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ORCIDMaruan Al-Shedivat
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2020 – today
- 2022
[b1]Maruan Al-Shedivat:
Principles of Learning in Multitask Settings: A Probabilistic Perspective. Carnegie Mellon University, USA, 2022- 2021
- [c19]Maruan Al-Shedivat, Liam Li, Eric P. Xing, Ameet Talwalkar:
On Data Efficiency of Meta-learning. AISTATS 2021: 1369-1377 - [c18]Huaxiu Yao, Yingxin Wu, Maruan Al-Shedivat, Eric P. Xing:
Knowledge-Aware Meta-learning for Low-Resource Text Classification. EMNLP (1) 2021: 1814-1821 - [c17]Maruan Al-Shedivat, Jennifer Gillenwater, Eric P. Xing, Afshin Rostamizadeh:
Federated Learning via Posterior Averaging: A New Perspective and Practical Algorithms. ICLR 2021 - [c16]Bowen Tan, Zichao Yang, Maruan Al-Shedivat, Eric P. Xing, Zhiting Hu:
Progressive Generation of Long Text with Pretrained Language Models. NAACL-HLT 2021: 4313-4324 - [i20]Maruan Al-Shedivat, Liam Li, Eric Poe Xing, Ameet Talwalkar:
On Data Efficiency of Meta-learning. CoRR abs/2102.00127 (2021) - [i19]Jianyu Wang, Zachary Charles, Zheng Xu, Gauri Joshi, H. Brendan McMahan, Blaise Agüera y Arcas, Maruan Al-Shedivat, Galen Andrew, Salman Avestimehr, Katharine Daly, Deepesh Data, Suhas N. Diggavi, Hubert Eichner, Advait Gadhikar, Zachary Garrett, Antonious M. Girgis, Filip Hanzely, Andrew Hard, Chaoyang He, Samuel Horváth
, Zhouyuan Huo, Alex Ingerman, Martin Jaggi, Tara Javidi, Peter Kairouz, Satyen Kale, Sai Praneeth Karimireddy, Jakub Konecný, Sanmi Koyejo, Tian Li, Luyang Liu, Mehryar Mohri, Hang Qi, Sashank J. Reddi, Peter Richtárik, Karan Singhal, Virginia Smith, Mahdi Soltanolkotabi, Weikang Song, Ananda Theertha Suresh, Sebastian U. Stich, Ameet Talwalkar, Hongyi Wang, Blake E. Woodworth, Shanshan Wu, Felix X. Yu, Honglin Yuan, Manzil Zaheer, Mi Zhang, Tong Zhang, Chunxiang Zheng, Chen Zhu, Wennan Zhu:
A Field Guide to Federated Optimization. CoRR abs/2107.06917 (2021) - [i18]Huaxiu Yao, Yingxin Wu, Maruan Al-Shedivat, Eric P. Xing:
Knowledge-Aware Meta-learning for Low-Resource Text Classification. CoRR abs/2109.04707 (2021) - 2020
- [j3]Maruan Al-Shedivat, Avinava Dubey, Eric P. Xing:
Contextual Explanation Networks. J. Mach. Learn. Res. 21: 194:1-194:44 (2020) - [c15]Gregory Plumb, Maruan Al-Shedivat, Ángel Alexander Cabrera, Adam Perer, Eric P. Xing, Ameet Talwalkar:
Regularizing Black-box Models for Improved Interpretability. NeurIPS 2020 - [i17]Emmanouil Antonios Platanios, Maruan Al-Shedivat, Eric P. Xing, Tom M. Mitchell:
Learning from Imperfect Annotations. CoRR abs/2004.03473 (2020) - [i16]Bowen Tan, Zichao Yang, Maruan Al-Shedivat, Eric P. Xing, Zhiting Hu:
Progressive Generation of Long Text. CoRR abs/2006.15720 (2020) - [i15]Maruan Al-Shedivat, Jennifer Gillenwater, Eric P. Xing, Afshin Rostamizadeh:
Federated Learning via Posterior Averaging: A New Perspective and Practical Algorithms. CoRR abs/2010.05273 (2020)
2010 – 2019
- 2019
- [c14]Jingkai Mao, Jakob N. Foerster, Tim Rocktäschel, Maruan Al-Shedivat, Gregory Farquhar, Shimon Whiteson:
A Baseline for Any Order Gradient Estimation in Stochastic Computation Graphs. ICML 2019: 4343-4351 - [c13]Maruan Al-Shedivat, Ankur P. Parikh:
Consistency by Agreement in Zero-Shot Neural Machine Translation. NAACL-HLT (1) 2019: 1184-1197 - [i14]Gregory Plumb, Maruan Al-Shedivat, Eric P. Xing, Ameet Talwalkar:
Regularizing Black-box Models for Improved Interpretability. CoRR abs/1902.06787 (2019) - [i13]Maruan Al-Shedivat, Ankur P. Parikh:
Consistency by Agreement in Zero-shot Neural Machine Translation. CoRR abs/1904.02338 (2019) - [i12]Gregory Plumb, Maruan Al-Shedivat, Eric P. Xing, Ameet Talwalkar:
Regularizing Black-box Models for Improved Interpretability (HILL 2019 Version). CoRR abs/1906.01431 (2019) - 2018
- [c12]Jakob N. Foerster, Richard Y. Chen, Maruan Al-Shedivat, Shimon Whiteson, Pieter Abbeel, Igor Mordatch:
Learning with Opponent-Learning Awareness. AAMAS 2018: 122-130 - [c11]Aditya Grover, Maruan Al-Shedivat, Jayesh K. Gupta, Yuri Burda, Harrison Edwards:
Evaluating Generalization in Multiagent Systems using Agent-Interaction Graphs. AAMAS 2018: 1944-1946 - [c10]Maruan Al-Shedivat, Trapit Bansal, Yura Burda, Ilya Sutskever, Igor Mordatch, Pieter Abbeel:
Continuous Adaptation via Meta-Learning in Nonstationary and Competitive Environments. ICLR 2018 - [c9]Jakob N. Foerster, Gregory Farquhar, Maruan Al-Shedivat, Tim Rocktäschel, Eric P. Xing, Shimon Whiteson:
DiCE: The Infinitely Differentiable Monte-Carlo Estimator. ICLR (Workshop) 2018 - [c8]Jakob N. Foerster, Gregory Farquhar, Maruan Al-Shedivat, Tim Rocktäschel, Eric P. Xing, Shimon Whiteson:
DiCE: The Infinitely Differentiable Monte Carlo Estimator. ICML 2018: 1524-1533 - [c7]Aditya Grover, Maruan Al-Shedivat, Jayesh K. Gupta, Yuri Burda, Harrison Edwards:
Learning Policy Representations in Multiagent Systems. ICML 2018: 1797-1806 - [i11]Maruan Al-Shedivat, Avinava Dubey, Eric P. Xing:
The Intriguing Properties of Model Explanations. CoRR abs/1801.09808 (2018) - [i10]Maruan Al-Shedivat, Avinava Dubey, Eric P. Xing:
Personalized Survival Prediction with Contextual Explanation Networks. CoRR abs/1801.09810 (2018) - [i9]Jakob N. Foerster, Gregory Farquhar, Maruan Al-Shedivat, Tim Rocktäschel, Eric P. Xing, Shimon Whiteson:
DiCE: The Infinitely Differentiable Monte-Carlo Estimator. CoRR abs/1802.05098 (2018) - [i8]Aditya Grover, Maruan Al-Shedivat, Jayesh K. Gupta, Yura Burda, Harrison Edwards:
Learning Policy Representations in Multiagent Systems. CoRR abs/1806.06464 (2018) - [i7]Maruan Al-Shedivat, Lisa Lee, Ruslan Salakhutdinov, Eric P. Xing:
On the Complexity of Exploration in Goal-Driven Navigation. CoRR abs/1811.06889 (2018) - 2017
- [j2]Maruan Al-Shedivat, Andrew Gordon Wilson, Yunus Saatchi, Zhiting Hu, Eric P. Xing:
Learning Scalable Deep Kernels with Recurrent Structure. J. Mach. Learn. Res. 18: 82:1-82:37 (2017) - [i6]Maruan Al-Shedivat, Avinava Dubey, Eric P. Xing:
Contextual Explanation Networks. CoRR abs/1705.10301 (2017) - [i5]Jakob N. Foerster, Richard Y. Chen, Maruan Al-Shedivat, Shimon Whiteson, Pieter Abbeel, Igor Mordatch:
Learning with Opponent-Learning Awareness. CoRR abs/1709.04326 (2017) - [i4]Maruan Al-Shedivat, Trapit Bansal, Yuri Burda, Ilya Sutskever, Igor Mordatch, Pieter Abbeel:
Continuous Adaptation via Meta-Learning in Nonstationary and Competitive Environments. CoRR abs/1710.03641 (2017) - 2016
- [c6]Moustapha Cissé, Maruan Al-Shedivat, Samy Bengio:
ADIOS: Architectures Deep In Output Space. ICML 2016: 2770-2779 - [c5]Rawan Naous, Maruan Al-Shedivat, Emre Neftci, Gert Cauwenberghs, Khaled Nabil Salama:
Stochastic synaptic plasticity with memristor crossbar arrays. ISCAS 2016: 2078-2081 - [c4]Kirthevasan Kandasamy, Maruan Al-Shedivat, Eric P. Xing:
Learning HMMs with Nonparametric Emissions via Spectral Decompositions of Continuous Matrices. NIPS 2016: 2865-2873 - [i3]Kirthevasan Kandasamy, Maruan Al-Shedivat, Eric P. Xing:
Learning HMMs with Nonparametric Emissions via Spectral Decompositions of Continuous Matrices. CoRR abs/1609.06390 (2016) - [i2]Maruan Al-Shedivat, Andrew Gordon Wilson, Yunus Saatchi, Zhiting Hu, Eric P. Xing:
Learning Scalable Deep Kernels with Recurrent Structure. CoRR abs/1610.08936 (2016) - 2015
- [j1]Maruan Al-Shedivat, Rawan Naous, Gert Cauwenberghs, Khaled Nabil Salama:
Memristors Empower Spiking Neurons With Stochasticity. IEEE J. Emerg. Sel. Topics Circuits Syst. 5(2): 242-253 (2015) - [c3]Maruan Al-Shedivat, Rawan Naous, Emre Neftci, Gert Cauwenberghs, Khaled N. Salama:
Inherently stochastic spiking neurons for probabilistic neural computation. NER 2015: 356-359 - [c2]Maruan Al-Shedivat, Emre Neftci, Gert Cauwenberghs:
Learning Non-deterministic Representations with Energy-based Ensembles. ICLR (Workshop) 2015 - [i1]Emre Neftci, Bruno U. Pedroni, Siddharth Joshi, Maruan Al-Shedivat, Gert Cauwenberghs:
Unsupervised Learning in Synaptic Sampling Machines. CoRR abs/1511.04484 (2015) - 2014
- [c1]Maruan Al-Shedivat, Jim Jing-Yan Wang, Majed Alzahrani, Jianhua Z. Huang, Xin Gao:
Supervised Transfer Sparse Coding. AAAI 2014: 1665-1672
Coauthor Index
aka: Eric Poe Xing
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