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2020 – today
- 2025
[j23]Nitika Sharma, Hari Shankar Singh, Rajesh Khanna, Amanpreet Kaur, Mayank Agarwal:
Design a metamaterial based applicator for hyperthermia cancer treatment. Biomed. Signal Process. Control. 99: 106826 (2025)- 2024
- [j22]Fawzia Omer Albasheer, Raghavendra Ramesh Haibatti
, Mayank Agarwal, Seung Yeob Nam:
A Novel IDS Based on Jaya Optimizer and Smote-ENN for Cyberattacks Detection. IEEE Access 12: 101506-101527 (2024) - [j21]Deepti Shakya, Vishal Deshpande, Mir Jafar Sadegh Safari, Mayank Agarwal:
Performance evaluation of machine learning algorithms for the prediction of particle Froude number (Frn) using hyper-parameter optimizations techniques. Expert Syst. Appl. 256: 124960 (2024) - [j20]Anmol Kumar, Gaurav Somani, Mayank Agarwal:
Comparing HAProxy Scheduling Algorithms During the DDoS Attacks. IEEE Netw. Lett. 6(2): 139-142 (2024) - [j19]Anmol Kumar, Mayank Agarwal:
Quick service during DDoS attacks in the container-based cloud environment. J. Netw. Comput. Appl. 229: 103946 (2024) - [j18]Prabhat Kumar Bharti, Tirthankar Ghosal, Mayank Agarwal, Asif Ekbal:
PEERRec: An AI-based approach to automatically generate recommendations and predict decisions in peer review. Int. J. Digit. Libr. 25(1): 55-72 (2024) - [j17]Prabhat Kumar Bharti, Meith Navlakha, Mayank Agarwal, Asif Ekbal:
PolitePEER: does peer review hurt? A dataset to gauge politeness intensity in the peer reviews. Lang. Resour. Evaluation 58(4): 1291-1313 (2024) - [j16]Prabhat Kumar Bharti, Mayank Agarwal, Asif Ekbal:
Please be polite to your peers: a multi-task model for assessing the tone and objectivity of critiques of peer review comments. Scientometrics 129(3): 1377-1413 (2024) - [j15]Neha Pramanick, Vatsal Singhal, Neeraj, Jimson Mathew, Mayank Agarwal:
Fusion of Wavelet Decomposition and N-BEATS for Improved Stock Market Forecasting. SN Comput. Sci. 5(7): 869 (2024) - [j14]Neha Pramanick, Shourya Srivastava, Jimson Mathew, Mayank Agarwal:
Enhanced IDS Using BBA and SMOTE-ENN for Imbalanced Data for Cybersecurity. SN Comput. Sci. 5(7): 875 (2024) - [c42]Lilian Ngweta, Mayank Agarwal, Subha Maity, Alex Gittens, Yuekai Sun, Mikhail Yurochkin:
Aligners: Decoupling LLMs and Alignment. EMNLP (Findings) 2024: 13785-13802 - [c41]Subha Maity, Mayank Agarwal, Mikhail Yurochkin, Yuekai Sun:
An Investigation of Representation and Allocation Harms in Contrastive Learning. ICLR 2024 - [c40]Lilian Ngweta, Mayank Agarwal, Subha Maity, Alex Gittens, Yuekai Sun, Mikhail Yurochkin:
Aligners: Decoupling LLMs and Alignment. Tiny Papers @ ICLR 2024 - [i25]Mayank Agarwal, Yikang Shen, Bailin Wang, Yoon Kim, Jie Chen:
Structured Code Representations Enable Data-Efficient Adaptation of Code Language Models. CoRR abs/2401.10716 (2024) - [i24]Lilian Ngweta, Mayank Agarwal, Subha Maity, Alex Gittens, Yuekai Sun, Mikhail Yurochkin:
