발행물

전체 논문

150

41

Learning Analysis Strategies for Octagon and Context Sensitivity from Labeled Data Generated by Static Analyses
Kihong Heo, Hakjoo Oh, Hongseok Yang
Formal Methods in System Design, 2018

42

Adaptive Static Analysis via Learning with Bayesian Optimization
Kihong Heo, Hakjoo Oh, Hongseok Yang, Kwangkeun Yi
ACM Transactions on Programming Languages and Systems, 2018

43

Towards a Testable Notion of Generalisation for Generative Adversarial Networks
Robert Cornish, Frank Wood, Hongseok Yang
NIPS Workshop on Deep Learning: Bridging Theory and Practice, 2017.12

44

Inference Trees: Adaptive Inference with Exploration
Tom Rainforth, Yuan Zhou, Xiaoyu Lu, Yee Whye Teh, Frank Wood, Hongseok Yang, Jan-Willem van de Meent
NIPS Workshop on Advances in Approximate Bayesian Inference (AABI 2017), 2017.12

45

Automatically Generating Features for Learning Program Analysis Heuristics for C-like Languages
Kwonsoo Chae, Hakjoo Oh, Kihong Heo, Hongseok Yang
OOPSLA 2017, 2017.10

46

Algebraic Laws for Weak Consistency
Andrea Cerone, Alexey Gotsman, Hongseok Yang
CONCUR 2017, 2017.09

47

A Convenient Category for Higher-Order Probability Theory
Chris Heunen, Ohad Kammar, Sam Staton, Hongseok Yang
LICS 2017, 2017.06

48

Design and Implementation of Probabilistic Programming Language Anglican
David Tolpin, Jan-Willem van de Meent, Hongseok Yang, Frank Wood
Post-conference Proceedings of IFL 2016, 2017.02

49

Exchangeable Random Processes and Data Abstraction
Sam Staton, Hongseok Yang, Nathanael Ackerman, Cameron Freer, Daniel M. Roy
Workshop on Probabilistic Programming Semantics (PPS 2017), 2017

50

Efficient Exact Inference in Discrete Anglican Programs
Robert Cornish, Frank Wood, Hongseok Yang
Workshop on Probabilistic Programming Semantics (PPS 2017), 2017