{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2024,9,6]],"date-time":"2024-09-06T11:08:59Z","timestamp":1725620939253},"publisher-location":"New York, NY, USA","reference-count":19,"publisher":"ACM","content-domain":{"domain":["dl.acm.org"],"crossmark-restriction":true},"short-container-title":[],"published-print":{"date-parts":[[2021,10,21]]},"DOI":"10.1145\/3486001.3486244","type":"proceedings-article","created":{"date-parts":[[2021,10,22]],"date-time":"2021-10-22T15:57:44Z","timestamp":1634918264000},"page":"1-7","update-policy":"http:\/\/dx.doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":1,"title":["Towards Accelerating Offline RL based Recommender Systems"],"prefix":"10.1145","author":[{"given":"Mayank","family":"Mishra","sequence":"first","affiliation":[{"name":"TCS Research, India"}]},{"given":"Rekha","family":"Singhal","sequence":"additional","affiliation":[{"name":"TCS Research, India"}]},{"given":"Ravi","family":"Singh","sequence":"additional","affiliation":[{"name":"TCS Research, India"}]}],"member":"320","published-online":{"date-parts":[[2021,10,22]]},"reference":[{"key":"e_1_3_2_1_1_1","unstructured":"M.\u00a0Mehdi Afsar Trafford Crump and Behrouz\u00a0H. Far. 2021. Reinforcement learning based recommender systems: A survey. CoRR abs\/2101.06286(2021). arxiv:2101.06286https:\/\/arxiv.org\/abs\/2101.06286 M.\u00a0Mehdi Afsar Trafford Crump and Behrouz\u00a0H. Far. 2021. Reinforcement learning based recommender systems: A survey. CoRR abs\/2101.06286(2021). arxiv:2101.06286https:\/\/arxiv.org\/abs\/2101.06286"},{"key":"e_1_3_2_1_2_1","unstructured":"Marc\u00a0G. Bellemare Will Dabney and R\u00e9mi Munos. 2017. A Distributional Perspective on Reinforcement Learning. arxiv:1707.06887\u00a0[cs.LG] Marc\u00a0G. Bellemare Will Dabney and R\u00e9mi Munos. 2017. A Distributional Perspective on Reinforcement Learning. arxiv:1707.06887\u00a0[cs.LG]"},{"volume-title":"Batch Reinforcement Learning in the Real World: A Survey. Offline RL Workshop, NeuroIPS(2020)","year":"2020","author":"Fu Yuwei","key":"e_1_3_2_1_3_1","unstructured":"Yuwei Fu , Wu Di , and Benoit Boulet . 2020 . Batch Reinforcement Learning in the Real World: A Survey. Offline RL Workshop, NeuroIPS(2020) . Yuwei Fu, Wu Di, and Benoit Boulet. 2020. Batch Reinforcement Learning in the Real World: A Survey. Offline RL Workshop, NeuroIPS(2020)."},{"key":"e_1_3_2_1_4_1","unstructured":"Scott Fujimoto Edoardo Conti Mohammad Ghavamzadeh and Joelle Pineau. 2019. Benchmarking Batch Deep Reinforcement Learning Algorithms. arxiv:1910.01708\u00a0[cs.LG] Scott Fujimoto Edoardo Conti Mohammad Ghavamzadeh and Joelle Pineau. 2019. Benchmarking Batch Deep Reinforcement Learning Algorithms. arxiv:1910.01708\u00a0[cs.LG]"},{"volume-title":"International Conference on Machine Learning. 2052\u20132062","year":"2019","author":"Fujimoto Scott","key":"e_1_3_2_1_5_1","unstructured":"Scott Fujimoto , David Meger , and Doina Precup . 2019 . Off-Policy Deep Reinforcement Learning without Exploration . In International Conference on Machine Learning. 2052\u20132062 . Scott Fujimoto, David Meger, and Doina Precup. 2019. Off-Policy Deep Reinforcement Learning without Exploration. In International Conference on Machine Learning. 2052\u20132062."},{"key":"e_1_3_2_1_6_1","unstructured":"Diksha Garg Priyanka Gupta Pankaj Malhotra Lovekesh Vig and Gautam Shroff. 2020. Batch-Constrained Distributional Reinforcement Learning for Session-based Recommendation. CoRR abs\/2012.08984(2020). arxiv:2012.08984https:\/\/arxiv.org\/abs\/2012.08984 Diksha Garg Priyanka Gupta Pankaj Malhotra Lovekesh Vig and Gautam Shroff. 2020. Batch-Constrained Distributional Reinforcement Learning for Session-based Recommendation. CoRR abs\/2012.08984(2020). arxiv:2012.08984https:\/\/arxiv.org\/abs\/2012.08984"},{"volume-title":"NISER: Normalized Item and Session Representations with Graph Neural Networks. CoRR abs\/1909.04276(2019). arxiv:1909.04276http:\/\/arxiv.org\/abs\/1909.04276","year":"2019","author":"Gupta Priyanka","key":"e_1_3_2_1_7_1","unstructured":"Priyanka Gupta , Diksha Garg , Pankaj Malhotra , Lovekesh Vig , and Gautam Shroff . 