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2020 – today
- 2024
[j15]Velma K. Lopez
, Estee Y. Cramer, Robert Pagano, John M. Drake, Eamon B. O'Dea, Madeline Adee, Turgay Ayer, Jagpreet Chhatwal, Ozden O. Dalgic, Mary A. Ladd, Benjamin P. Linas, Peter P. Mueller, Jade Xiao, Johannes Bracher, Alvaro J. Castro Rivadeneira, Aaron Gerding, Tilmann Gneiting, Yuxin Huang, Dasuni Jayawardena, Abdul H. Kanji, Khoa Le, Anja Mühlemann, Jarad Niemi, Evan L. Ray, Ariane Stark, Yijin Wang, Nutcha Wattanachit, Martha W. Zorn, Sen Pei, Jeffrey Shaman, Teresa K. Yamana, Samuel R. Tarasewicz, Daniel J. Wilson, Sid Baccam, Heidi Gurung, Steve Stage, Brad Suchoski, Lei Gao, Zhiling Gu, Myungjin Kim, Xinyi Li, Guannan Wang, Lily Wang, Yueying Wang, Shan Yu, Lauren Gardner, Sonia Jindal, Maximilian Marshall, Kristen Nixon, Juan Dent, Alison L. Hill, Joshua Kaminsky, Elizabeth C. Lee, Joseph Chadi Lemaitre, Justin Lessler, Claire P. Smith, Shaun Truelove, Matt Kinsey, Luke C. Mullany, Kaitlin Rainwater-Lovett, Lauren Shin, Katharine Tallaksen, Shelby Wilson, Dean Karlen, Lauren Castro, Geoffrey Fairchild, Isaac Michaud, Dave Osthus, Jiang Bian, Wei Cao, Zhifeng Gao, Juan Lavista Ferres, Chaozhuo Li, Tie-Yan Liu, Xing Xie, Shun Zhang, Shun Zheng, Matteo Chinazzi, Jessica T. Davis, Kunpeng Mu, Ana L. Pastore y Piontti, Alessandro Vespignani, Xinyue Xiong, Robert Walraven, Jinghui Chen, Quanquan Gu, Lingxiao Wang, Pan Xu, Weitong Zhang, Difan Zou, Graham Casey Gibson, Daniel Sheldon, Ajitesh Srivastava, Aniruddha Adiga, Benjamin Hurt, Gursharn Kaur, Bryan Lewis, Madhav V. Marathe, Akhil Sai Peddireddy, Przemyslaw J. Porebski, Srinivasan Venkatramanan, Lijing Wang, Pragati V. Prasad, Jo W. Walker, Alexander E. Webber, Rachel B. Slayton, Matthew Biggerstaff, Nicholas G. Reich, Michael A. Johansson:
Challenges of COVID-19 Case Forecasting in the US, 2020-2021. PLoS Comput. Biol. 20(5): 1011200 (2024)- [c46]Ajitesh Srivastava, Juan Marcos Ramirez, Sergio Díaz-Aranda, José Aguilar, Antonio Fernández Anta, Antonio Ortega, Rosa Elvira Lillo:
Nowcasting Temporal Trends Using Indirect Surveys. AAAI 2024: 22359-22367 - [c45]Sarthak Kumar Maharana, Krishna Kamal Adidam, Shoumik Nandi, Ajitesh Srivastava:
Acoustic-to-Articulatory Inversion for Dysarthric Speech: are Pre-Trained Self-Supervised Representations Favorable? ICASSP Workshops 2024: 408-412 - [c44]Alexander Rodríguez, Bijaya Adhikari, Ajitesh Srivastava, Sen Pei, Marie-Laure Charpignon, Kai Wang, Serina Chang, Anil Vullikanti, B. Aditya Prakash:
epiDAMIK 2024: The 7th International Workshop on Epidemiology meets Data Mining and Knowledge Discovery. KDD 2024: 6735-6736 - [i25]Majd Al Aawar, Srikar Mutnuri, Mansooreh Montazerin, Ajitesh Srivastava:
Global Prediction of COVID-19 Variant Emergence Using Dynamics-Informed Graph Neural Networks. CoRR abs/2401.03390 (2024) - [i24]Zhengtao Yao, Hong Nguyen, Ajitesh Srivastava, Jose Luis Ambite:
Task-Agnostic Federated Learning. CoRR abs/2406.17235 (2024) - [i23]Zitong Huang, Mansooreh Montazerin, Ajitesh Srivastava:
Simultaneous Weight and Architecture Optimization for Neural Networks. CoRR abs/2410.08339 (2024) - 2023
