{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,11]],"date-time":"2026-03-11T16:48:21Z","timestamp":1773247701374,"version":"3.50.1"},"publisher-location":"New York, NY, USA","reference-count":39,"publisher":"ACM","license":[{"start":{"date-parts":[[2022,8,14]],"date-time":"2022-08-14T00:00:00Z","timestamp":1660435200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.acm.org\/publications\/policies\/copyright_policy#Background"}],"content-domain":{"domain":["dl.acm.org"],"crossmark-restriction":true},"short-container-title":[],"published-print":{"date-parts":[[2022,8,14]]},"DOI":"10.1145\/3534678.3539220","type":"proceedings-article","created":{"date-parts":[[2022,8,12]],"date-time":"2022-08-12T19:06:41Z","timestamp":1660331201000},"page":"2692-2702","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":13,"title":["Generalizable Floorplanner through Corner Block List Representation and Hypergraph Embedding"],"prefix":"10.1145","author":[{"given":"Mohammad","family":"Amini","sequence":"first","affiliation":[{"name":"Huawei Noah's Ark Lab, Montreal, Canada"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Zhanguang","family":"Zhang","sequence":"additional","affiliation":[{"name":"Huawei Noah's Ark Lab, Montreal, Canada"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Surya","family":"Penmetsa","sequence":"additional","affiliation":[{"name":"Huawei Noah's Ark Lab, Montreal, Canada"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yingxue","family":"Zhang","sequence":"additional","affiliation":[{"name":"Huawei Noah's Ark Lab, Montreal, PQ, Canada"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jianye","family":"Hao","sequence":"additional","affiliation":[{"name":"Huawei Noah's Ark Lab, Beijing, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Wulong","family":"Liu","sequence":"additional","affiliation":[{"name":"Huawei Noah's Ark Lab, Montreal, Canada"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"320","published-online":{"date-parts":[[2022,8,14]]},"reference":[{"key":"e_1_3_2_1_1_1","unstructured":"[n.d.]. GSRC Benchmark. http:\/\/vlsicad.eecs.umich.edu\/BK\/GSRCbench\/"},{"key":"e_1_3_2_1_2_1","unstructured":"[n.d.]. MCNC Benchmark. http:\/\/vlsicad.eecs.umich.edu\/BK\/MCNCbench\/"},{"key":"e_1_3_2_1_3_1","volume-title":"Int. Conf. on Learning Representations (ICLR).","author":"Andrychowicz Marcin","unstructured":"Marcin Andrychowicz, Anton Raichuk, and et al. Sta\"czyk. 2021. What matters in on-policy reinforcement learning? a large-scale empirical study. In Int. Conf. on Learning Representations (ICLR)."},{"key":"e_1_3_2_1_4_1","volume-title":"Torr","author":"Bai Song","year":"2021","unstructured":"Song Bai, Feihu Zhang, and Philip H. S. Torr. 2021. Hypergraph Convolution and Hypergraph Attention. Pattern Recognition (2021)."},{"key":"e_1_3_2_1_5_1","volume-title":"Proc. Adv. Neural Inf. Proc. Systems (NIPS).","author":"Blake Charlie","year":"2021","unstructured":"Charlie Blake, Vitaly Kurin, Maximilian Igl, and Shimon Whiteson. 2021. Snowflake: Scaling GNNs to High-Dimensional Continuous Control via Parameter Freezing. In Proc. Adv. Neural Inf. Proc. Systems (NIPS)."},{"key":"e_1_3_2_1_6_1","doi-asserted-by":"publisher","DOI":"10.1145\/337292.337541"},{"key":"e_1_3_2_1_7_1","volume-title":"Modern floorplanning based on B\/sup *\/-tree and fast simulated annealing","author":"Chen Tung-Chieh","year":"2006","unstructured":"Tung-Chieh Chen and Yao-Wen Chang. 