2019 . NISER: Normalized Item and Session Representations with Graph Neural Networks. CoRR abs\/1909.04276(2019). arxiv:1909.04276http:\/\/arxiv.org\/abs\/1909.04276 Priyanka Gupta, Diksha Garg, Pankaj Malhotra, Lovekesh Vig, and Gautam Shroff. 2019. NISER: Normalized Item and Session Representations with Graph Neural Networks. CoRR abs\/1909.04276(2019). arxiv:1909.04276http:\/\/arxiv.org\/abs\/1909.04276"},{"key":"e_1_3_2_1_8_1","doi-asserted-by":"publisher","DOI":"10.1109\/BigData50022.2020.9378470"},{"key":"e_1_3_2_1_9_1","unstructured":"Sergey Levine Aviral Kumar George Tucker and Justin Fu. 2020. Offline Reinforcement Learning: Tutorial Review and Perspectives on Open Problems. arxiv:2005.01643\u00a0[cs.LG] Sergey Levine Aviral Kumar George Tucker and Justin Fu. 2020. Offline Reinforcement Learning: Tutorial Review and Perspectives on Open Problems. arxiv:2005.01643\u00a0[cs.LG]"},{"volume-title":"DEPLOYMENT-EFFICIENT REINFORCEMENT LEARNING VIA MODEL-BASED OFFLINE OPTIMIZATION. Offline RL Workshop, NeuroIPS(2020)","year":"2020","author":"Matsushima Tatsuya","key":"e_1_3_2_1_10_1","unstructured":"Tatsuya Matsushima , Hiroki Furuta , Yutaka Matsuo , Ofir Nachum , and Shixiang\u00a0Shane Gu . 2020 . DEPLOYMENT-EFFICIENT REINFORCEMENT LEARNING VIA MODEL-BASED OFFLINE OPTIMIZATION. Offline RL Workshop, NeuroIPS(2020) . Tatsuya Matsushima, Hiroki Furuta, Yutaka Matsuo, Ofir Nachum, and Shixiang\u00a0Shane Gu. 2020. DEPLOYMENT-EFFICIENT REINFORCEMENT LEARNING VIA MODEL-BASED OFFLINE OPTIMIZATION. Offline RL Workshop, NeuroIPS(2020)."},{"key":"e_1_3_2_1_11_1","unstructured":"Gregory\u00a0P. Meyer. 2020. An Alternative Probabilistic Interpretation of the Huber Loss. arxiv:1911.02088\u00a0[stat.ML] Gregory\u00a0P. Meyer. 2020. An Alternative Probabilistic Interpretation of the Huber Loss. arxiv:1911.02088\u00a0[stat.ML]"},{"key":"e_1_3_2_1_12_1","unstructured":"Louis Monier Jakub Kmec Alexandre Laterre Thomas Pierrot Valentin Courgeau Olivier Sigaud and Karim Beguir. 2020. Offline Reinforcement Learning Hands-On. CoRR abs\/2011.14379(2020). arxiv:2011.14379https:\/\/arxiv.org\/abs\/2011.14379 Louis Monier Jakub Kmec Alexandre Laterre Thomas Pierrot Valentin Courgeau Olivier Sigaud and Karim Beguir. 2020. Offline Reinforcement Learning Hands-On. CoRR abs\/2011.14379(2020). arxiv:2011.14379https:\/\/arxiv.org\/abs\/2011.14379"},{"volume-title":"Proceedings of the 13th USENIX Conference on Operating Systems Design and Implementation","year":"2018","author":"Moritz Philipp","key":"e_1_3_2_1_13_1","unstructured":"Philipp Moritz , Robert Nishihara , Stephanie Wang , Alexey Tumanov , Richard Liaw , Eric Liang , Melih Elibol , Zongheng Yang , William Paul , Michael\u00a0 I. Jordan , and Ion Stoica . 2018 . Ray: A Distributed Framework for Emerging AI Applications . In Proceedings of the 13th USENIX Conference on Operating Systems Design and Implementation ( Carlsbad, CA, USA) (OSDI\u201918). USENIX Association, USA, 561\u2013577. Philipp Moritz, Robert Nishihara, Stephanie Wang, Alexey Tumanov, Richard Liaw, Eric Liang, Melih Elibol, Zongheng Yang, William Paul, Michael\u00a0I. Jordan, and Ion Stoica. 2018. Ray: A Distributed Framework for Emerging AI Applications. In Proceedings of the 13th USENIX Conference on Operating Systems Design and Implementation (Carlsbad, CA, USA) (OSDI\u201918). USENIX Association, USA, 561\u2013577."},{"key":"e_1_3_2_1_14_1","unstructured":"Arun Nair Praveen Srinivasan Sam Blackwell Cagdas Alcicek Rory Fearon Alessandro\u00a0De Maria Vedavyas Panneershelvam Mustafa Suleyman Charles Beattie Stig Petersen Shane Legg Volodymyr Mnih Koray Kavukcuoglu and David Silver. 2015. Massively Parallel Methods for Deep Reinforcement Learning. arxiv:1507.04296\u00a0[cs.LG] Arun Nair Praveen Srinivasan Sam Blackwell Cagdas Alcicek Rory Fearon Alessandro\u00a0De Maria Vedavyas Panneershelvam Mustafa Suleyman Charles Beattie Stig Petersen Shane Legg Volodymyr Mnih Koray Kavukcuoglu and David Silver. 