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Rejection of Workers with Heterogeneous (Mismatched) Data in Federated Learning *
ICASSP 2025 - 2025 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)
Year: 2025 | Conference Paper |
Federated learning (FL) has attracted great attention lately due to many advantages it provides. The community has noted that FL performance can be greatly degraded by heterogeneous data or any data that is unsuitable for the learning problem under consideration. Here we focus on the gradient descent and heavy ball algorithms in a worker-server architecture and describe a simple but effective appr...Show More
Regret and Belief Complexity Tradeoff in Gaussian Process Bandits via Information Thresholding
Amrit Singh Bedi;Dheeraj Peddireddy;Vaneet Aggarwal;Brian M. Sadler;Alec Koppel
Bayesian optimization is a powerful framework for global search, using maximum a posteriori updates instead of simulated annealing. We cast it as a multiarmed bandit problem with a Gaussian process (GP) for the payoff function. Action selections rely on upper confidence bound (UCB) or expected improvement (EI). Prior works with GPs faced challenges for large iteration horizons ($T$) due to cubic s...Show More
Robust Stochastic Shortest-Path Planning via Risk-Sensitive Incremental Sampling*
Clinton Enwerem;Erfaun Noorani;John S. Baras;Brian M. Sadler
2024 IEEE 63rd Conference on Decision and Control (CDC)
Year: 2024 | Conference Paper |
With the pervasiveness of Stochastic Shortest-Path (SSP) problems in high-risk industries, such as last-mile autonomous delivery and supply chain management, robust planning algorithms are crucial for ensuring successful task completion while mitigating hazardous outcomes. Mainstream chance-constrained incremental sampling techniques for solving SSP problems tend to be overly conservative and typi...Show More
Deceptive Planning for Resource Allocation
Shenghui Chen;Yagiz Savas;Mustafa O. Karabag;Brian M. Sadler;Ufuk Topcu
We consider a team of autonomous agents that navigate in an adversarial environment and aim to achieve a task by allocating their resources over a set of target locations. An adversary in the environment observes the autonomous team's behavior to infer their objective and responds against the team. In this setting, we propose strategies for controlling the density of the autonomous team so that th...Show More
An Invitation to Hypercomplex Phase Retrieval: Theory and applications
Roman Jacome;Kumar Vijay Mishra;Brian M. Sadler;Henry Arguello
IEEE Signal Processing Magazine
Cited by: Papers (3)
Hypercomplex signal processing (HSP) provides state-of-the-art tools to handle multidimensional signals by harnessing the intrinsic correlation of the signal dimensions through Clifford algebra. Recently, the hypercomplex representation of the phase retrieval (PR) problem, wherein a complex-valued signal is estimated through its intensity-only projections, has attracted significant interest. The h...Show More
Dual-Blind Deconvolution in ISAC Receiver Using Multi-Dimensional Beurling-Selberg Functions
Jonathan Monsalve;Edwin Vargas;Kumar Vijay Mishra;Brian M. Sadler;Henry Arguello
2024 IEEE Radar Conference (RadarConf24)
Year: 2024 | Conference Paper |
Recent interest in integrated sensing and communications (ISAC) systems has led to the development of innovative signal processing techniques to extract information from a shared radar-communications spectrum setup. We focus on a dual-blind deconvolution (DBD) problem, where the ISAC receiver admits a multi-carrier wireless communications signal overlaid with the radar signal reflected off multipl...Show More
Signal processing over hypercomplex numbers arises in many optical imaging applications. In particular, spectral image or color stereo data are often processed using octonion algebra. Recently, the eight-band multispectral image phase recovery has gained salience, wherein it is desired to recover the eight bands from the phaseless measurements. In this letter, we tackle this hitherto unaddressed h...Show More
Multi-Antenna ISAC Receiver with n-Tuple Blind Deconvolution
Roman Jacome;Edwin Vargas;Kumar Vijay Mishra;Brian M. Sadler;Henry Arguello
ICASSP 2024 - 2024 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)
Year: 2024 | Conference Paper |
Recent developments in spectrum-sharing technologies include integrated sensing and communications (ISAC) systems to save resources, cost, and power. In this paper, we consider a co-existence topology with n-tuple radar and communications transmitters, wherein neither the transmitted signal nor the channels are known. Estimating these unknown quantities is modeled as a n-tuple blind deconvolution ...Show More
Low Frequency Multi-Robot Networking
Brian M. Sadler;Fikadu T. Dagefu;Jeffrey N. Twigg;Gunjan Verma;Predrag Spasojevic;Richard J. Kozick;Justin Kong