2006. Modern floorplanning based on B\/sup *\/-tree and fast simulated annealing. IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems (TCAD) (2006)."},{"key":"e_1_3_2_1_8_1","doi-asserted-by":"publisher","DOI":"10.1145\/1233501.1233538"},{"key":"e_1_3_2_1_9_1","volume-title":"Proc. Adv. Neural Inf. Proc. Systems (NIPS).","author":"Cheng Ruoyu","year":"2021","unstructured":"Ruoyu Cheng and Junchi Yan. 2021. On Joint Learning for Solving Placement and Routing in Chip Design. In Proc. Adv. Neural Inf. Proc. Systems (NIPS)."},{"key":"e_1_3_2_1_10_1","unstructured":"Prafulla Dhariwal Christopher Hesse Oleg Klimov Alex Nichol Matthias Plappert Alec Radford John Schulman Szymon Sidor Yuhuai Wu and Peter Zhokhov. 2017. OpenAI Baselines. https:\/\/github.com\/openai\/baselines."},{"key":"e_1_3_2_1_11_1","volume-title":"Deep reinforcement learning in large discrete action spaces. arXiv preprint arXiv:1512.07679","author":"Dulac-Arnold Gabriel","year":"2015","unstructured":"Gabriel Dulac-Arnold, Richard Evans, Hado van Hasselt, Peter Sunehag, Timothy Lillicrap, Jonathan Hunt, Timothy Mann, Theophane Weber, Thomas Degris, and Ben Coppin. 2015. Deep reinforcement learning in large discrete action spaces. arXiv preprint arXiv:1512.07679 (2015)."},{"key":"e_1_3_2_1_12_1","volume-title":"Int. Conf. on Machine Learning (ICML).","author":"Farquhar Gregory","year":"2020","unstructured":"Gregory Farquhar, Laura Gustafson, Zeming Lin, Shimon Whiteson, Nicolas Usunier, and Gabriel Synnaeve. 2020. Growing action spaces. In Int. Conf. on Machine Learning (ICML)."},{"key":"e_1_3_2_1_13_1","volume-title":"Generalizable Cross-Graph Embedding for GNN-based Congestion Prediction. In 2021 IEEE\/ACM International Conference On Computer Aided Design (ICCAD).","author":"Ghose Amur","year":"2021","unstructured":"Amur Ghose, Vincent Zhang, Yingxue Zhang, Dong Li, Wulong Liu, and Mark Coates. 2021. Generalizable Cross-Graph Embedding for GNN-based Congestion Prediction. In 2021 IEEE\/ACM International Conference On Computer Aided Design (ICCAD)."},{"key":"e_1_3_2_1_14_1","doi-asserted-by":"publisher","DOI":"10.1109\/ICCD50377.2020.00061"},{"key":"e_1_3_2_1_15_1","doi-asserted-by":"publisher","DOI":"10.1109\/TCSII.2004.824047"},{"key":"e_1_3_2_1_16_1","volume-title":"IEEE\/ACM International Conference on Computer-Aided Design (ICCAD).","author":"Kahng A.B.","year":"2005","unstructured":"A.B. Kahng, S. Reda, and Qinke Wang. 2005. Architecture and details of a high quality, large-scale analytical placer. In ICCAD-2005. IEEE\/ACM International Conference on Computer-Aided Design (ICCAD)."},{"key":"e_1_3_2_1_17_1","volume-title":"Int. Conf. on Learning Representations (ICLR).","author":"Kingma Diederik P","year":"2015","unstructured":"Diederik P Kingma and Jimmy Ba. 2015. Adam: A method for stochastic optimization. In Int. Conf. on Learning Representations (ICLR)."},{"key":"e_1_3_2_1_18_1","volume-title":"Int. Conf. on Learning Representations (ICLR).","author":"Kipf Thomas N","year":"2017","unstructured":"Thomas N Kipf and Max Welling. 2017. Semi-supervised classification with graph convolutional networks. In Int. Conf. on Learning Representations (ICLR)."},{"key":"e_1_3_2_1_19_1","doi-asserted-by":"publisher","DOI":"10.1109\/VLSI-SoC.2019.8920342"},{"key":"e_1_3_2_1_20_1","volume-title":"C Daniel Gelatt Jr, and Mario P Vecchi","author":"Kirkpatrick Scott","year":"1983","unstructured":"Scott Kirkpatrick, C Daniel Gelatt Jr, and Mario P Vecchi. 