- [j14]Sina Jahandari, Ajitesh Srivastava:
Detection of Delays and Feedthroughs in Dynamic Networked Systems. IEEE Control. Syst. Lett. 7: 1201-1206 (2023) - [j13]Sina Jahandari, Ajitesh Srivastava:
Adjusting for Unmeasured Confounding Variables in Dynamic Networks. IEEE Control. Syst. Lett. 7: 1237-1242 (2023) - [j12]Chung Ming Cheung, Sanmukh Rao Kuppannagari, Ajitesh Srivastava, Rajgopal Kannan, Viktor K. Prasanna:
Behind-the-Meter Solar Generation Disaggregation at Varying Aggregation Levels Using Consumer Mixture Models. IEEE Trans. Sustain. Comput. 8(1): 43-55 (2023) - [c43]James Orme-Rogers, Ajitesh Srivastava:
Spatio-Temporal Attention in Multi-Granular Brain Chronnectomes For Detection of Autism Spectrum Disorder. ICASSP 2023: 1-5 - [c42]Bijaya Adhikari, Alexander Rodríguez, Amulya Yadav, Sen Pei, Ajitesh Srivastava, Marie-Laure Charpignon, Anil Vullikanti, B. Aditya Prakash:
epiDAMIK 6.0: The 6th International Workshop on Epidemiology meets Data Mining and Knowledge Discovery. KDD 2023: 5847-5848 - [i22]Ajitesh Srivastava, Juan Marcos Ramirez, Sergio Díaz-Aranda, José Aguilar, Antonio Ortega, Antonio Fernández Anta, Rosa Lillo-Rodriguez:
Estimating Temporal Trends using Indirect Surveys. CoRR abs/2307.06643 (2023) - [i21]Sarthak Kumar Maharana, Krishna Kamal Adidam, Shoumik Nandi, Ajitesh Srivastava:
Acoustic-to-articulatory inversion for dysarthric speech: Are pre-trained self-supervised representations favorable? CoRR abs/2309.01108 (2023) - [i20]Ajitesh Srivastava:
DTW+S: Shape-based Comparison of Time-series with Ordered Local Trend. CoRR abs/2309.03579 (2023) - [i19]Yue Niu, Rajgopal Kannan, Ajitesh Srivastava, Viktor K. Prasanna:
Reuse Kernels or Activations? A Flexible Dataflow for Low-latency Spectral CNN Acceleration. CoRR abs/2310.10902 (2023) - 2022
- [j11]Pengmiao Zhang, Ajitesh Srivastava, Ta-Yang Wang, César A. F. De Rose, Rajgopal Kannan, Viktor K. Prasanna:
C-MemMAP: clustering-driven compact, adaptable, and generalizable meta-LSTM models for memory access prediction. Int. J. Data Sci. Anal. 13(1): 3-16 (2022) - [c41]Ajitesh Srivastava, Satwant Singh, Fiona Lee:
Shape-based Evaluation of Epidemic Forecasts. IEEE Big Data 2022: 1701-1710 - [c40]Pengmiao Zhang, Ajitesh Srivastava, Anant V. Nori, Rajgopal Kannan, Viktor K. Prasanna:
Fine-grained address segmentation for attention-based variable-degree prefetching. CF 2022: 103-112 - [c39]Bijaya Adhikari, Amulya Yadav, Sen Pei, Ajitesh Srivastava, Sarah Kefayati, Alexander Rodríguez, Marie-Laure Charpignon, Anil Vullikanti, B. Aditya Prakash:
epiDAMIK 5.0: The 5th International Workshop on Epidemiology meets Data Mining and Knowledge Discovery. KDD 2022: 4850-4851 - [c38]Carson Gray, Trevor Webster, Brian Ozarowicz, Yuhang Chen, Timothy Bui, Ajitesh Srivastava, Naomi T. Fitter:
"This Bot Knows What I'm Talking About!" Human-Inspired Laughter Classification Methods for Adaptive Robotic Comedians. RO-MAN 2022: 1007-1014 - [c37]Pengmiao Zhang, Rajgopal Kannan, Ajitesh Srivastava, Anant V. Nori, Viktor K. Prasanna:
ReSemble: Reinforced Ensemble Framework for Data Prefetching. SC 2022: 81:1-81:14 - [p1]Ajitesh Srivastava, Charalampos Chelmis, Viktor K. Prasanna:
Computational Models for Cascades in Massive Graphs. Massive Graph Analytics 2022: 377-395 - [i18]Hanqing Zeng, Muhan Zhang, Yinglong Xia, Ajitesh Srivastava, Andrey Malevich, Rajgopal Kannan, Viktor K. Prasanna, Long Jin, Ren Chen:
Decoupling the Depth and Scope of Graph Neural Networks. CoRR abs/2201.07858 (2022) - [i17]Hongkuan Zhou, Ajitesh Srivastava, Rajgopal Kannan, Viktor K. Prasanna:
Design and Implementation of Knowledge Base for Runtime Management of Software Defined Hardware. CoRR abs/2203.15534 (2022) - [i16]Pengmiao Zhang, Ajitesh Srivastava, Anant V. Nori, Rajgopal Kannan, Viktor K. Prasanna:
Fine-Grained Address Segmentation for Attention-Based Variable-Degree Prefetching. CoRR abs/2205.02269 (2022) - [i15]Pengmiao Zhang, Ajitesh Srivastava, Anant V. Nori, Rajgopal Kannan, Viktor K. Prasanna:
TransforMAP: Transformer for Memory Access Prediction. CoRR abs/2205.14778 (2022) - [i14]Majd Al Aawar, Ajitesh Srivastava:
Random Forest of Epidemiological Models for Influenza Forecasting. CoRR abs/2206.08967 (2022) - [i13]James Orme-Rogers, Ajitesh Srivastava:
Spatio-Temporal Attention in Multi-Granular Brain Chronnectomes for Detection of Autism Spectrum Disorder. CoRR abs/2211.07360 (2022) - 2021
- [j10]Hanqing Zeng, Hongkuan Zhou, Ajitesh Srivastava, Rajgopal Kannan, Viktor K. Prasanna:
Accurate, efficient and scalable training of Graph Neural Networks. J. Parallel Distributed Comput. 147: 166-183 (2021) - [j9]Hongkuan Zhou, Ajitesh Srivastava, Hanqing Zeng, Rajgopal Kannan, Viktor K. Prasanna:
Accelerating Large Scale Real-Time GNN Inference using Channel Pruning. Proc. VLDB Endow. 14(9): 1597-1605 (2021) - [c36]Ta-Yang Wang, William Chang, Ajitesh Srivastava, Rajgopal Kannan, Viktor K. Prasanna:
Monte Carlo Tree Search for Task Mapping onto Heterogeneous Platforms. HiPC 2021: 63-70 - [c35]Ajitesh Srivastava, Naomi T. Fitter:
A Robot Walks into a Bar: Automatic Robot Joke Success Assessment. ICRA 2021: 2710-2716 - [c34]Bijaya Adhikari, Ajitesh Srivastava, Sen Pei, Sarah Kefayati, Rose Yu, Amulya Yadav, Alexander Rodríguez, Arvind Ramanathan, Anil Vullikanti, B. Aditya Prakash:
The 4th International Workshop on Epidemiology meets Data Mining and Knowledge Discovery (epiDAMIK 4.0 @ KDD2021). KDD 2021: 4104-4105 - [c33]Hanqing Zeng, Muhan Zhang, Yinglong Xia, Ajitesh Srivastava, Andrey Malevich, Rajgopal Kannan, Viktor K. Prasanna, Long Jin, Ren Chen:
Decoupling the Depth and Scope of Graph Neural Networks. NeurIPS 2021: 19665-19679 - [c32]Naifeng Zhang, Ajitesh Srivastava, Rajgopal Kannan, Viktor K. Prasanna:
GenMAT: A General-Purpose Machine Learning-Driven Auto-Tuner for Heterogeneous Platforms. PEHC@SC 2021: 1-9 - [i12]Ajitesh Srivastava, Tianjian Xu, Viktor K. Prasanna:
The EpiBench Platform to Propel AI/ML-based Epidemic Forecasting: A Prototype Demonstration Reaching Human Expert-level Performance. CoRR abs/2102.02842 (2021) - [i11]Hongkuan Zhou, Ajitesh Srivastava, Hanqing Zeng, Rajgopal Kannan, Viktor K. Prasanna:
Accelerating Large Scale Real-Time GNN Inference using Channel Pruning. CoRR abs/2105.04528 (2021) - 2020