Aligners: Decoupling LLMs and Alignment. CoRR abs/2403.04224 (2024) - [i23]Mayank Mishra, Matt Stallone, Gaoyuan Zhang, Yikang Shen, Aditya Prasad, Adriana Meza Soria, Michele Merler, Parameswaran Selvam, Saptha Surendran, Shivdeep Singh, Manish Sethi, Xuan-Hong Dang, Pengyuan Li, Kun-Lung Wu, Syed Zawad, Andrew Coleman, Matthew White, Mark Lewis, Raju Pavuluri, Yan Koyfman, Boris Lublinsky, Maximilien de Bayser, Ibrahim Abdelaziz, Kinjal Basu, Mayank Agarwal, Yi Zhou, Chris Johnson, Aanchal Goyal, Hima Patel, S. Yousaf Shah, Petros Zerfos, Heiko Ludwig, Asim Munawar, Maxwell Crouse, Pavan Kapanipathi, Shweta Salaria, Bob Calio, Sophia Wen, Seetharami Seelam, Brian Belgodere, Carlos A. Fonseca, Amith Singhee, Nirmit Desai, David D. Cox, Ruchir Puri, Rameswar Panda:
Granite Code Models: A Family of Open Foundation Models for Code Intelligence. CoRR abs/2405.04324 (2024) - [i22]Ibrahim Abdelaziz, Kinjal Basu, Mayank Agarwal, Sadhana Kumaravel, Matthew Stallone, Rameswar Panda, Yara Rizk, GP Bhargav, Maxwell Crouse, Chulaka Gunasekara, Shajith Ikbal, Sachin Joshi, Hima Karanam, Vineet Kumar, Asim Munawar, Sumit Neelam, Dinesh Raghu, Udit Sharma, Adriana Meza Soria, Dheeraj Sreedhar, Praveen Venkateswaran, Merve Unuvar, David Cox, Salim Roukos, Luis A. Lastras, Pavan Kapanipathi:
Granite-Function Calling Model: Introducing Function Calling Abilities via Multi-task Learning of Granular Tasks. CoRR abs/2407.00121 (2024) - 2023
- [j13]Deepti Shakya, Vishal Deshpande, Bimlesh Kumar, Mayank Agarwal:
Predicting total sediment load transport in rivers using regression techniques, extreme learning and deep learning models. Artif. Intell. Rev. 56(9): 10067-10098 (2023) - [j12]Divya Singh, Jimson Mathew, Mayank Agarwal, Mahesh Govind:
DLIRIR : Deep learning based improved Reverse Image Retrieval. Eng. Appl. Artif. Intell. 126: 106833 (2023) - [j11]Sanjit Kumar, Bimlesh Kumar, Vishal Deshpande, Mayank Agarwal:
Predicting flow velocity in a vegetative alluvial channel using standalone and hybrid machine learning techniques. Expert Syst. Appl. 232: 120885 (2023) - [j10]Divya Singh, Jimson Mathew, Mayank Agarwal, Mahesh Govind:
Indoor dataset for Person Re-Identification: Exploring the impact of backpacks. J. Vis. Commun. Image Represent. 96: 103931 (2023) - [c39]Zahra Ashktorab, Benjamin Hoover, Mayank Agarwal, Casey Dugan, Werner Geyer, Hao Bang Yang, Mikhail Yurochkin:
Fairness Evaluation in Text Classification: Machine Learning Practitioner Perspectives of Individual and Group Fairness. CHI 2023: 565:1-565:20 - [c38]Zilu Tang, Mayank Agarwal, Alexander Shypula, Bailin Wang, Derry Wijaya, Jie Chen, Yoon Kim:
Explain-then-translate: an analysis on improving program translation with self-generated explanations. EMNLP (Findings) 2023: 1741-1788 - [c37]Djallel Bouneffouf, Mayank Agarwal, Irina Rish:
Dialogue System with Missing Observation. ICASSP 2023: 1-5 - [c36]Anmol Kumar, Mayank Agarwal:
Preserving Service Availability Under DDoS Attack in Micro-Service Based Cloud Infrastructure. SIN 2023: 1-8 - [i21]Naveen Venkat, Mayank Agarwal, Maneesh Kumar Singh, Shubham Tulsiani:
Geometry-biased Transformers for Novel View Synthesis. CoRR abs/2301.04650 (2023) - [i20]Zahra Ashktorab, Benjamin Hoover, Mayank Agarwal, Casey Dugan, Werner Geyer, Hao Bang Yang, Mikhail Yurochkin:
Fairness Evaluation in Text Classification: Machine Learning Practitioner Perspectives of Individual and Group Fairness. CoRR abs/2303.00673 (2023) - [i19]Subha Maity, Mayank Agarwal, Mikhail Yurochkin, Yuekai Sun:
An Investigation of Representation and Allocation Harms in Contrastive Learning. CoRR abs/2310.01583 (2023) - [i18]Zilu Tang, Mayank Agarwal, Alex Shypula, Bailin Wang, Derry Wijaya, Jie Chen, Yoon Kim:
Explain-then-Translate: An Analysis on Improving Program Translation with Self-generated Explanations. CoRR abs/2311.07070 (2023) - 2022
- [j9]Deepti Shakya, Vishal Deshpande, Mayank Agarwal, Bimlesh Kumar:
Standalone and ensemble-based machine learning techniques for particle Froude number prediction in a sewer system. Neural Comput. Appl. 34(18): 15481-15497 (2022) - [c35]Prabhat Kumar Bharti, Tirthankar Ghosal, Mayank Agarwal, Asif Ekbal:
BetterPR: A Dataset for Estimating the Constructiveness of Peer Review Comments. TPDL 2022: 500-505 - [c34]Prabhat Kumar Bharti, Tirthankar Ghosal, Mayank Agarwal, Asif Ekbal:
A Method for Automatically Estimating the Informativeness of Peer Reviews. ICON 2022: 280-289 - [c33]Stephanie Houde, Steven I. Ross, Michael J. Muller, Mayank Agarwal, Fernando Martinez, John T. Richards, Kartik Talamadupula, Justin D. Weisz:
Opportunies for Generative AI in UX Modernization 81-91. IUI Workshops 2022: 81-91 - [c32]Michael J. Muller, Steven I. Ross, Stephanie Houde, Mayank Agarwal, Fernando Martinez, John T. Richards, Kartik Talamadupula, Justin D. Weisz:
Drinking Chai with Your (AI) Programming Partner: A Design Fiction about Generative AI for Software Engineering 107-122. IUI Workshops 2022: 107-122 - [c31]Jiao Sun, Q. Vera Liao, Michael J. Muller, Mayank Agarwal, Stephanie Houde, Kartik Talamadupula, Justin D. Weisz:
Investigating Explainability of Generative AI for Code through Scenario-based Design. IUI 2022: 212-228 - [c30]Justin D. Weisz, Michael J. Muller, Steven I. Ross, Fernando Martinez, Stephanie Houde, Mayank Agarwal, Kartik Talamadupula, John T. Richards:
Better Together? An Evaluation of AI-Supported Code Translation. IUI 2022: 369-391 - [p1]Mayank Agarwal, Mikhail Yurochkin, Yuekai Sun:
Personalization in Federated Learning. Federated Learning 2022: 71-98 - [i17]Jiao Sun, Q. Vera Liao, Michael J. Muller, Mayank Agarwal, Stephanie Houde, Kartik Talamadupula, Justin D. Weisz:
Investigating Explainability of Generative AI for Code through Scenario-based Design. CoRR abs/2202.04903 (2022) - [i16]Justin D. Weisz, Michael J. Muller, Steven I. Ross, Fernando Martinez, Stephanie Houde, Mayank Agarwal, Kartik Talamadupula, John T. Richards:
Better Together? An Evaluation of AI-Supported Code Translation. CoRR abs/2202.07682 (2022) - 2021
- [c29]Mayank Agarwal:
DES Based IDS for detection Minimal De-authentication DoS Attack in 802.11 Wi-Fi Networks. ANTS 2021: 143-148 - [c28]Djallel Bouneffouf, Raphaël Féraud, Sohini Upadhyay, Mayank Agarwal, Yasaman Khazaeni, Irina Rish:
Toward Skills Dialog Orchestration with Online Learning. ICASSP 2021: 3600-3604 - [c27]Michael J. Muller, April Yi Wang, Steven I. Ross, Justin D. Weisz, Mayank Agarwal, Kartik Talamadupula, Stephanie Houde, Fernando Martinez, John T. Richards, Jaimie Drozdal, Xuye Liu, David Piorkowski, Dakuo Wang:
How Data Scientists Improve Generated Code Documentation in Jupyter Notebooks. IUI Workshops 2021 - [c26]Justin D. Weisz, Michael J. Muller, Stephanie Houde, John T. Richards, Steven I. Ross, Fernando Martinez, Mayank Agarwal, Kartik Talamadupula:
Perfection Not Required? Human-AI Partnerships in Code Translation. IUI 2021: 402-412 - [c25]Mayank Agarwal, Mikhail Yurochkin, Yuekai Sun:
On sensitivity of meta-learning to support data. NeurIPS 2021: 20447-20460 - [i15]Mayank Agarwal, Tathagata Chakraborti, Quchen Fu, David Gros, Xi Victoria Lin, Jaron Maene, Kartik Talamadupula, Zhongwei Teng, Jules White:
NeurIPS 2020 NLC2CMD Competition: Translating Natural Language to Bash Commands. CoRR abs/2103.02523 (2021) - [i14]Justin D. Weisz, Michael J. Muller, Stephanie Houde, John T. Richards, Steven I. Ross, Fernando Martinez, Mayank Agarwal, Kartik Talamadupula:
Perfection Not Required? Human-AI Partnerships in Code Translation. CoRR abs/2104.03820 (2021) - [i13]Mayank Agarwal, Tathagata Chakraborti, Sachin Grover:
COVID-19 India Dataset: Parsing Detailed COVID-19 Data in Daily Health Bulletins from States in India. CoRR abs/2110.02311 (2021) - [i12]Mayank Agarwal, Kartik Talamadupula, Fernando Martinez, Stephanie Houde, Michael J. Muller, John T. Richards, Steven I. Ross, Justin D. Weisz:
Using Document Similarity Methods to create Parallel Datasets for Code Translation. CoRR abs/2110.05423 (2021) - [i11]Mayank Agarwal, Mikhail Yurochkin, Yuekai Sun:
On sensitivity of meta-learning to support data. CoRR abs/2110.13953 (2021) - 2020
- [c24]Shubham Agarwal, Christian Muise, Mayank Agarwal, Sohini Upadhyay, Zilu Tang, Zhongshen Zeng, Yasaman Khazaeni:
TraceHub - A Platform to Bridge the Gap between State-of-the-Art Time-Series Analytics and Datasets. AAAI 2020: 13600-13601 - [c23]Mayank Agarwal, Tathagata Chakraborti, Quchen Fu, David Gros, Xi Victoria Lin, Jaron Maene, Kartik Talamadupula, Zhongwei Teng, Jules White:
NeurIPS 2020 NLC2CMD Competition: Translating Natural Language to Bash Commands. NeurIPS (Competition and Demos) 2020: 302-324 - [i10]Mayank Agarwal, Jorge J. Barroso, Tathagata Chakraborti, Eli M. Dow, Kshitij P. Fadnis, Borja Godoy, Kartik Talamadupula:
CLAI: A Platform for AI Skills on the Command Line. CoRR abs/2002.00762 (2020) - [i9]Heiko Ludwig, Nathalie Baracaldo, Gegi Thomas, Yi Zhou, Ali Anwar, Shashank Rajamoni, Yuya Jeremy Ong, Jayaram Radhakrishnan, Ashish Verma, Mathieu Sinn, Mark Purcell, Ambrish Rawat, Tran Ngoc Minh, Naoise Holohan, Supriyo Chakraborty, Shalisha Witherspoon, Dean Steuer, Laura Wynter, Hifaz Hassan, Sean Laguna, Mikhail Yurochkin, Mayank Agarwal, Ebube Chuba, Annie Abay:
IBM Federated Learning: an Enterprise Framework White Paper V0.1. CoRR abs/2007.10987 (2020) - [i8]Sohini Upadhyay, Mikhail Yurochkin, Mayank Agarwal, Yasaman Khazaeni, Djallel Bouneffouf:
Online Semi-Supervised Learning with Bandit Feedback. CoRR abs/2010.12574 (2020) - [i7]Mayank Agarwal, Kartik Talamadupula, Stephanie Houde, Fernando Martinez, Michael J. Muller, John T. Richards, Steven I. Ross, Justin D. Weisz:
Quality Estimation & Interpretability for Code Translation. CoRR abs/2012.07581 (2020)
2010 – 2019
- 2019
- [j8]Mayank Agarwal, Santosh Biswas, Sukumar Nandi:
Discrete event system framework for fault diagnosis with measurement inconsistency: case study of rogue DHCP attack. IEEE CAA J. Autom. Sinica 6(3): 789-806 (2019) - [c22]Navaneet K. L., Priyanka Mandikal, Mayank Agarwal, R. Venkatesh Babu:
CAPNet: Continuous Approximation Projection for 3D Point Cloud Reconstruction Using 2D Supervision. AAAI 2019: 8819-8826 - [c21]Mikhail Yurochkin, Mayank Agarwal, Soumya Ghosh, Kristjan H. Greenewald, Trong Nghia Hoang, Yasaman Khazaeni:
Bayesian Nonparametric Federated Learning of Neural Networks. ICML 2019: 7252-7261 - [c20]Mikhail Yurochkin, Mayank Agarwal, Soumya Ghosh, Kristjan H. Greenewald, Trong Nghia Hoang:
Statistical Model Aggregation via Parameter Matching. NeurIPS 2019: 10954-10964 - [c19]Mayank Agarwal:
Rogue Twin Attack Detection: A Discrete Event System Paradigm Approach. SMC 2019: 1813-1818 - [i6]Ankush Garg, Mayank Agarwal:
Machine Translation: A Literature Review. CoRR abs/1901.01122 (2019) - [i5]Mikhail Yurochkin, Mayank Agarwal, Soumya Ghosh, Kristjan H. Greenewald, Trong Nghia Hoang, Yasaman Khazaeni:
Bayesian Nonparametric Federated Learning of Neural Networks. CoRR abs/1905.12022 (2019) - [i4]Sohini Upadhyay, Mayank Agarwal, Djallel Bouneffouf, Yasaman Khazaeni:
A Bandit Approach to Posterior Dialog Orchestration Under a Budget. CoRR abs/1906.09384 (2019) - [i3]Mikhail Yurochkin, Mayank Agarwal, Soumya Ghosh, Kristjan H. Greenewald, Trong Nghia Hoang:
Statistical Model Aggregation via Parameter Matching. CoRR abs/1911.00218 (2019) - 2018
- [j7]Mayank Agarwal, Santosh Biswas, Sukumar Nandi:
An Efficient Scheme to Detect Evil Twin Rogue Access Point Attack in 802.11 Wi-Fi Networks. Int. J. Wirel. Inf. Networks 25(2): 130-145 (2018) - [c18]Priyanka Mandikal, Navaneet K. L., Mayank Agarwal, Venkatesh Babu Radhakrishnan:
3D-LMNet: Latent Embedding Matching for Accurate and Diverse 3D Point Cloud Reconstruction from a Single Image. BMVC 2018: 55 - [c17]Mayank Agarwal, Rami Puzis, Jawad Haj-Yahya, Polina Zilberman, Yuval Elovici:
Anti-forensic = Suspicious: Detection of Stealthy Malware that Hides Its Network Traffic. SEC 2018: 216-230 - [i2]Priyanka Mandikal, Navaneet K. L., Mayank Agarwal, R. Venkatesh Babu:
3D-LMNet: Latent Embedding Matching for Accurate and Diverse 3D Point Cloud Reconstruction from a Single Image. CoRR abs/1807.07796 (2018) - [i1]Navaneet K. L., Priyanka Mandikal, Mayank Agarwal, R. Venkatesh Babu:
CAPNet: Continuous Approximation Projection For 3D Point Cloud Reconstruction Using 2D Supervision. CoRR abs/1811.11731 (2018) - 2017
- [j6]Mayank Agarwal, Sanketh Purwar, Santosh Biswas, Sukumar Nandi:
Intrusion detection system for PS-Poll DoS attack in 802.11 networks using real time discrete event system. IEEE CAA J. Autom. Sinica 4(4): 792-808 (2017) - 2016
- [j5]Mayank Agarwal, Dileep Pasumarthi, Santosh Biswas, Sukumar Nandi:
Machine learning approach for detection of flooding DoS attacks in 802.11 networks and attacker localization. Int. J. Mach. Learn. Cybern. 7(6): 1035-1051 (2016) - 2015
- [j4]Mayank Agarwal, Santosh Biswas, Sukumar Nandi:
Advanced Stealth Man-in-The-Middle Attack in WPA2 Encrypted Wi-Fi Networks. IEEE Commun. Lett. 19(4): 581-584 (2015) - [c16]Mayank Agarwal, Santosh Biswas, Sukumar Nandi:
I2-diagnosability framework for detection of Advanced Stealth Man in the Middle attack in Wi-Fi networks. MED 2015: 349-356 - [c15]Mayank Agarwal, Santosh Biswas, Sukumar Nandi:
Detection of De-Authentication DoS Attacks in Wi-Fi Networks: A Machine Learning Approach. SMC 2015: 246-251 - 2014