1983. Optimization by simulated annealing. science (1983)."},{"key":"e_1_3_2_1_21_1","doi-asserted-by":"publisher","DOI":"10.1109\/ASPDAC.2014.6742866"},{"key":"e_1_3_2_1_22_1","volume-title":"Int. Conf. on Machine Learning (ICML).","author":"Laskin Michael","year":"2020","unstructured":"Michael Laskin, Aravind Srinivas, and Pieter Abbeel. 2020. Curl: Contrastive unsupervised representations for reinforcement learning. In Int. Conf. on Machine Learning (ICML)."},{"key":"e_1_3_2_1_23_1","unstructured":"Jai-Ming Lin and Yao-Wen Chang. 2004. TCG-S: orthogonal coupling of P\/sup*\/- admissible representations for general floorplans."},{"key":"e_1_3_2_1_24_1","doi-asserted-by":"publisher","DOI":"10.1145\/3240765.3240769"},{"key":"e_1_3_2_1_25_1","volume-title":"UFO: Unified convex optimization algorithms for fixed-outline floorplanning considering pre-placed modules","author":"Lin Jai-Ming","year":"2011","unstructured":"Jai-Ming Lin and Zhi-Xiong Hung. 2011. UFO: Unified convex optimization algorithms for fixed-outline floorplanning considering pre-placed modules. IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems (TCAD) (2011)."},{"key":"e_1_3_2_1_26_1","volume-title":"Implementation Matters in Deep Policy Gradients: A Case Study on PPO and TRPO. In Int. Conf. on Learning Representations (ICLR).","author":"Shibani","unstructured":"Shibani Santurkar et al. Logan Engstrom, Andrew Ilyas. 2020. Implementation Matters in Deep Policy Gradients: A Case Study on PPO and TRPO. In Int. Conf. on Learning Representations (ICLR)."},{"key":"e_1_3_2_1_27_1","unstructured":"Azalia Mirhoseini Anna Goldie Mustafa Yazgan et al. 2021. Chip placement with deep reinforcement learning. Nature (2021)."},{"key":"e_1_3_2_1_28_1","doi-asserted-by":"crossref","unstructured":"Hiroshi Murata Kunihiro Fujiyoshi Shigetoshi Nakatake and Yoji Kajitani. 1996. VLSI module placement based on rectangle-packing by the sequence-pair.","DOI":"10.1109\/43.552084"},{"key":"e_1_3_2_1_29_1","volume-title":"Proc. of the 32nd Int. Conf. on Machine Learning (ICML).","author":"Schulman John","year":"2015","unstructured":"John Schulman, Sergey Levine, Pieter Abbeel, Michael Jordan, and Philipp Moritz. 2015. Trust Region Policy Optimization. In Proc. of the 32nd Int. Conf. on Machine Learning (ICML)."},{"key":"e_1_3_2_1_30_1","volume-title":"Int. Conf. on Learning Representations (ICLR).","author":"Schulman John","year":"2016","unstructured":"John Schulman, Philipp Moritz, Sergey Levine, Michael Jordan, and Pieter Abbeel. 2016. High-dimensional continuous control using generalized advantage estimation. In Int. Conf. on Learning Representations (ICLR)."},{"key":"e_1_3_2_1_31_1","unstructured":"John Schulman Filip Wolski Prafulla Dhariwal Alec Radford and Oleg Klimov. 2017. Proximal Policy Optimization Algorithms. (2017)."},{"key":"e_1_3_2_1_32_1","volume-title":"Proc. Adv. Neural Inf. Proc. Systems (NIPS).","author":"Schwarzer Max","year":"2021","unstructured":"Max et al. Schwarzer. 2021. Pretraining representations for data-efficient reinforcement learning. Proc. Adv. Neural Inf. Proc. Systems (NIPS)."},{"key":"e_1_3_2_1_33_1","doi-asserted-by":"crossref","unstructured":"K. Shahookar and P. Mazumder. 