- [c31]Yue Niu, Rajgopal Kannan, Ajitesh Srivastava, Viktor K. Prasanna:
Reuse Kernels or Activations?: A Flexible Dataflow for Low-latency Spectral CNN Acceleration. FPGA 2020: 266-276 - [c30]Rachit Rajat, Yuan Meng, Sanmukh R. Kuppannagari, Ajitesh Srivastava, Viktor K. Prasanna, Rajgopal Kannan:
QTAccel: A Generic FPGA based Design for Q-Table based Reinforcement Learning Accelerators. FPGA 2020: 323 - [c29]Ajitesh Srivastava, Naifeng Zhang, Rajgopal Kannan, Viktor K. Prasanna:
Towards High Performance, Portability, and Productivity: Lightweight Augmented Neural Networks for Performance Prediction. HiPC 2020: 21-30 - [c28]Ta-Yang Wang, Ajitesh Srivastava, Viktor K. Prasanna:
A Framework for Task Mapping onto Heterogeneous Platforms. HPEC 2020: 1-6 - [c27]Hanqing Zeng, Hongkuan Zhou, Ajitesh Srivastava, Rajgopal Kannan, Viktor K. Prasanna:
GraphSAINT: Graph Sampling Based Inductive Learning Method. ICLR 2020 - [c26]Yuan Meng, Sanmukh R. Kuppannagari, Rachit Rajat, Ajitesh Srivastava, Rajgopal Kannan, Viktor K. Prasanna:
QTAccel: A Generic FPGA based Design for Q-Table based Reinforcement Learning Accelerators. IPDPS Workshops 2020: 107-114 - [c25]Pengmiao Zhang, Ajitesh Srivastava, Benjamin Brooks, Rajgopal Kannan, Viktor K. Prasanna:
RAOP: Recurrent Neural Network Augmented Offset Prefetcher. MEMSYS 2020: 352-362 - [c24]Ajitesh Srivastava, Ta-Yang Wang, Pengmiao Zhang, César Augusto Fonticielha De Rose, Rajgopal Kannan, Viktor K. Prasanna:
MemMAP: Compact and Generalizable Meta-LSTM Models for Memory Access Prediction. PAKDD (2) 2020: 57-68 - [c23]Connor Imes, Alexei Colin, Naifeng Zhang, Ajitesh Srivastava, Viktor K. Prasanna, John Paul Walters:
Compiler Abstractions and Runtime for Extreme-scale SAR and CFD Workloads. ESPM2@SC 2020: 1-7 - [c22]Yang Yang, Sanmukh R. Kuppannagari, Ajitesh Srivastava, Rajgopal Kannan, Viktor K. Prasanna:
FASTHash: FPGA-Based High Throughput Parallel Hash Table. ISC 2020: 3-22 - [i10]Ajitesh Srivastava, Naifeng Zhang, Rajgopal Kannan, Viktor K. Prasanna:
Towards High Performance, Portability, and Productivity: Lightweight Augmented Neural Networks for Performance Prediction. CoRR abs/2003.07497 (2020) - [i9]Ajitesh Srivastava, Viktor K. Prasanna:
Learning to Forecast and Forecasting to Learn from the COVID-19 Pandemic. CoRR abs/2004.11372 (2020) - [i8]Ajitesh Srivastava, Viktor K. Prasanna:
Data-driven Identification of Number of Unreported Cases for COVID-19: Bounds and Limitations. CoRR abs/2006.02127 (2020) - [i7]Ajitesh Srivastava, Tianjian Xu, Viktor K. Prasanna:
Fast and Accurate Forecasting of COVID-19 Deaths Using the SIkJα Model. CoRR abs/2007.05180 (2020) - [i6]Hanqing Zeng, Hongkuan Zhou, Ajitesh Srivastava, Rajgopal Kannan, Viktor K. Prasanna:
Accurate, Efficient and Scalable Training of Graph Neural Networks. CoRR abs/2010.03166 (2020)
2010 – 2019
- 2019
- [j8]Ajitesh Srivastava, Robin Petering, Nicholas Barr, Rajgopal Kannan, Eric Rice, Viktor K. Prasanna:
Network-based intervention strategies to reduce violence among homeless. Soc. Netw. Anal. Min. 9(1): 38:1-38:12 (2019) - [c21]Max Noormohammadpour, Ajitesh Srivastava, Cauligi S. Raghavendra:
Optimizing Inter-Datacenter Tail Flow Completion Times using Best Worst-case Routing. Allerton 2019: 25-31 - [c20]Ajitesh Srivastava, Rajgopal Kannan, Charalampos Chelmis, Viktor K. Prasanna:
RecANt: Network-based Recruitment for Active Fake News Correction. IEEE BigData 2019: 940-949 - [c19]Kartik Lakhotia, Rajgopal Kannan, Aditya Gaur, Ajitesh Srivastava, Viktor K. Prasanna:
Parallel edge-based sampling for static and dynamic graphs. CF 2019: 125-134 - [c18]Chuanxiu Xiong, Ajitesh Srivastava, Rajgopal Kannan, Omkar Damle, Viktor K. Prasanna, Erroll Southers:
On Predicting Crime with Heterogeneous Spatial Patterns: Methods and Evaluation. SIGSPATIAL/GIS 2019: 43-51 - [c17]Yue Niu, Hanqing Zeng, Ajitesh Srivastava, Kartik Lakhotia, Rajgopal Kannan, Yanzhi Wang, Viktor K. Prasanna:
SPEC2: SPECtral SParsE CNN Accelerator on FPGAs. HiPC 2019: 195-204 - [c16]Hongkuan Zhou, Ajitesh Srivastava, Rajgopal Kannan, Viktor K. Prasanna:
Design and Implementation of Knowledge Base for Runtime Management of Software Defined Hardware. HPEC 2019: 1-7 - [c15]Hanqing Zeng, Hongkuan Zhou, Ajitesh Srivastava, Rajgopal Kannan, Viktor K. Prasanna:
Accurate, Efficient and Scalable Graph Embedding. IPDPS 2019: 462-471 - [c14]Ajitesh Srivastava, Angelos Lazaris, Benjamin Brooks, Rajgopal Kannan, Viktor K. Prasanna:
Predicting memory accesses: the road to compact ML-driven prefetcher. MEMSYS 2019: 461-470 - [c13]Akshit Goel, Sanmukh R. Kuppannagari, Yang Yang, Ajitesh Srivastava, Viktor K. Prasanna:
Parallel Totally Induced Edge Sampling on FPGAs. PARCO 2019: 671-680 - [i5]Hanqing Zeng, Hongkuan Zhou, Ajitesh Srivastava, Rajgopal Kannan, Viktor K. Prasanna:
GraphSAINT: Graph Sampling Based Inductive Learning Method. CoRR abs/1907.04931 (2019) - [i4]Max Noormohammadpour, Ajitesh Srivastava, Cauligi S. Raghavendra:
Optimizing Inter-Datacenter Tail Flow Completion Times using Best Worst-case Routing. CoRR abs/1908.09070 (2019) - [i3]Yue Niu, Hanqing Zeng, Ajitesh Srivastava, Kartik Lakhotia, Rajgopal Kannan, Yanzhi Wang, Viktor K. Prasanna:
SPEC2: SPECtral SParsE CNN Accelerator on FPGAs. CoRR abs/1910.11103 (2019) - 2018
- [j7]Mohammad Noormohammadpour, Ajitesh Srivastava, Cauligi S. Raghavendra:
On Minimizing the Completion Times of Long Flows Over Inter-Datacenter WAN. IEEE Commun. Lett. 22(12): 2475-2478 (2018) - [c12]Ajitesh Srivastava, Robin Petering, Rajgopal Kannan, Eric Rice, Viktor K. Prasanna:
How to Stop Violence Among Homeless: Extension of Voter Model and Intervention Strategies. ASONAM 2018: 83-86 - [c11]Ajitesh Srivastava, Rajgopal Kannan, Charalampos Chelmis, Viktor K. Prasanna:
FActCheck: Keeping Activation of Fake News at Check. AAMAS 2018: 2079-2081 - [c10]Chung Ming Cheung, Wen Zhong, Chuanxiu Xiong, Ajitesh Srivastava, Rajgopal Kannan, Viktor K. Prasanna:
Behind-the-Meter Solar Generation Disaggregation using Consumer Mixture Models. SmartGridComm 2018: 1-6 - [i2]Mohammad Noormohammadpour, Ajitesh Srivastava, Cauligi S. Raghavendra:
On Minimizing the Completion Times of Long Flows over Inter-Datacenter WAN. CoRR abs/1810.00169 (2018) - [i1]Hanqing Zeng, Hongkuan Zhou, Ajitesh Srivastava, Rajgopal Kannan, Viktor K. Prasanna:
Accurate, Efficient and Scalable Graph Embedding. CoRR abs/1810.11899 (2018) - 2017
- [c9]Michail Misyrlis, Chung Ming Cheung, Ajitesh Srivastava, Rajgopal Kannan, Viktor K. Prasanna:
Spatio-Temporal Modeling of Criminal Activity. SocialSens@CPSWeek 2017: 3-8 - [c8]Shreyas G. Singapura, Ajitesh Srivastava, Rajgopal Kannan, Viktor K. Prasanna:
OSCAR: Optimizing SCrAtchpad reuse for graph processing. HPEC 2017: 1-7 - 2016
- [j6]Ajitesh Srivastava, Charalampos Chelmis, Viktor K. Prasanna:
Computing competing cascades on signed networks. Soc. Netw. Anal. Min. 6(1): 82:1-82:14 (2016) - [c7]Ajitesh Srivastava, Charalampos Chelmis, Viktor K. Prasanna:
Mining Large Dense Subgraphs. WWW (Companion Volume) 2016: 111-112 - 2015
- [j5]Ajitesh Srivastava, Charalampos Chelmis, Viktor K. Prasanna:
The unified model of social influence and its application in influence maximization. Soc. Netw. Anal. Min. 5(1): 66:1-66:15 (2015) - [c6]Ajitesh Srivastava, Charalampos Chelmis, Viktor K. Prasanna:
Social Influence Computation and Maximization in Signed Networks with Competing Cascades. ASONAM 2015: 41-48 - [c5]Ajitesh Srivastava, Ren Chen, Viktor K. Prasanna, Charalampos Chelmis:
A hybrid design for high performance large-scale sorting on FPGA. ReConFig 2015: 1-6 - 2014
- [j4]Charalampos Chelmis, Ajitesh Srivastava, Viktor K. Prasanna:
Computational models of technology adoption at the workplace. Soc. Netw. Anal. Min. 4(1): 199 (2014) - [c4]Ajitesh Srivastava, Charalampos Chelmis, Viktor K. Prasanna:
Influence in social networks: A unified model? ASONAM 2014: 451-454 - 2013
- [j3]Saptarshi Ghosh, Sudipta Saha, Ajitesh Srivastava, Tyll Krueger, Niloy Ganguly, Animesh Mukherjee:
Understanding Evolution of Inter-Group Relationships Using Bipartite Networks. IEEE J. Sel. Areas Commun. 31(9-Supplement): 584-594 (2013) - [c3]Ajitesh Srivastava, Axel J. Soto, Evangelos E. Milios:
A graph-based topic extraction method enabling simple interactive customization. ACM Symposium on Document Engineering 2013: 71-80 - [c2]Ajitesh Srivastava, Axel J. Soto, Evangelos E. Milios:
Text clustering using one-mode projection of document-word bipartite graphs. SAC 2013: 927-932 - 2012
- [j2]Saptarshi Ghosh, Ajitesh Srivastava, Niloy Ganguly:
Effects of a soft cut-off on node-degree in the Twitter social network. Comput. Commun. 35(7): 784-795 (2012) - [j1]Niloy Ganguly, Saptarshi Ghosh, Tyll Krueger, Ajitesh Srivastava:
Degree distributions of evolving alphabetic bipartite networks and their projections. Theor. Comput. Sci. 466: 20-36 (2012) - 2011
- [c1]Saptarshi Ghosh, Ajitesh Srivastava, Niloy Ganguly:
Assessing the Effects of a Soft Cut-Off in the Twitter Social Network. Networking (2) 2011: 288-300
Coauthor Index
[j12] [i19] [j11] [c40] [c37] [p1] [i18] [i17] [i16] [i15] [j10] [j9] [c36] [c33] [c32] [i12] [i11] [c31] [c30] [c29] [c28] [c27] [c26] [c25] [c24] [c23] [c22] [i10] [i9] [i8] [i7] [i6] [j8] [c20] [c19] [c18] [c17] [c16] [c15] [c14] [c13] [i5] [i3] [c12] [c11] [c10] [i1] [c9] [c8] [j6] [c7] [j5] [c6] [c5] [j4] [c4]
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