2015. Massively Parallel Methods for Deep Reinforcement Learning. arxiv:1507.04296\u00a0[cs.LG]"},{"key":"e_1_3_2_1_15_1","unstructured":"Tom\u00a0Le Paine Cosmin Paduraru Andrea Michi Caglar Gulcehre Konrad Zolna Alexander Novikov Ziyu Wang and Nando de Freitas. 2020. Hyperparameter Selection for Offline Reinforcement Learning. arxiv:2007.09055\u00a0[cs.LG] Tom\u00a0Le Paine Cosmin Paduraru Andrea Michi Caglar Gulcehre Konrad Zolna Alexander Novikov Ziyu Wang and Nando de Freitas. 2020. Hyperparameter Selection for Offline Reinforcement Learning. arxiv:2007.09055\u00a0[cs.LG]"},{"key":"e_1_3_2_1_16_1","doi-asserted-by":"publisher","DOI":"10.14778\/3213880.3213890"},{"volume-title":"Taming the Wild: A Unified Analysis of Hogwild-Style Algorithms. In Advances in Neural Information Processing Systems 28: Annual Conference on Neural Information Processing Systems 2015","year":"2015","author":"Sa Christopher\u00a0De","key":"e_1_3_2_1_17_1","unstructured":"Christopher\u00a0De Sa , Ce Zhang , Kunle Olukotun , and Christopher R\u00e9 . 2015 . Taming the Wild: A Unified Analysis of Hogwild-Style Algorithms. In Advances in Neural Information Processing Systems 28: Annual Conference on Neural Information Processing Systems 2015 , December 7-12, 2015, Montreal, Quebec, Canada, Corinna Cortes, Neil\u00a0D. Lawrence, Daniel\u00a0D. Lee, Masashi Sugiyama, and Roman Garnett (Eds.). 2674\u20132682. https:\/\/proceedings.neurips.cc\/paper\/ 2015\/hash\/98986c005e5def2da341b4e0627d4712-Abstract.html Christopher\u00a0De Sa, Ce Zhang, Kunle Olukotun, and Christopher R\u00e9. 2015. Taming the Wild: A Unified Analysis of Hogwild-Style Algorithms. In Advances in Neural Information Processing Systems 28: Annual Conference on Neural Information Processing Systems 2015, December 7-12, 2015, Montreal, Quebec, Canada, Corinna Cortes, Neil\u00a0D. Lawrence, Daniel\u00a0D. Lee, Masashi Sugiyama, and Roman Garnett (Eds.). 2674\u20132682. https:\/\/proceedings.neurips.cc\/paper\/2015\/hash\/98986c005e5def2da341b4e0627d4712-Abstract.html"},{"key":"e_1_3_2_1_18_1","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v33i01.3301346"},{"volume-title":"2020 USENIX Annual Technical Conference (USENIX ATC 20)","year":"2020","author":"Yuan Gina","key":"e_1_3_2_1_19_1","unstructured":"Gina Yuan , Shoumik Palkar , Deepak Narayanan , and Matei Zaharia . 2020 . Offload Annotations: Bringing Heterogeneous Computing to Existing Libraries and Workloads . In 2020 USENIX Annual Technical Conference (USENIX ATC 20) . USENIX Association, 293\u2013306. https:\/\/www.usenix.org\/conference\/atc20\/presentation\/yuan Gina Yuan, Shoumik Palkar, Deepak Narayanan, and Matei Zaharia. 2020. Offload Annotations: Bringing Heterogeneous Computing to Existing Libraries and Workloads. In 2020 USENIX Annual Technical Conference (USENIX ATC 20). USENIX Association, 293\u2013306. https:\/\/www.usenix.org\/conference\/atc20\/presentation\/yuan"}],"event":{"name":"AIMLSystems 2021: The First International Conference on AI-ML-Systems","acronym":"AIMLSystems 2021","location":"Bangalore India"},"container-title":["The First International Conference on AI-ML-Systems"],"original-title":[],"link":[{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.1145\/3486001.3486244","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2023,1,13]],"date-time":"2023-01-13T00:38:16Z","timestamp":1673570296000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3486001.3486244"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2021,10,21]]},"references-count":19,"alternative-id":["10.1145\/3486001.3486244","10.1145\/3486001"],"URL":"https:\/\/doi.org\/10.1145\/3486001.3486244","relation":{},"subject":[],"published":{"date-parts":[[2021,10,21]]},"assertion":[{"value":"2021-10-22","order":2,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}]}}