Browse "CS-Conference Papers(학술회의논문)" by Author Yang, Hongseok
Showing results 1 to 22 of 22
| Adaptive Strategy for Resetting a Non-stationary Markov Chain during Learning via Joint Stochastic Approximation Kim, Hyunsu; Lee, Juho; Yang, Hongseok, The 3rd Symposium on Advances in Approximate Bayesian Inference (AABI 2021), Organisers of advances in approximate Bayesian inference (AABI), 2021-01-13 |
| Bayesian Policy Search for Stochastic Domains Tolpin, David; Zhou, Yuan; Yang, Hongseok, The Second International Conference on Probabilistic Programming (PROBPROG 2020), Organisers of PROBPROG 2020, 2020-10-23 |
| DemoDICE: Offline Imitation Learning with Supplementary Imperfect Demonstrations Kim, Geon-Hyeong; Seo, Seokin; Lee, Jongmin; Jeon, Wonseok; Hwang, HyeongJoo; Yang, Hongseok; Kim, Kee-Eung, Tenth International Conference on Learning Representations (ICLR 2022), International Conference on Learning Representations, 2022-04-26 |
| Differentiable Algorithm for Marginalising Changepoints Lim, Hyoungjin; Che, Gwonsoo; Lee, Wonyeol; Yang, Hongseok, The 34th AAAI Conference on Artificial Intelligence (AAAI 2020), pp.4828 - 4835, AAAI, 2020-02-10 |
| Divide, Conquer, and Combine: a New Inference Strategy for Probabilistic Programs with Stochastic Support Zhou, Yuan; Yang, Hongseok; Teh, Yee Whye; Rainforth, Tom, The 37th International Conference on Machine Learning (ICML 2020), pp.2127 - 2138, ICML Organisation, 2020-07-15 |
| Learning a variable-clustering strategy for octagon from labeled data generated by a static analysis Heo, Kihong; Oh, Hakjoo; Yang, Hongseok, 23rd International Symposium on Static Analysis, SAS 2016, pp.237 - 256, SAS Committee, 2016-09-08 |
| Learning Symmetric Rules with SATNet Lim, Sangho; Oh, Eun-Gyeol; Yang, Hongseok, The 36th Conference on Neural Information Processing Systems (NeurIPS 2022), Neural information processing systems foundation, 2022-11-30 |
| LF-PPL: A Low-Level First Order Probabilistic Programming Language for Non-Differentiable Models Zhou, Yuan; Gram-Hansen, Bradley; Kohn, Tobias; Rainforth, Tom; Yang, Hongseok; Wood, Frank, The 22nd International Conference on Artificial Intelligence and Statistics (AISTATS 2019), pp.148 - 157, AISTATS 2019, 2019-04-16 |
| LobsDICE: Offline Learning from Observation via Stationary Distribution Correction Estimation Kim, Geon-Hyeong; Lee, Jongmin; Jang, Youngsoo; Yang, Hongseok; Kim, Kee-Eung, The 36th Conference on Neural Information Processing Systems (NeurIPS 2022), Neural information processing systems foundation, 2022-12-01 |
| On correctness of automatic differentiation for non-differentiable functions Lee, Wonyeol; Yu, Hangyeol; Rival, Xavier; Yang, Hongseok, The 34th Conference on Neural Information Processing Systems (NeurIPS 2020), Neural information processing systems foundation, 2020-12-08 |
| On nesting Monte Carlo estimators Rainforth, Tom; Cornish, Robert; Yang, Hongseok; Warrington, Andrew; Wood, Frank, 35th International Conference on Machine Learning, ICML 2018, pp.6789 - 6817, International Machine Learning Society (IMLS), 2018-07-13 |
| Regularized Behavior Cloning for Blocking the Leakage of Past Action Information Seo, Seokin; HWANG, HYEONGJOO; Yang, Hongseok; Kim, Kee-Eung, The 37th Conference on Neural Information Processing Systems (NeurIPS 2023), Neural information processing systems foundation, 2023-12-13 |
| Regularizing towards soft equivariance under mixed symmetries Kim, Hyunsu; Lee, Hyungi; Yang, Hongseok; Lee, Juho, Fortieth International Conference on Machine Learning, International Conference on Machine Learning, 2023-07-23 |
| Reparameterization gradient for non-differentiable models Lee, Wonyeol; Yu, Hangyeol; Yang, Hongseok, The 32nd Conference on Neural Information Processing Systems (NeurIPS 2018), pp.5553 - 5563, Neural information processing systems foundation, 2018-12-06 |
| Resource-Aware Program Analysis Via Online Abstraction Coarsening Heo, Kihong; Oh, Hakjoo; Yang, Hongseok, The 41st ACM/IEEE International Conference on Software Engineering (ICSE 2019), pp.94 - 104, ACM, IEEE, 2019-05-29 |
| Scale mixtures of neural network Gaussian processes Lee, Hyungi; Yun, Eunggu; Yang, Hongseok; Lee, Juho, Tenth International Conference on Learning Representations (ICLR 2022), International Conference on Learning Representations, 2022-04-25 |
| Selective context-sensitivity guided by impact pre-analysis Oh, Hakjoo; Lee, Wonchan; Heo, Kihong; Yang, Hongseok; Yi, Kwangkeun, 35th ACM SIGPLAN Conference on Programming Language Design and Implementation, PLDI 2014, pp.475 - 484, ACM Special Interest Group on Programming Languages (SIGPLAN), 2014-06-09 |
| Some semantic issues in probabilistic programming languages Yang, Hongseok, 4th International Conference on Formal Structures for Computation and Deduction, FSCD 2019, Schloss Dagstuhl- Leibniz-Zentrum fur Informatik GmbH, Dagstuhl Publishing, 2019-06 |
| The Beta-Bernoulli process and algebraic effects Staton, Sam; Stein, Dario; Yang, Hongseok; Ackerman, Nathanael L.; Freer, Cameron E.; Roy, Daniel M., The 45th International Colloquium on Automata, Languages, and Programming, ICALP 2018, pp.141:1 - 141:15, European Association for Theoretical Computer Science (EATCS), 2018-07-10 |
| Towards verified stochastic variational inference for probabilistic programs Lee, Wonyeol; Yu, Hangyeol; Rival, Xavier; Yang, Hongseok, The 47th ACM SIGPLAN Symposium on Principles of Programming Languages (POPL 2020), Association for Computing Machinery, 2020-01-22 |
| Trust Region Sequential Variational Inference Kim, Geon-Hyeong; Jang, Youngsoo; Lee, Jongmin; Jeon, Wonseok; Yang, Hongseok; Kim, Kee-Eung, Conference on Asian Conference on Machine Learning (ACML 2019), Asian Conference on Machine Learning, 2019-11-19 |
| Variational Inference for Sequential Data with Future Likelihood Estimates Kim, Geon-Hyeong; Jang, Youngsoo; Yang, Hongseok; Kim, Kee-Eung, The 37th International Conference on Machine Learning (ICML 2020), pp.5252 - 5261, ICML Organisation, 2020-07-16 |
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