| RockSalt: better, faster, stronger SFI for the x86 G Morrisett, G Tan, J Tassarotti, JB Tristan, E Gan Proceedings of the 33rd ACM SIGPLAN conference on Programming Language …, 2012 | 157 | 2012 |
| Evaluating value-graph translation validation for LLVM JB Tristan, P Govereau, G Morrisett Proceedings of the 32nd ACM SIGPLAN conference on programming language …, 2011 | 111 | 2011 |
| Formal verification of translation validators: a case study on instruction scheduling optimizations JB Tristan, X Leroy Proceedings of the 35th annual ACM SIGPLAN-SIGACT symposium on Principles of …, 2008 | 102 | 2008 |
| A simple, verified validator for software pipelining JB Tristan, X Leroy ACM Sigplan Notices 45 (1), 83-92, 2010 | 61 | 2010 |
| Verified validation of lazy code motion JB Tristan, X Leroy ACM Sigplan Notices 44 (6), 316-326, 2009 | 60 | 2009 |
| Augur: Data-parallel probabilistic modeling JB Tristan, D Huang, J Tassarotti, AC Pocock, S Green, GL Steele Advances in Neural Information Processing Systems 27, 2600-2608, 2014 | 35* | 2014 |
| Exponential stochastic cellular automata for massively parallel inference M Zaheer, M Wick, JB Tristan, A Smola, G Steele Artificial Intelligence and Statistics, 966-975, 2016 | 27* | 2016 |
| Compiling Markov chain Monte Carlo algorithms for probabilistic modeling D Huang, JB Tristan, G Morrisett Proceedings of the 38th ACM SIGPLAN Conference on Programming Language …, 2017 | 25 | 2017 |
| Gradient-based inference for networks with output constraints JY Lee, SV Mehta, M Wick, JB Tristan, J Carbonell Proceedings of the AAAI Conference on Artificial Intelligence 33 (01), 4147-4154, 2019 | 23* | 2019 |
| Adding approximate counters GL Steele Jr, JB Tristan ACM Transactions on Parallel Computing (TOPC) 4 (1), 1-45, 2017 | 21* | 2017 |
| Efficient training of LDA on a GPU by mean-for-mode estimation JB Tristan, J Tassarotti, G Steele International Conference on Machine Learning, 59-68, 2015 | 20* | 2015 |
| Unlocking fairness: a trade-off revisited M Wick, S Panda, JB Tristan | 18 | 2019 |
| Using butterfly-patterned partial sums to draw from discrete distributions GL Steele Jr, JB Tristan Proceedings of the 22nd ACM SIGPLAN Symposium on Principles and Practice of …, 2017 | 10* | 2017 |
| Sparse and data-parallel inference method and system for the latent Dirichlet allocation model J Tristan, GL Steele Jr, J Tassarotti US Patent 9,767,416, 2017 | 8 | 2017 |
| Formal verification of translation validators JB Tristan Université Paris-Diderot-Paris VII, 2009 | 7 | 2009 |
| Data-parallel parameter estimation of the Latent Dirichlet allocation model by greedy Gibbs sampling J Tristan, G Steele US Patent 10,860,829, 2020 | 6 | 2020 |
| A formal proof of PAC learnability for decision stumps J Tassarotti, K Vajjha, A Banerjee, JB Tristan Proceedings of the 10th ACM SIGPLAN International Conference on Certified …, 2021 | 2 | 2021 |
| Streaming latent dirichlet allocation J Tristan, M Wick, S Green US Patent App. 15/934,262, 2019 | 2 | 2019 |
| Ensembled Decision Systems Using Feature Hashing Models J Tristan, A Pocock, M Wick, G Steele US Patent App. 15/717,830, 2019 | 2 | 2019 |
| Differentiable set to increase the memory capacity of recurrent neural networks J Tristan, M Wick, M Zaheer US Patent App. 15/339,303, 2018 | 2 | 2018 |
Michael WickUniversity of MassachusettsVerified email at cs.umass.edu