Autonomous teams of unmanned ground and air vehicles rely on networking and distributed processing to collaborate as they jointly localize, explore, map, and learn in sometimes difficult and adverse conditions. Co-designed intelligent wireless networks are needed for these autonomous mobile agents for applications including disaster response, logistics and transportation, supplementing cellular ne...Show More
Quickest Detection for Human-Sensor Systems Using Quantum Decision Theory
A sensor observes an underlying state of nature in noise, computes a posterior probability of this state, and provides this posterior as a recommendation to a human decision-maker. The human then makes decisions based on this recommendation. By recording these human decisions over time, how can a quickest detector detect a change in the underlying state? This paper addresses the above human-sensor...Show More
Toward Scene Understanding with Depth and Object-Aware Clustering in Contested Environment
Manish Bhurtel;Yuba R. Siwakoti;Danda B. Rawat;Brian M. Sadler;John M. Fossaceca;Daniel O. Rice
2023 International Conference on Machine Learning and Applications (ICMLA)
Year: 2023 | Conference Paper |
Cited by: Papers (4)
Scene understanding in a contested battlefield is one of the very difficult tasks for detecting and identifying threats. In a complex battlefield, multiple autonomous robots for multi-domain operations are likely to track the activities of the same threat/objects leading to inefficient and redundant tasks. To address this problem, we propose a novel and effective object clustering framework that t...Show More
Factor Graph Processing for Dual-Blind Deconvolution at ISAC Receiver
Roman Jacome;Edwin Vargas;Kumar Vijay Mishra;Brian M. Sadler;Henry Arguello
2023 IEEE 9th International Workshop on Computational Advances in Multi-Sensor Adaptive Processing (CAMSAP)
Year: 2023 | Conference Paper |
Cited by: Papers (4)
Integrated sensing and communications (ISAC) systems have gained significant interest because of their ability to jointly and efficiently access, utilize, and manage the scarce electromagnetic spectrum. The co-existence approach toward ISAC focuses on the receiver processing of overlaid radar and communications signals coming from independent transmitters. A specific ISAC coexistence problem is du...Show More
Beurling-Selberg Extremization for Dual-Blind Deconvolution Recovery in Joint Radar-Communications
Jonathan Monsalve;Edwin Vargas;Kumar Vijay Mishra;Brian M. Sadler;Henry Arguello
2023 IEEE 9th International Workshop on Computational Advances in Multi-Sensor Adaptive Processing (CAMSAP)
Year: 2023 | Conference Paper |
Cited by: Papers (5)
Recent interest in integrated sensing and communications has led to the design of novel signal processing techniques to recover information from an overlaid radar-communications signal. Here, we focus on a spectral coexistence scenario, wherein the channels and transmit signals of both radar and communications systems are unknown to the common receiver. In this dual-blind deconvolution (DBD) probl...Show More
LLM-Planner: Few-Shot Grounded Planning for Embodied Agents with Large Language Models
Chan Hee Song;Brian M. Sadler;Jiaman Wu;Wei-Lun Chao;Clayton Washington;Yu Su
2023 IEEE/CVF International Conference on Computer Vision (ICCV)
Year: 2023 | Conference Paper |
Cited by: Papers (76)
This study focuses on using large language models (LLMs) as a planner for embodied agents that can follow natural language instructions to complete complex tasks in a visually-perceived environment. The high data cost and poor sample efficiency of existing methods hinders the development of versatile agents that are capable of many tasks and can learn new tasks quickly. In this work, we propose a ...Show More
Index-Modulated Metasurface Transceiver Design Using Reconfigurable Intelligent Surfaces for 6G Wireless Networks
John A. Hodge;Kumar Vijay Mishra;Brian M. Sadler;Amir I. Zaghloul
Higher spectral and energy efficiencies are the envisioned defining characteristics of high data-rate sixth-generation (6G) wireless networks. One of the enabling technologies to meet these requirements is index modulation (IM), which transmits information through permutations of indices of spatial, frequency, or temporal media. In this paper, we propose novel electromagnetics-compliant designs of...Show More
Calibration of Multi-Robot Coherent Beamforming
Mitchell J. Grabner;Fikadu T. Dagefu;Jeffrey N. Twigg;Babak Azimi-Sadjadi;Brian M. Sadler
2023 International Conference on Military Communications and Information Systems (ICMCIS)
Year: 2023 | Conference Paper |
Cited by: Papers (1)
In this paper, we develop and evaluate a calibration procedure for multi-robot unmanned ground vehicle (UGV) beamforming arrays operating in challenging non-line-of-sight (NLOS) scenarios. The proposed approach is open-loop, uni-directional, and location agnostic. It enables a beamforming array to employ the help of an auxiliary agent to perform the calibration. Location agnosticism in the calibra...Show More
Performance Metrics for Biomimetic Antenna Array (BMAA) Systems
