakers. Inspired by the recent success of deep ne…
Consensus-based Distributed Quantile Estimation in Sensor Networks
Jongmin Lee, Cihan Tepedelenlioglu, Andreas Spanias
A quantile is defined as a value below which random draws from a given distribution falls with a given probability. In a centralized setting where the cumulative distribution funct…