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Author Information
Hanson Wang (Facebook)
Yujun Lin (MIT)
Yixiao Duan (Beihang University)
Aditya Paliwal (Google)
AI Resident at Google NYC
Ameer Haj-Ali (University of California, Berkeley)
Ryan Marcus (MIT CSAIL)
Tom Hope (Hebrew University of Jerusalem)
Tom Hope is completing his PhD with Prof. Dafna Shahaf at the Hebrew University of Jerusalem, working on boosting innovation and creativity with methods at the intersection of NLP, weak supervision and crowdsourcing. His work received the KDD Best Research Paper and Best Student Paper awards, appeared in top venues (PNAS, KDD, WSDM, ECML/PKDD, IJCAI, CSCW), and received attention from the popular press (including “most thought-provoking paper of the week” from MIT Technology Review). In parallel to his PhD he also leads an applied AI research team at Intel (won Best Paper Award at ICPRAM). Tom holds an MSc in statistics, was selected as one of 200 young researchers to participate in the 7th Heidelberg Laureate Forum, and wrote a book for O’Reilly on TensorFlow.
Qiumin Xu (Google)
Nham Le (University of Waterloo)
Yuxiang Sun (University of South Carolina)
Ross Cutler (Microsoft)
Vikram Nathan (MIT)
Min Sun (Appier, Inc.)
More from the Same Authors
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2021 : TenSet: A Large-scale Program Performance Dataset for Learned Tensor Compilers »
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2022 Poster: 360-MLC: Multi-view Layout Consistency for Self-training and Hyper-parameter Tuning »
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2021 Poster: Delayed Gradient Averaging: Tolerate the Communication Latency for Federated Learning »
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2020 Poster: MCUNet: Tiny Deep Learning on IoT Devices »
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2020 Poster: Transferable Graph Optimizers for ML Compilers »
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2020 Spotlight: MCUNet: Tiny Deep Learning on IoT Devices »
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2020 Oral: Transferable Graph Optimizers for ML Compilers »
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2020 Poster: Mitigating Forgetting in Online Continual Learning via Instance-Aware Parameterization »
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2019 : Contributed Talk 6: Zero-Shot Learning for Fast Optimization of Computation Graphs »
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2019 : Contributed Talk 5: Predictive Precompute with Recurrent Neural Networks »
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2019 : Contributed Talk 4: Neural Hardware Architecture Search »
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2019 : Contributed Talk 3: Learned Multi-dimensional Indexing »
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2019 : Poster Session 1 »
Hongzi Mao · Vikram Nathan · Ioana Baldini · Viswanath Sivakumar · Haonan Wang · Vinoj Yasanga Jayasundara Magalle Hewa · Zhan Shi · Samuel Kaufman · Joyce Fang · Giulio Zhou · Jialin Ding · Hao He · Miles Lubin -
2019 Poster: Park: An Open Platform for Learning-Augmented Computer Systems »
Hongzi Mao · Parimarjan Negi · Akshay Narayan · Hanrui Wang · Jiacheng Yang · Haonan Wang · Ryan Marcus · Ravichandra Addanki · Mehrdad Khani Shirkoohi · Songtao He · Vikram Nathan · Frank Cangialosi · Shaileshh Venkatakrishnan · Wei-Hung Weng · Song Han · Tim Kraska · Dr.Mohammad Alizadeh -
2019 Poster: Point-Voxel CNN for Efficient 3D Deep Learning »
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2019 Spotlight: Point-Voxel CNN for Efficient 3D Deep Learning »
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