- [j3]Rajesh Singh, Gaurav Kumar Pandey, Mayank Agarwal, Hari Shankar Singh, Pradutt Kumar Bharti, Manoj Kumar Meshram:
Compact Planar Monopole Antenna with Dual Band Notched Characteristics Using T-Shaped Stub and Rectangular Mushroom Type Electromagnetic Band Gap Structure for UWB and Bluetooth Applications. Wirel. Pers. Commun. 78(1): 215-230 (2014) - 2012
- [c14]Mayank Agarwal, Javed Mostafa:
Cohort Selection through Content-Based Image Retrieval: vfM A Case Study. HISB 2012: 117 - 2011
- [j2]Eugenio Cinquemani, Mayank Agarwal, Debasish Chatterjee, John Lygeros:
Convexity and convex approximations of discrete-time stochastic control problems with constraints. Autom. 47(9): 2082-2087 (2011) - [c13]Mayank Agarwal, Javed Mostafa:
Content-based image retrieval for Alzheimer's disease detection. CBMI 2011: 13-18 - [c12]Mahendra Mehra, Mayank Agarwal, R. Pawar, Deven Shah:
Mitigating denial of service attack using CAPTCHA mechanism. ICWET 2011: 284-287 - [c11]Mayank Agarwal, Mahendra Mehra, R. Pawar, Deven Shah:
Secure authentication using dynamic virtual keyboard layout. ICWET 2011: 288-291 - 2010
- [c10]Mayank Agarwal, Himanshu Agrawal, Nikunj Jain, Manish Kumar:
Face Recognition Using Principle Component Analysis, Eigenface and Neural Network. ICSAP 2010: 310-314
2000 – 2009
- 2009
- [b1]Mayank Agarwal:
Identifying, Quantifying, Extracting and Enhancing Implicit Parallelism. University of Illinois Urbana-Champaign, USA, 2009 - [c9]Mayank Agarwal, Eugenio Cinquemani, Debasish Chatterjee, John Lygeros:
On convexity of stochastic optimization problems with constraints. ECC 2009: 2827-2832 - [c8]Mayank Agarwal, Matthew I. Frank:
SPARTAN: A software tool for Parallelization Bottleneck Analysis. IWMSE@ICSE 2009: 56-63 - [c7]Mayank Agarwal, Javed Mostafa:
Image Retrieval for Alzheimer's Disease Detection. MCBR-CDS 2009: 49-60 - [c6]Deven Shah, Ashish Mangal, Mayank Agarwal, Mahendra Mehra, Tushar Dave, Dhiren R. Patel:
Protecting Global SOA from DoS and Other Security Threats. ISA 2009: 652-661 - 2008
- [j1]Adrian David Cheok, Owen Noel Newton Fernando, Imiyage Janaka Prasad Wijesena, Abd-ur-Rehman Mustafa, Ramkumar Shankar, Anne-Katrin Barthoff, Naoko Tosa, Yongsoon Choi, Mayank Agarwal:
BlogWall: Social and Cultural Interaction for Children. Adv. Hum. Comput. Interact. 2008: 341615:1-341615:8 (2008) - [c5]Kshitiz Malik, Mayank Agarwal, Vikram Dhar, Matthew I. Frank:
PaCo: Probability-based path confidence prediction. HPCA 2008: 50-61 - [c4]Kshitiz Malik, Mayank Agarwal, Sam S. Stone, Kevin M. Woley, Matthew I. Frank:
Branch-mispredict level parallelism (BLP) for control independence. HPCA 2008: 62-73 - [c3]Mayank Agarwal, Nitin Navale, Kshitiz Malik, Matthew I. Frank:
Fetch-Criticality Reduction through Control Independence. ISCA 2008: 13-24 - 2007
- [c2]Mayank Agarwal, Kshitiz Malik, Kevin M. Woley, Sam S. Stone, Matthew I. Frank:
Exploiting Postdominance for Speculative Parallelization. HPCA 2007: 295-305 - 2005
- [c1]Ankit Mathur, Mayank Agarwal, Soumyadeb Mitra, Anup Gangwar, M. Balakrishnan, Subhashis Banerjee:
SMPS: an FPGA-based prototyping environment for multiprocessor embedded systems (abstract only). FPGA 2005: 273
Coauthor Index
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