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Michael Carbin
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The lottery ticket hypothesis: Finding sparse, trainable neural networks
J Frankle, M Carbin
arXiv preprint arXiv:1803.03635, 2018
37932018
Linear mode connectivity and the lottery ticket hypothesis
J Frankle, GK Dziugaite, D Roy, M Carbin
International Conference on Machine Learning, 3259-3269, 2020
765*2020
Automatically patching errors in deployed software
JH Perkins, S Kim, S Larsen, S Amarasinghe, J Bachrach, M Carbin, ...
Proceedings of the ACM SIGOPS 22nd symposium on Operating systems principles …, 2009
5152009
Dynamic knobs for responsive power-aware computing
H Hoffmann, S Sidiroglou, M Carbin, S Misailovic, A Agarwal, M Rinard
ACM SIGARCH computer architecture news 39 (1), 199-212, 2011
4442011
Comparing rewinding and fine-tuning in neural network pruning
A Renda, J Frankle, M Carbin
arXiv preprint arXiv:2003.02389, 2020
4032020
The lottery ticket hypothesis for pre-trained bert networks
T Chen, J Frankle, S Chang, S Liu, Y Zhang, Z Wang, M Carbin
Advances in neural information processing systems 33, 15834-15846, 2020
3552020
Verifying quantitative reliability for programs that execute on unreliable hardware
M Carbin, S Misailovic, MC Rinard
ACM SIGPLAN Conference on Object-Oriented Programming, Systems, Languages …, 2013
3402013
Using Datalog with binary decision diagrams for program analysis
J Whaley, D Avots, M Carbin, MS Lam
Asian Symposium on Programming Languages and Systems, 97-118, 2005
2872005
Context-sensitive program analysis as database queries
MS Lam, J Whaley, VB Livshits, MC Martin, D Avots, M Carbin, C Unkel
Proceedings of the twenty-fourth ACM SIGMOD-SIGACT-SIGART symposium on …, 2005
2442005
Chisel: Reliability-and accuracy-aware optimization of approximate computational kernels
S Misailovic, M Carbin, S Achour, Z Qi, MC Rinard
ACM Sigplan Notices 49 (10), 309-328, 2014
2402014
Pruning neural networks at initialization: Why are we missing the mark?
J Frankle, GK Dziugaite, DM Roy, M Carbin
arXiv preprint arXiv:2009.08576, 2020
2162020
Ithemal: Accurate, portable and fast basic block throughput estimation using deep neural networks
C Mendis, A Renda, S Amarasinghe, M Carbin
International Conference on machine learning, 4505-4515, 2019
1722019
Proving acceptability properties of relaxed nondeterministic approximate programs
M Carbin, D Kim, S Misailovic, MC Rinard
PLDI: Programming Languages Design and Implementation 47 (6), 169-180, 2012
1382012
The lottery tickets hypothesis for supervised and self-supervised pre-training in computer vision models
T Chen, J Frankle, S Chang, S Liu, Y Zhang, M Carbin, Z Wang
Proceedings of the IEEE/CVF conference on computer vision and pattern …, 2021
1262021
Detecting and escaping infinite loops with jolt
M Carbin, S Misailovic, M Kling, MC Rinard
ECOOP 2011–Object-Oriented Programming: 25th European Conference, Lancaster …, 2011
1042011
Automatically identifying critical input regions and code in applications
M Carbin, MC Rinard
Proceedings of the 19th international symposium on Software testing and …, 2010
802010
Exploiting errors for efficiency: A survey from circuits to applications
P Stanley-Marbell, A Alaghi, M Carbin, E Darulova, L Dolecek, ...
ACM Computing Surveys (CSUR) 53 (3), 1-39, 2020
722020
Automatic input rectification
F Long, V Ganesh, M Carbin, S Sidiroglou, M Rinard
2012 34th International Conference on Software Engineering (ICSE), 80-90, 2012
722012
Bypass virtualization
IITJ Purtell, W Chun, M Carbin
US Patent 8,065,687, 2011
722011
The three pillars of machine programming
J Gottschlich, A Solar-Lezama, N Tatbul, M Carbin, M Rinard, R Barzilay, ...
Proceedings of the 2nd ACM SIGPLAN International Workshop on Machine …, 2018
672018
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