Browse "School of Computing(전산학부)" by Author Yang, Hongseok
Showing results 1 to 60 of 77
| A Divide-and-Conquer Approach for Analysing Overlaid Data Structures Lee, Oukseh; Yang, Hongseok; Petersen, Rasmus, FORMAL METHODS IN SYSTEM DESIGN, v.41, no.1, pp.4 - 24, 2012-08 |
| A Generalization of Hierarchical Exchangeability on Trees to Directed Acyclic Graphs Jung, Paul Heajoon; Lee, Jiho; Sam Staton; Yang, Hongseok, Annales Henri Lebesgue, v.4, pp.325 - 368, 2021-01 |
| A local shape analysis based on separation logic Distefano, Dino; O'Hearn, Peter W.; Yang, Hongseok, TOOLS AND ALGORITHMS FOR THE CONSTRUCTION AND ANALYSIS OF SYSTEMS, PROCEEDINGS, v.3920, pp.287 - 302, 2006 |
| A Step-Indexed Kripke Model of Hidden State Schwinghammer, Jan; Birkedal, Lars; Pottier, Francois; Reus, Bernhard; Stovring, Kristian; Yang, Hongseok, MATHEMATICAL STRUCTURES IN COMPUTER SCIENCE, v.23, no.1, pp.1 - 54, 2013-02 |
| Abstraction for Concurrent Objects Filipovic, Ivana; O'Hearn, Peter; Rinetzky, Noam; Yang, Hongseok, THEORETICAL COMPUTER SCIENCE, v.411, no.51-52, pp.4379 - 4398, 2010-12 |
| Abstraction Refinement Guided by a Learnt Probabilistic Model Grigore, Radu y; Yang, Hongseok, ACM SIGPLAN NOTICES, v.51, no.1, pp.485 - 498, 2016-01 |
| Abstractions from Tests Naik, Mayur; Yang, Hongseok; Castelnuovo, Ghila; Sagiv, Mooly, ACM SIGPLAN NOTICES, v.47, no.1, pp.373 - 385, 2012-01 |
| Adaptive Static Analysis via Learning with Bayesian Optimization Heo, Kihong; Oh, Hakjoo; Yang, Hongseok; Yi, Kwangkeun, ACM TRANSACTIONS ON PROGRAMMING LANGUAGES AND SYSTEMS, v.40, no.4, 2018-12 |
| 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 |
| Adaptive strategy for resetting a non-stationary Markov chain during learning via joint stochastic approximation = 결합확률근사 학습에서 비정상 마르코프 연쇄를 재설정하는 적응형 전략link Kim, Hyunsu; Yang, Hongseok; et al, 한국과학기술원, 2021 |
| Algorithms for offline imitation learning with supplementary demonstrations = 추가적인 시연을 활용한 오프라인 모방학습 알고리즘 연구link Kim, Geon-Hyeong; Kim, Kee-Eung; 김기응; Yang, Hongseok; et al, 한국과학기술원, 2022 |
| Alpha-stable convergence of heavy-/light-tailed infinitely wide neural networks Jung, Paul; Lee, Hoil; Lee, Jiho; Yang, Hongseok, ADVANCES IN APPLIED PROBABILITY, v.55, no.4, pp.1415 - 1441, 2023-12 |
| 'Cause I'm Strong Enough: Reasoning about Consistency Choices in Distributed Systems Gotsman, Alexey; Yang, Hongseok; Ferreira, Carla; Najafzadeh, Mahsa; Shapiro, Marc, ACM SIGPLAN NOTICES, v.51, no.1, pp.371 - 384, 2016-01 |
| Automatic construction of hoare proofs from abstract interpretation results Seo, SN; Yang, Hongseok; Yi, Kwangkeun, PROGRAMMING LANGUAGES AND SYSTEMS, PROCEEDINGS, v.2895, pp.230 - 245, 2003 |
| Automatic verification of pointer programs using grammar-based shape analysis Lee, O; Yang, Hongseok; Yi, KK, PROGRAMMING LANGUAGES AND SYSTEMS, PROCEEDINGS, v.3444, pp.124 - 140, 2005 |
| Automatically Generating Features for Learning Program Analysis Heuristics Chae, Kwonsoo; Oh, Hakjoo; Heo, Kihong; Yang, Hongseok, Proceedings of the ACM on Programming Languages, v.1, no.OOPSLA, pp.101:1 - 101:25, 2017-10 |
| 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 |
| Beyond reachability: Shape abstraction in the presence of pointer arithmetic Calcagno, Cristiano; Distefano, Dino; O'Hearn, Peter W.; Yang, Hongseok, STATIC ANALYSIS, PROCEEDINGS, v.4134, pp.182 - 203, 2006 |
| Blaming the Client: On Data Refinement in the Presence of Pointers Filipovic, Ivana; O'Hearn, Peter; Torp-Smith, Noah; Yang, Hongseok, FORMAL ASPECTS OF COMPUTING, v.22, no.5, pp.547 - 583, 2010-09 |
| Compositional Shape Analysis by Means of Bi-Abduction Calcagno, Cristiano; Distefano, Dino; O'Hearn, Peter W.; Yang, Hongseok, JOURNAL OF THE ACM, v.58, no.6, 2011-12 |
| Compositional Shape Analysis by means of Bi-Abduction Calcagno, Cristiano; Distefano, Dino; O'Hearn, Peter; Yang, Hongseok, ACM SIGPLAN NOTICES, v.44, no.1, pp.289 - 300, 2009-01 |
| Correctness of Data Representations involving Heap Data Structures Reddy, US; Yang, Hongseok, SCIENCE OF COMPUTER PROGRAMMING, v.50, no.1-3, pp.129 - 160, 2004-03 |
| Correctness of data representations involving heap data structures Reddy, US; Yang, Hongseok, PROGRAMMING LANGUAGES AND SYSTEMS, v.2618, pp.223 - 237, 2003 |
