ICML 2021 — accepted papers
ICML 2021 is the 2021 edition of the International Conference on Machine Learning (ICML). OpenAlex lists 196 papers of it; our library holds 2 with our summaries. Below: the most cited papers, every accepted paper, and ours with their topics, authors and institutions.
Most cited papers
- SimAM: A Simple, Parameter-Free Attention Module for Convolutional Neural Networks ↗Lingxiao Yang, Ru‐Yuan Zhang, Lida Li et al.638 citations
- HAWQ-V3: Dyadic Neural Network Quantization ↗Zhewei Yao, Zhen Dong, Zhangcheng Zheng et al.37 citations
- LEGO: Latent Execution-Guided Reasoning for Multi-Hop Question Answering on Knowledge Graphs ↗Hongyu Ren, Hanjun Dai, Bo Dai et al.31 citations
- Representation Subspace Distance for Domain Adaptation Regression ↗Xinyang Chen, Sinan Wang, Jianmin Wang et al.29 citations
- Ditto: Fair and Robust Federated Learning Through Personalization ↗Tian Li, Shengyuan Hu, Ahmad Beirami et al.22 citations
- Inferring Latent Dynamics Underlying Neural Population Activity via Neural Differential Equations ↗Timothy Kim, Thomas Zhihao Luo, Jonathan W. Pillow et al.19 citations
- Accelerating Safe Reinforcement Learning with Constraint-mismatched Baseline Policies ↗Jimmy Jimmy, Justinian P. Rosca, Karthik Narasimhan et al.18 citations
- RAD-TTS: Parallel Flow-Based TTS with Robust Alignment Learning and Diverse Synthesis ↗Kevin J. Shih, Rafael Valle, Rohan Badlani et al.18 citations
- Synthesizer: Rethinking Self-Attention for Transformer Models ↗Yi Tay, Dara Bahri, Donald Metzler et al.17 citations
- Dissecting Supervised Constrastive Learning ↗Florian Gräf, Christoph D. Hofer, Marc Niethammer et al.15 citations
All accepted papers (196)
- SimAM: A Simple, Parameter-Free Attention Module for Convolutional Neural Networks ↗Lingxiao Yang, Ru‐Yuan Zhang, Lida Li et al.638 citations
- HAWQ-V3: Dyadic Neural Network Quantization ↗Zhewei Yao, Zhen Dong, Zhangcheng Zheng et al.37 citations
- LEGO: Latent Execution-Guided Reasoning for Multi-Hop Question Answering on Knowledge Graphs ↗Hongyu Ren, Hanjun Dai, Bo Dai et al.31 citations
- Representation Subspace Distance for Domain Adaptation Regression ↗Xinyang Chen, Sinan Wang, Jianmin Wang et al.29 citations
- Ditto: Fair and Robust Federated Learning Through Personalization ↗Tian Li, Shengyuan Hu, Ahmad Beirami et al.22 citations
- Inferring Latent Dynamics Underlying Neural Population Activity via Neural Differential Equations ↗Timothy Kim, Thomas Zhihao Luo, Jonathan W. Pillow et al.19 citations
- Accelerating Safe Reinforcement Learning with Constraint-mismatched Baseline Policies ↗Jimmy Jimmy, Justinian P. Rosca, Karthik Narasimhan et al.18 citations
- RAD-TTS: Parallel Flow-Based TTS with Robust Alignment Learning and Diverse Synthesis ↗Kevin J. Shih, Rafael Valle, Rohan Badlani et al.18 citations
- Synthesizer: Rethinking Self-Attention for Transformer Models ↗Yi Tay, Dara Bahri, Donald Metzler et al.17 citations
- Dissecting Supervised Constrastive Learning ↗Florian Gräf, Christoph D. Hofer, Marc Niethammer et al.15 citations
- How Does Loss Function Affect Generalization Performance of Deep Learning? Application to Human Age Estimation ↗Ali Akbari, Muhammad Awais, Manijeh Bashar et al.14 citations
- When Does Data Augmentation Help With Membership Inference Attacks ↗Yiğitcan Kaya, Tudor Dumitraş14 citations
- Modelling Behavioural Diversity for Learning in Open-Ended Games ↗Nicolas Perez-Nieves, Yaodong Yang, Oliver Slumbers et al.13 citations
- One Pass Late Fusion Multi-view Clustering ↗Xinwang Liu, Li Liu, Qing Liao et al.13 citations
- SiameseXML: Siamese Networks meet Extreme Classifiers with 100M Labels ↗Kunal Dahiya, Ananye Agarwal, Deepak Saini et al.13 citations
- AutoAttend: Automated Attention Representation Search ↗Chaoyu Guan, Xin Wang, Wenwu Zhu11 citations
- Federated Learning under Arbitrary Communication Patterns ↗Dmitrii Avdiukhin, Shiva Prasad Kasiviswanathan11 citations
- Helper-based Adversarial Training: Reducing Excessive Margin to Achieve a Better Accuracy vs. Robustness Trade-off ↗Rahul Rade, Seyed-Mohsen Moosavi-Dezfooli11 citations
- PipeTransformer: Automated Elastic Pipelining for Distributed Training of Large-scale Models ↗Chaoyang He, Li Shen, Mahdi Soltanolkotabi et al.11 citations
- Revisiting Rainbow: Promoting more insightful and inclusive deep reinforcement learning research ↗Johan Obando-Ceron, Pablo Samuel Castro11 citations
- Improved OOD Generalization via Adversarial Training and Pretraing ↗Mingyang Yi, Lu Hou, Jiacheng Sun et al.10 citations
- Sharper Generalization Bounds for Clustering ↗Shaojie Li, Yong Liu10 citations
- Understanding and Mitigating Accuracy Disparity in Regression ↗Jianfeng Chi, Han Zhao, Geoff Gordon et al.10 citations
- Double-Win Quant: Aggressively Winning Robustness of Quantized Deep Neural Networks via Random Precision Training and Inference ↗Yonggan Fu, Qixuan Yu, Meng Li et al.9 citations
- Improving Gradient Regularization using Complex-Valued Neural Networks ↗Eric Yeats, Yiran Chen, Hai Helen Li9 citations
See all 196 papers in ICML 2021 — accepted papers →
Papers with our summary in our library (2)
- Scaling Up Visual and Vision-Language Representation Learning With Noisy Text SupervisionInternational Conference on Machine Learning (ICML)Chao Jia, Yinfei Yang, Ye Xia, et al.2021 · 1,615 citations
- I-BERT: Integer-only BERT QuantizationInternational Conference on Machine Learning (ICML)Sehoon Kim, Amir Gholami, Zhewei Yao, et al.2021 · 122 citations
Top topics
Vision & language (1)Efficient models & compression (1)
Fields
Computer Science (2)Arts and Humanities (1)
Top authors
🧑🔬Hieu Pham1 work here · 1,615 citations🧑🔬Quoc Viet Le1 work here · 1,615 citations🧑🔬Yinfei Yang1 work here · 1,615 citations🧑🔬Zhen Li1 work here · 1,615 citations🧑🔬Amir Gholami1 work here · 122 citations🧑🔬Kurt Keutzer1 work here · 122 citations🧑🔬Michael W. Mahoney1 work here · 122 citations🧑🔬Sehoon Kim1 work here · 122 citations🧑🔬Zhewei Yao1 work here · 122 citations
Top institutions
🏢GoogleMountain View ·
United States1 work here🎓University of California, BerkeleyBerkeley ·
United States1 work here
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