2023 IEEE International Symposium on Antennas and Propagation and USNC-URSI Radio Science Meeting (USNC-URSI)
Year: 2023 | Conference Paper |
Cited by: Papers (3)
Biomimetic antenna array (BMAA) systems consist of antennas spaced by much less than one-half wavelength and an external coupling network (ECN) that matches the impedance of the antenna array with the measurement device. BMAAs with two antennas have been designed and fabricated during the past 12 years. The primary performance metric considered in past studies is the phase difference in the measur...Show More
A high peak-to-average power ratio (PAPR) is a major disadvantage of orthogonal frequency division multiplexing (OFDM) communications systems. In this letter, we present a graph-theoretic heuristic to mitigate high PAPR. In particular, we focus on searching for an optimal Gray-coded mapping to encode user messages such that minimum PAPR is obtained for a given message sequence in an $M$-ary quadra...Show More
Statistical Detection of Coordination in a Cognitive Radar Network through Inverse Multi-Objective Optimization
2023 26th International Conference on Information Fusion (FUSION)
Year: 2023 | Conference Paper |
Consider a target being tracked by a cognitive radar network. If the target can intercept noisy radar emissions, how can it detect coordination in the network? By ‘coordination’ we mean that the radar emissions satisfy Pareto optimality with respect to multi-objective optimization over the objective functions of each radar and a constraint on total network power output. This paper provides a novel...Show More
Dual-Blind Deconvolution for Overlaid Radar-Communications Systems
Edwin Vargas;Kumar Vijay Mishra;Roman Jacome;Brian M. Sadler;Henry Arguello
The increasingly crowded spectrum has spurred the design of joint radar-communications systems that share hardware resources and efficiently use the radio frequency spectrum. We study a general spectral coexistence scenario, wherein the channels and transmit signals of both radar and communications systems are unknown at the receiver. In this dual-blind deconvolution (DBD) problem, a common receiv...Show More
Identifying Coordination in a Cognitive Radar Network - A Multi-Objective Inverse Reinforcement Learning Approach
ICASSP 2023 - 2023 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)
Year: 2023 | Conference Paper |
Cited by: Papers (2)
Consider a target being tracked by a cognitive radar network. If the target can intercept some radar network emissions, how can it detect coordination among the radars? By 'coordination' we mean that the radar emissions satisfy Pareto optimality with respect to multiobjective optimization over each radar's utility. This paper provides a novel multi-objective inverse reinforcement learning approach...Show More
Unique Bispectrum Inversion for Signals with Finite Spectral/Temporal Support
ICASSP 2023 - 2023 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)
Year: 2023 | Conference Paper |
Retrieving a signal from its triple correlation spectrum, also called bispectrum, arises in a wide range of signal processing problems. Conventional methods do not provide an accurate inversion of bispectrum to the underlying signal. In this paper, we present an approach that uniquely recovers signals with finite spectral support (band-limited signals) from at least 3B measurements of its bispectr...Show More
Ensemble Deep Learning for Sustainable Multimodal UAV Classification
Unmanned aerial vehicles (UAVs) have increasingly shown to be useful in civilian applications (such as agriculture, public safety, surveillance) and mission critical military applications. Despite the growth in popularity and applications, UAVs have also been used for malicious purposes. In such instances, their timely detection and identification has garnished rising interest from government, ind...Show More
A Survey of Small, Low-Frequency Antennas: Recent designs, practical challenges, and research directions
Robust, secure, low-power wireless communications and networking are needed to support emerging applications in emergency and disaster response, robotics, autonomous vehicles, and the Internet of Things (IoT) in physically complex environments, such as indoor/outdoor, dense urban, and other challenging scenarios. These applications require a variety of wireless communications modalities, including...Show More
Adversarial Promotion for Video based Recommender Systems
2022 IEEE 4th International Conference on Cognitive Machine Intelligence (CogMI)
Year: 2022 | Conference Paper |
Cited by: Papers (1)
Short-form video content is fast to consume, easy to digest, and for most creators, inexpensive to make. Content Creators on Video Content platforms have a vested interest in having their videos appear as high as possible in recommendations that users are shown. This paper demonstrates how content creators can manipulate video content to adversarially promote their ranking in a recommendation mode...Show More
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