| Deep Neural Networks with Dependent Weights: Gaussian Process Mixture Limit, Heavy Tails, Sparsity and Compressibility Lee, Hoil; Ayed, Fadhel; Jung, Paul; Lee, Juho; Yang, Hongseok; Caron, Francois, JOURNAL OF MACHINE LEARNING RESEARCH, v.24, pp.1 - 78, 2023-09 |
| 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 |
| Denotational Validation of Higher-order Bayesian Inference Scibior, Adam; Kammar, Ohad; Vakar, Matthijs; Staton, Sam; Yang, Hongseok; Cai, Yufei; Ostermann, Klaus; et al, Proceedings of the ACM on Programming Languages, v.2, 2018-01 |
| 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 |
| Editorial Message Yang, Hongseok, PROCEEDINGS OF THE ACM ON PROGRAMMING LANGUAGES-PACMPL, v.6, 2022-01 |
| Finding Optimum Abstractions in Parametric Dataflow Analysis Zhang, Xin; Naik, Mayur; Yang, Hongseok, ACM SIGPLAN NOTICES, v.48, no.6, pp.365 - 376, 2013-06 |
| Goal-directed Weakening of Abstract Interpretation Results Seo, Sunae; Yang, Hongseok; Yi, Kwangkeun; Han, Taisook, ACM TRANSACTIONS ON PROGRAMMING LANGUAGES AND SYSTEMS, v.29, no.10, 2007-10 |
| Hybrid Top-down and Bottom-up Interprocedural Analysis Zhang, Xin; Mangal, Ravi; Naik, Mayur; Yang, Hongseok, ACM SIGPLAN NOTICES, v.49, no.6, pp.249 - 258, 2014-06 |
| Learning a Strategy for Adapting a Program Analysis via Bayesian Optimisation Oh, Hakjoo; Yang, Hongseok; Yi, Kwangkeun, ACM SIGPLAN NOTICES, v.50, no.10, pp.572 - 588, 2015-10 |
| 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 Analysis Strategies for Octagon and Context Sensitivity from Labeled Data Generated by Static Analyses Heo, Kihong; Oh, Hakjoo; Yang, Hongseok, FORMAL METHODS IN SYSTEM DESIGN, v.53, no.2, pp.189 - 220, 2018-10 |
| Learning symmetric rules with SATNet = SATNet을 이용하여 대칭성을 가지는 논리적 문제 학습하기link Lim, Sangho; Yang, Hongseok; et al, 한국과학기술원, 2023 |
| 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 |
| Linearizability with Ownership Transfer Gotsman, Alexey; Yang, Hongseok, LOGICAL METHODS IN COMPUTER SCIENCE, v.9, no.3, 2013 |
| 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 |
| Modular Verification of Preemptive OS Kernels Gotsman, Alexey; Yang, Hongseok, JOURNAL OF FUNCTIONAL PROGRAMMING, v.23, no.4, pp.452 - 514, 2013-07 |
| Modular Verification of Preemptive OS Kernels Gotsman, Alexey; Yang, Hongseok, ACM SIGPLAN NOTICES, v.46, no.9, pp.404 - 417, 2011-09 |
| Nested Hoare Triples and Frame Rule for Higher-order Store Schwinghammer, Jan; Birkedal, Lars; Reus, Bernhard; Yang, Hongseok, LOGICAL METHODS IN COMPUTER SCIENCE, v.7, no.3, 2011 |
| On Abstraction Refinement for Program Analyses in Datalog Zhang, Xin; Mangal, Ravi; Grigore, Radu; Naik, Mayur; Yang, Hongseok, ACM SIGPLAN NOTICES, v.49, no.6, pp.239 - 248, 2014-06 |
| On applying the group symmetries to SATNet = SATNet과 군 대칭성의 활용link Oh, Eun-Gyeol; Yang, Hongseok; et al, 한국과학기술원, 2022 |
| 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 |
| On the connection between lottery ticket hypothesis and neural tangent Kernel = Lottery ticket hypothesis와 neural tangent kernel의 관계에 대한 연구link Park, Jeongmin; Yang, Hongseok; et al, 한국과학기술원, 2021 |
| On the semantics of refinement calculi Yang, Hongseok; Reddy, US, FOUNDATIONS OF SOFTWARE SCIENCE AND COMPUTATION STRUCTURES, v.1784, pp.359 - 374, 2000 |
| 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 |
| Relational Parametricity and Separation Logic Birkedal, Lars; Yang, Hongseok, LOGICAL METHODS IN COMPUTER SCIENCE, v.4, no.2, 2008 |
| Relational Separation Logic Yang, Hongseok, THEORETICAL COMPUTER SCIENCE, v.375, no.1-3, pp.308 - 334, 2007-05 |
| 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 |
| Replicated Data Types: Specification, Verification, Optimality Burckhardt, Sebastian; Gotsman, Alexey; Yang, Hongseok; Zawirski, Marek, ACM SIGPLAN NOTICES, v.49, no.1, pp.271 - 284, 2014-01 |
| 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, ACM SIGPLAN NOTICES, v.49, no.6, pp.475 - 484, 2014-06 |
| 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 |
| Selective X-Sensitive Analysis Guided by Impact Pre-Analysis Oh, Hakjoo; Lee, Wonchan; Heo, Kihong; Yang, Hongseok; Yi, Kwangkeun, ACM TRANSACTIONS ON PROGRAMMING LANGUAGES AND SYSTEMS, v.38, no.2, 2016-01 |
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