1991. VLSI Cell Placement Techniques. ACM Comput. Surv. (1991).","DOI":"10.1145\/103724.103725"},{"key":"e_1_3_2_1_34_1","volume-title":"Int. Conf. on Machine Learning (ICML).","author":"Stooke Adam","year":"2021","unstructured":"Adam Stooke, Kimin Lee, Pieter Abbeel, and Michael Laskin. 2021. Decoupling representation learning from reinforcement learning. In Int. Conf. on Machine Learning (ICML)."},{"key":"e_1_3_2_1_35_1","volume-title":"Representation learning with contrastive predictive coding. arXiv e-prints","author":"den Oord Aaron Van","year":"2018","unstructured":"Aaron Van den Oord, Yazhe Li, and Oriol Vinyals. 2018. Representation learning with contrastive predictive coding. arXiv e-prints (2018)."},{"key":"e_1_3_2_1_36_1","volume-title":"2020 57th ACM\/IEEE Design Automation Conference (DAC).","author":"Jiacheng Yang Linxiao Shen Kuan Wang","year":"2020","unstructured":"Kuan Wang Jiacheng Yang Linxiao Shen Nan Sun Hae-Seung Lee Wang, Hanrui and Song Han. 2020. GCN-RL circuit designer: Transferable transistor sizing with graph neural networks and reinforcement learning.. In 2020 57th ACM\/IEEE Design Automation Conference (DAC)."},{"key":"e_1_3_2_1_37_1","volume-title":"Int. Conf. on Learning Representations (ICLR).","author":"Wang Tingwu","year":"2018","unstructured":"Tingwu Wang, Renjie Liao, Jimmy Ba, and Sanja Fidler. 2018. Nervenet: Learning structured policy with graph neural networks. In Int. Conf. on Learning Representations (ICLR)."},{"key":"e_1_3_2_1_38_1","volume-title":"Combining the ant system algorithm and simulated annealing for 3D\/2D fixed-outline floorplanning. Applied Soft Computing","author":"Xu Qi","year":"2016","unstructured":"Qi Xu, Song Chen, and Bin Li. 2016. Combining the ant system algorithm and simulated annealing for 3D\/2D fixed-outline floorplanning. Applied Soft Computing (2016)."},{"key":"e_1_3_2_1_39_1","volume-title":"GoodFloorplan: Graph Convolutional Network and Reinforcement Learning Based Floorplanning","author":"Xu Qi","year":"2021","unstructured":"Qi Xu, Hao Geng, Song Chen, Bo Yuan, Cheng Zhuo, Yi Kang, and Xiaoqing Wen. 2021. GoodFloorplan: Graph Convolutional Network and Reinforcement Learning Based Floorplanning. IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems (TCAD) (2021)."}],"event":{"name":"KDD '22: The 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining","location":"Washington DC USA","acronym":"KDD '22","sponsor":["SIGMOD ACM Special Interest Group on Management of Data","SIGKDD ACM Special Interest Group on Knowledge Discovery in Data"]},"container-title":["Proceedings of the 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining"],"original-title":[],"link":[{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3534678.3539220","content-type":"unspecified","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.1145\/3534678.3539220","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,6,17]],"date-time":"2025-06-17T18:59:58Z","timestamp":1750186798000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3534678.3539220"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022,8,14]]},"references-count":39,"alternative-id":["10.1145\/3534678.3539220","10.1145\/3534678"],"URL":"https:\/\/doi.org\/10.1145\/3534678.3539220","relation":{},"subject":[],"published":{"date-parts":[[2022,8,14]]},"assertion":[{"value":"2022-08-14","order":3,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}]}}