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2020 – today
- 2024
[c12]Darren Ng, Andrew Lin, Arjun Kashyap, Guanpeng Li, Xiaoyi Lu:
NVMe-oPF: Designing Efficient Priority Schemes for NVMe-over-Fabrics with Multi-Tenancy Support. IPDPS 2024: 519-531- 2023
- [c11]Nipun Manral, Andrew Lin
, Caroline Park, Priscilla McElhinney, Aditya Killekar, Hidenari Matsumoto, Jacek Kwiecinski, Konrad Pieszko, Aryabod Razipour, Kajetan Grodecki, Mhairi Doris, Alan C. Kwan, Donghee Han, Keiichiro Kuronuma, Guadalupe Flores Tomasino, Evangelos Tzolos, Aakash D. Shanbhag, Markus Goeller, Mohamed Marwan, Sebastien Cadet, Stephen Achenbach, Stephen J. Nicholls, Dennis T. Wong, Daniel S. Berman, Marc R. Dweck, David E. Newby, Michelle C. Williams, Piotr J. Slomka, Damini Dey:
Direct head-to-head comparison of convolutional long short-term memory and transformer networks for artificial Intelligence-based quantification of atherosclerotic plaque and stenosis from coronary CT angiography. Medical Imaging: Image Processing 2023 - [i3]Kiriaki Frangias, Andrew Lin, Ellen Vitercik, Manolis Zampetakis:
Algorithmic Contract Design for Crowdsourced Ranking. CoRR abs/2310.09974 (2023) - 2022
- [c10]Darren Ng, Colin Schmierer, Andrew Lin, Zeyu Liu, Falin Yu, Shawn D. Newsam, Reza Ehsani, Xiaoyi Lu:
Benchmarking Object Detection Models with Mummy Nuts Datasets. Bench 2022: 102-119 - [c9]Aditya Killekar, Kajetan Grodecki, Andrew Lin, Sebastien Cadet, Priscilla McElhinney, Aryabod Razipour, Cato Chan, Barry D. Pressman, Peter Julien, Peter Chen, Judit Simon, Nitesh Nerlekar, Pál Maurovich-Horvat, Nicola Gaibazzi, Udit Thakur, Elisabetta Mancini, Cecilia Agalbato, Jiro Munechika, Hidenari Matsumoto, Roberto Menè, Damini Dey, Gianfranco Parati, Franco Cernigliaro, Camilla Torlasco, Gianluca Pontone, Piotr J. Slomka:
COVID-19 lesion segmentation using convolutional LSTM for self-attention. Medical Imaging: Image Processing 2022 - 2021
- [c8]Jonathan Jaramillo, Andrew Lin, Emma Sung, Isabel Jane Hunt Richter, Kirstin Petersen:
Mobile, Inflatable Interface to Support Human Robot Interaction Studies. UR 2021: 320-325 - [i2]Kajetan Grodecki, Aditya Killekar, Andrew Lin, Sebastien Cadet, Priscilla McElhinney, Aryabod Razipour, Cato Chan, Barry D. Pressman, Peter Julien, Judit Simon, Pál Maurovich-Horvat, Nicola Gaibazzi, Udit Thakur, Elisabetta Mancini, Cecilia Agalbato, Jiro Munechika, Hidenari Matsumoto, Roberto Menè, Gianfranco Parati, Franco Cernigliaro, Nitesh Nerlekar, Camilla Torlasco, Gianluca Pontone, Damini Dey, Piotr J. Slomka:
Rapid quantification of COVID-19 pneumonia burden from computed tomography with convolutional LSTM networks. CoRR abs/2104.00138 (2021) - 2020
- [c7]Andrew Lin:
Learning Cube Strategy in Backgammon with Neural Networks. TAAI 2020: 29-34 - [c6]Andrew Lin:
Playing AI Dots-And-Boxes Using Endgame Theory and Nimstring Sprague-Grundy Values. TAAI 2020: 211-216
2010 – 2019
- 2019
- [c5]Lisa Wu, David Bruns-Smith, Frank A. Nothaft, Qijing Huang, Sagar Karandikar, Johnny Le, Andrew Lin, Howard Mao, Brendan Sweeney, Krste Asanovic, David A. Patterson, Anthony D. Joseph:
FPGA Accelerated INDEL Realignment in the Cloud. HPCA 2019: 277-290 - [c4]Andrew Lin:
Using Combinatorial Solutions and Atomic Weights to Play Competitive AI Clobber. TAAI 2019: 1-7 - 2011
- [c3]Andrew Lin:
Solving election manipulation using integer partitioning problems. AAMAS 2011: 583-590 - [c2]Charlynn Clayton, Andrew Lin, Janine Pitt:
Key Intelligence Topics (KITs) and Key Intelligence Questions (KIQs) in safety signal intelligence. FUSION 2011: 1-8 - [c1]Andrew Lin:
The Complexity of Manipulating k-Approval Elections. ICAART (2) 2011: 212-218 - 2010
- [i1]Andrew Lin:
The Complexity of Manipulating $k$-Approval Elections. CoRR abs/1005.4159 (2010)
Coauthor Index
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last updated on 2024-10-07 21:26 CEST by the dblp team
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