Search Results - "Dasari, Venkat"

Virtual and Augmented Reality Applications to Support Data Analysis and Assessment of Science and Engineering by Su, Simon, Perry, Vince, Bravo, Luis, Kase, Sue, Roy, Heather, Cox, Katherine, R. Dasari, Venkat

“…For decades, virtual reality (VR) and augmented reality (AR) technologies have remained absent from science and engineering workflows due to the custom-built…”
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Private and rateless adaptive coded matrix-vector multiplication by Bitar, Rawad, Xing, Yuxuan, Keshtkarjahromi, Yasaman, Dasari, Venkat, El Rouayheb, Salim, Seferoglu, Hulya

“…Edge computing is emerging as a new paradigm to allow processing data near the edge of the network, where the data is typically generated and collected. This…”
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Complexity and mission computability of adaptive computing systems by Dasari, Venkat R, Im, Mee Seong, Geerhart, Billy

“…There is a subset of computational problems that existing algorithms may not complete due to a lack of adequate computational resources on tactical edge…”
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Game Theory in Mobile CrowdSensing:A Comprehensive Survey by Dasari, Venkat Surya, Kantarci, Burak, Pouryazdan, Maryam, Foschini, Luca, Girolami, Michele

“…Mobile CrowdSensing (MCS) is an emerging paradigm in the distributed acquisition of smart city and Internet of Things (IoT) data. MCS requires large number of…”
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Programmable control plane for mission critical wireless networks by Dasari, Venkat R, Jalaian, Brian, Bhat, Saleil

“…The control plane is an essential element to manage the data plane communications in wired and wireless networks. In a traditional network architecture, the…”
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OpenFlow arbitrated programmable network channels for managing quantum metadata by Dasari, Venkat R, Humble, Travis S

“…Quantum networks must classically exchange complex metadata between devices in order to carry out information for protocols such as teleportation, super-dense…”
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The Case for Robust Adaptation: Autonomic Resource Management is a Vulnerability by Noor, Joseph, Ali-Eldin, Ahmed, Garcia, Luis, Rao, Chirag, Dasari, Venkat R., Ganesan, Deepak, Jalaian, Brian, Shenoy, Prashant, Srivastava, Mani

“…Autonomic resource management for distributed edge computing systems provides an effective means of enabling dynamic placement and adaptation in the face of…”
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E2CM: Early Exit via Class Means for Efficient Supervised and Unsupervised Learning by Gormez, Alperen, Dasari, Venkat R., Koyuncu, Erdem

“…State-of-the-art neural networks with early exit mechanisms often need considerable amount of training and fine tuning to achieve good performance with low…”
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Deep learning acceleration at the resource-constrained tactical edge by Geerhart, Billy, Dasari, Venkat R., Wang, Peng, Rapp, Brian

“…This paper outlines how we modified the torch2trt library which allowed us to build a recursive framework that can quantize previously unsupported PyTorch…”
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Model-Distributed DNN Training for Memory-Constrained Edge Computing Devices by Li, Pengzhen, Seferoglu, Hulya, Dasari, Venkat R., Koyuncu, Erdem

“…We consider a model-distributed learning framework in which layers of a deep learning model is distributed across multiple workers. To achieve consistent…”
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Trustworthiness and Comfort-Aware Participant Recruitment for Mobile Crowd-Sensing in Smart Environments by Dasari, Venkat Surya, Kantarci, Burak, Simsek, Murat

“…Mobile crowd-sensing (MCS) has gained significant momentum in recent years for sensory data acquisition through non-dedicated sensors. Even though most of the…”
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Adaptive Distributed Stochastic Gradient Descent for Minimizing Delay in the Presence of Stragglers by Hanna, Serge Kas, Bitar, Rawad, Parag, Parimal, Dasari, Venkat, El Rouayheb, Salim

“…We consider the setting where a master wants to run a distributed stochastic gradient descent (SGD) algorithm on n workers each having a subset of the data…”
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On the integration of SIC and MIMO DoF for interference cancellation in wireless networks by Jalaian, Brian A., Yuan, Xu, Shi, Yi, Hou, Y. Thomas, Lou, Wenjing, Midkiff, Scott F., Dasari, Venkat

“…Recent advances in MIMO degree-of-freedom (DoF) models allowed MIMO research to penetrate the networking community. Independent from MIMO, successive…”
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Real Time Vehicle Tracking using YOLO Algorithm by Naresh, Seeramreddy Sai Pavan, Talasu, Ritesh, Venkat, Dasari Sri Sai Phani, Korada, Sravan Kumar, Mohanta, Bhabendu Kumar

“…In this research work, we aim to implement a real-time vehicle-detecting system using the YOLO algorithm. The system processes images and videos to identify…”
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GENI Deployment and Research at US Army Research Laboratory by Mishra, Vinod K., Dasari, Venkat R.

“…Global Environment for Network Innovation (GENI) is a comprehensive test bed technology to promote rapid network research and application development. It…”
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Computational complexity reduction of deep neural networks by Im, Mee Seong, Dasari, Venkat R

“…Mathematica Militaris, 25 (2022), no. 1, 1-10 Deep neural networks (DNN) have been widely used and play a major role in the field of computer vision and…”
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Participant Comfort Adaptation in Dependable Mobile Crowdsensing Services by Dasari, Venkat Surya, Simsek, Murat, Kantarci, Burak

“…Mobile Crowdsensing (MCS) is a ubiquitous sensing concept under the Internet of Things (IoT) ecosystem where builtin sensors in smart mobile devices are…”
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E$^2$CM: Early Exit via Class Means for Efficient Supervised and Unsupervised Learning by Görmez, Alperen, Dasari, Venkat R, Koyuncu, Erdem

“…State-of-the-art neural networks with early exit mechanisms often need considerable amount of training and fine tuning to achieve good performance with low…”
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Genetic optimization algorithms applied toward mission computability models by Im, Mee Seong, Dasari, Venkat R

“…Genetic algorithms are modeled after the biological evolutionary processes that use natural selection to select the best species to survive. They are…”
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A Transformer Approach for Camera-to-LIDAR Data Registration by Wang, Ju, Tang, Yong, Dasari, Venkat R., Geerhart, Billy, Rapp, Brian, Wang, Peng, Chen, Wei-Bang, Watts, Isaac

“…We proposes a novel method for camera-to-LIDAR calibration, which estimates the relative transform from LIDAR to camera sensors during on-field run-time…”
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