58 citations · 166 across the 14 of their papers we have counts for
14 papers
Efficient Implementation of Multi-sensor Adaptive Birth Samplers for Labeled Random Finite Set Tracking
Jennifer Bondarchuk, Anthony Trezza, Donald J. Bucci
Adaptive track initiation remains a crucial component of many modern multi-target tracking systems. For labeled random finite sets multi-object filters, prior work has been establi…
Transferability of Convolutional Neural Networks in Stationary Learning Tasks
Damian Owerko, Charilaos I. Kanatsoulis, Jennifer Bondarchuk +2
Recent advances in hardware and big data acquisition have accelerated the development of deep learning techniques. For an extended period of time, increasing the model complexity h…
Deterministic Multi-sensor Measurement-adaptive Birth using Labeled Random Finite Sets
Jennifer Bondarchuk, Anthony Trezza, Donald J. Bucci
Measurement-adaptive track initiation remains a critical design requirement of many practical multi-target tracking systems. For labeled random finite sets multi-object filters, pr…
On Gibbs Sampling Architecture for Labeled Random Finite Sets Multi-Object Tracking
Anthony Trezza, Donald J. Bucci, Pramod K. Varshney
Gibbs sampling is one of the most popular Markov chain Monte Carlo algorithms because of its simplicity, scalability, and wide applicability within many fields of statistics, scien…
Multi-Target Tracking with Transferable Convolutional Neural Networks
Damian Owerko, Charilaos I. Kanatsoulis, Jennifer Bondarchuk +2
Multi-target tracking (MTT) is a classical signal processing task, where the goal is to estimate the states of an unknown number of moving targets from noisy sensor measurements. I…
Multi-sensor Joint Adaptive Birth Sampler for Labeled Random Finite Set Tracking
Anthony Trezza, Donald J. Bucci, Pramod K. Varshney
This paper provides a scalable, multi-sensor measurement adaptive track initiation technique for labeled random finite set filters. A naive construction of the multi-sensor measure…
Decentralized Gaussian Filters for Cooperative Self-localization and Multi-target Tracking
Pranay Sharma, Augustin-Alexandru Saucan, Donald J. Bucci +1
Scalable and decentralized algorithms for Cooperative Self-localization (CS) of agents, and Multi-Target Tracking (MTT) are important in many applications. In this work, we address…
Robust Stochastic Bandit Algorithms under Probabilistic Unbounded Adversarial Attack
Ziwei Guan, Kaiyi Ji, Donald J Bucci +4
The multi-armed bandit formalism has been extensively studied under various attack models, in which an adversary can modify the reward revealed to the player. Previous studies focu…
On Distributed Online Convex Optimization with Sublinear Dynamic Regret and Fit
Pranay Sharma, Prashant Khanduri, Lixin Shen +2
In this work, we consider a distributed online convex optimization problem, with time-varying (potentially adversarial) constraints. A set of nodes, jointly aim to minimize a globa…
Decentralized Multi-target Tracking in Urban Environments: Overview and Challenges
Donald J. Bucci, Pramod K. Varshney
In multi-target tracking, sensor control involves dynamically configuring sensors to achieve improved tracking performance. Many of these techniques focus on sensors with memoryles…
Obstructed Target Tracking in Urban Environments
Christopher Berry, Donald J. Bucci
Accurate tracking in urban environments necessitates target birth, survival, and detection models that quantify the impact of terrain and building geometry on the sequential estima…
Passive Multi-Target Tracking Using the Adaptive Birth Intensity PHD Filter
Christopher Berry, Donald J. Bucci, Samuel W. Schmidt
Passive multi-target tracking applications require the integration of multiple spatially distributed sensor measurements to distinguish true tracks from ghost tracks. A popular mul…
K-medoids Clustering of Data Sequences with Composite Distributions
Tiexing Wang, Qunwei Li, Donald J. Bucci +3
This paper studies clustering of data sequences using the k-medoids algorithm. All the data sequences are assumed to be generated from \emph{unknown} continuous distributions, whic…
Nonparametric Composite Hypothesis Testing in an Asymptotic Regime
Qunwei Li, Tiexing Wang, Donald J. Bucci +3
We investigate the nonparametric, composite hypothesis testing problem for arbitrary unknown distributions in the asymptotic regime where both the sample size and the number of hyp…