Jean-Baptiste Tristan

ORCID

Publication Activity (10 Years)

Years Active: 2008-2023
Publications (10 Years): 24

Top Venues

CoRR

PPOPP

AISTATS

ACM Trans. Parallel Comput.

Paris Diderot University, France (PHD)

Education History

Paris Diderot University, France

PHD

Publications

Joseph Tassarotti, Jean-Baptiste Tristan
Verified Density Compilation for a Probabilistic Programming Language. Proc. ACM Program. Lang. 7 (PLDI) (2023)
Nathanael L. Ackerman, Julian Asilis, Jieqi Di, Cameron E. Freer, Jean-Baptiste Tristan
Computable PAC Learning of Continuous Features. LICS (2022)
Hao Wu, Babak Esmaeili, Michael L. Wick, Jean-Baptiste Tristan, Jan-Willem van de Meent
Conjugate Energy-Based Models. ICML (2021)
Hao Wu, Babak Esmaeili, Michael L. Wick, Jean-Baptiste Tristan, Jan-Willem van de Meent
Conjugate Energy-Based Models. CoRR (2021)
Alican Bozkurt, Babak Esmaeili, Jean-Baptiste Tristan, Dana H. Brooks, Jennifer G. Dy, Jan-Willem van de Meent
Rate-Regularization and Generalization in Variational Autoencoders. AISTATS (2021)
Ananya Gupta, Eric Johnson, Justin Payan, Aditya Kumar Roy, Ari Kobren, Swetasudha Panda, Jean-Baptiste Tristan, Michael L. Wick
Online Post-Processing in Rankings for Fair Utility Maximization. WSDM (2021)
Joseph Tassarotti, Koundinya Vajjha, Anindya Banerjee, Jean-Baptiste Tristan
A formal proof of PAC learnability for decision stumps. CPP (2021)
Nathanael L. Ackerman, Julian Asilis, Jieqi Di, Cameron E. Freer, Jean-Baptiste Tristan
On computable learning of continuous features. CoRR (2021)
Jean-Baptiste Tristan, Joseph Tassarotti, Koundinya Vajjha, Michael L. Wick, Anindya Banerjee
Verification of ML Systems via Reparameterization. CoRR (2020)
Michael L. Wick, Kate Silverstein, Jean-Baptiste Tristan, Adam Craig Pocock, Mark Johnson
Detecting and Exorcising Statistical Demons from Language Models with Anti-Models of Negative Data. CoRR (2020)
Joseph Tassarotti, Jean-Baptiste Tristan, Koundinya Vajjha
A Formal Proof of PAC Learnability for Decision Stumps. CoRR (2019)
Michael L. Wick, Swetasudha Panda, Joseph Tassarotti, Jean-Baptiste Tristan
Scaling Hierarchical Coreference with Homomorphic Compression. AKBC (2019)
Jay Yoon Lee, Sanket Vaibhav Mehta, Michael L. Wick, Jean-Baptiste Tristan, Jaime G. Carbonell
Gradient-Based Inference for Networks with Output Constraints. AAAI (2019)
Michael L. Wick, Swetasudha Panda, Jean-Baptiste Tristan
Unlocking Fairness: a Trade-off Revisited. NeurIPS (2019)
Guy L. Steele Jr., Jean-Baptiste Tristan
Using Butterfly-patterned Partial Sums to Draw from Discrete Distributions. ACM Trans. Parallel Comput. 6 (4) (2019)
Joseph Tassarotti, Jean-Baptiste Tristan, Michael L. Wick
Sketching for Latent Dirichlet-Categorical Models. AISTATS (2019)
Joseph Tassarotti, Jean-Baptiste Tristan, Michael L. Wick
Sketching for Latent Dirichlet-Categorical Models. CoRR (2018)
Guy L. Steele Jr., Jean-Baptiste Tristan
Using Butterfly-Patterned Partial Sums to Draw from Discrete Distributions. PPOPP (2017)
Daniel Huang, Jean-Baptiste Tristan, Greg Morrisett
Compiling Markov chain Monte Carlo algorithms for probabilistic modeling. PLDI (2017)
Jay Yoon Lee, Michael L. Wick, Jean-Baptiste Tristan, Jaime G. Carbonell
Enforcing Constraints on Outputs with Unconstrained Inference. CoRR (2017)
Guy L. Steele Jr., Jean-Baptiste Tristan
Adding Approximate Counters. ACM Trans. Parallel Comput. 4 (1) (2017)
Jay Yoon Lee, Michael L. Wick, Jean-Baptiste Tristan, Jaime G. Carbonell
Enforcing Output Constraints via SGD: A Step Towards Neural Lagrangian Relaxation. AKBC@NIPS (2017)
Manzil Zaheer, Michael L. Wick, Jean-Baptiste Tristan, Alexander J. Smola, Guy L. Steele Jr.
Exponential Stochastic Cellular Automata for Massively Parallel Inference. AISTATS (2016)
Guy L. Steele Jr., Jean-Baptiste Tristan
Adding approximate counters. PPOPP (2016)
Guy L. Steele Jr., Jean-Baptiste Tristan
Using Butterfly-Patterned Partial Sums to Optimize GPU Memory Accesses for Drawing from Discrete Distributions. CoRR (2015)
Jean-Baptiste Tristan, Joseph Tassarotti, Guy L. Steele Jr.
Efficient Training of LDA on a GPU by Mean-for-Mode Estimation. ICML (2015)
Jean-Baptiste Tristan, Daniel Huang, Joseph Tassarotti, Adam Craig Pocock, Stephen J. Green, Guy L. Steele Jr.
Augur: Data-Parallel Probabilistic Modeling. NIPS (2014)
Jean-Baptiste Tristan, Daniel Huang, Joseph Tassarotti, Adam Craig Pocock, Stephen J. Green, Guy L. Steele Jr.
Augur: a Modeling Language for Data-Parallel Probabilistic Inference. CoRR (2013)
Changhee Park, Guy L. Steele Jr., Jean-Baptiste Tristan
Parallel programming with big operators. PPOPP (2013)
Greg Morrisett, Gang Tan, Joseph Tassarotti, Jean-Baptiste Tristan, Edward Gan
RockSalt: better, faster, stronger SFI for the x86. PLDI (2012)
Jean-Baptiste Tristan, Paul Govereau, Greg Morrisett
Evaluating value-graph translation validation for LLVM. PLDI (2011)
Jean-Baptiste Tristan, Xavier Leroy
A simple, verified validator for software pipelining. POPL (2010)
Jean-Baptiste Tristan, Xavier Leroy
Verified validation of lazy code motion. PLDI (2009)
Jean-Baptiste Tristan, Xavier Leroy
Formal verification of translation validators: a case study on instruction scheduling optimizations. POPL (2008)

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Publication Activity (10 Years)

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Jean-Baptiste Tristan