Hanlin Tang

According to our database, Hanlin Tang authored at least 44 papers between 2016 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of three.

2024

Span Graph Transformer for Document-Level Named Entity Recognition.

Hongli Mao, Xian-Ling Mao, Hanlin Tang, Yuming Shang, Heyan Huang

Proceedings of the Thirty-Eighth AAAI Conference on Artificial Intelligence, 2024

2023

Attribute-based multi-user collaborative searchable encryption in COVID-19.

Fan Zhao, Changgen Peng, Dequan Xu, Yicen Liu, Kun Niu, Hanlin Tang

Comput. Commun., May, 2023

SQL#: A Language for Maintainable and Debuggable Database Queries.

Yamin Hu, Hao Jiang, Hanlin Tang, Xin Lin, Zongyao Hu

Int. J. Softw. Eng. Knowl. Eng., 2023

EasyQuant: An Efficient Data-free Quantization Algorithm for LLMs.

Hanlin Tang, Yifu Sun, Decheng Wu, Kai Liu, Jianchen Zhu, Zhanhui Kang

Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing, 2023

2022

MKQ-BERT: Quantized BERT with 4-bits Weights and Activations.

Hanlin Tang, Xipeng Zhang, Kai Liu, Jianchen Zhu, Zhanhui Kang

CoRR, 2022

1-bit LAMB: Communication Efficient Large-Scale Large-Batch Training with LAMB's Convergence Speed.

Conglong Li, Ammar Ahmad Awan, Hanlin Tang, Samyam Rajbhandari, Yuxiong He

Proceedings of the 29th IEEE International Conference on High Performance Computing, 2022

2021

PASTO: Strategic Parameter Optimization in Recommendation Systems - Probabilistic is Better than Deterministic.

Weicong Ding, Hanlin Tang, Jingshuo Feng, Lei Yuan, Sen Yang, Guangxu Yang, Jie Zheng, Jing Wang, Qiang Su, Dong Zheng, Xuezhong Qiu, Yongqi Liu, Yuxuan Chen, Yang Liu, Chao Song, Dongying Kong, Kai Ren, Peng Jiang, Qiao Lian, Ji Liu

CoRR, 2021

Syntactic Perturbations Reveal Representational Correlates of Hierarchical Phrase Structure in Pretrained Language Models.

Matteo Alleman, Jonathan Mamou, Miguel A. Del Rio, Hanlin Tang, Yoon Kim, SueYeon Chung

Proceedings of the 6th Workshop on Representation Learning for NLP, 2021

ErrorCompensatedX: error compensation for variance reduced algorithms.

Hanlin Tang, Yao Li, Ji Liu, Ming Yan

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

1-bit Adam: Communication Efficient Large-Scale Training with Adam's Convergence Speed.

Hanlin Tang, Shaoduo Gan, Ammar Ahmad Awan, Samyam Rajbhandari, Conglong Li, Xiangru Lian, Ji Liu, Ce Zhang, Yuxiong He

Proceedings of the 38th International Conference on Machine Learning, 2021

On the geometry of generalization and memorization in deep neural networks.

Cory Stephenson, Suchismita Padhy, Abhinav Ganesh, Yue Hui, Hanlin Tang, SueYeon Chung

Proceedings of the 9th International Conference on Learning Representations, 2021

Optimizing Memory Placement using Evolutionary Graph Reinforcement Learning.

Shauharda Khadka, Estelle Aflalo, Mattias Marder, Avrech Ben-David, Santiago Miret, Shie Mannor, Tamir Hazan, Hanlin Tang, Somdeb Majumdar

Proceedings of the 9th International Conference on Learning Representations, 2021

What Did You Refer to? Evaluating Co-References in Dialogue.

Weinan Zhang, Yue Zhang, Hanlin Tang, Zhengyu Zhao, Caihai Zhu, Ting Liu

Proceedings of the Findings of the Association for Computational Linguistics: ACL/IJCNLP 2021, 2021

2020

MLPerf: An Industry Standard Benchmark Suite for Machine Learning Performance.

Peter Mattson, Hanlin Tang, Gu-Yeon Wei, Carole-Jean Wu, Vijay Janapa Reddi, Christine Cheng, Cody Coleman, Greg Diamos, David Kanter, Paulius Micikevicius, David A. Patterson, Guenther Schmuelling

IEEE Micro, 2020

APMSqueeze: A Communication Efficient Adam-Preconditioned Momentum SGD Algorithm.

Hanlin Tang, Shaoduo Gan, Samyam Rajbhandari, Xiangru Lian, Ji Liu, Yuxiong He, Ce Zhang

CoRR, 2020

LSTM-based argument recommendation for non-API methods.

Guangjie Li, Hui Liu, Ge Li, Sijie Shen, Hanlin Tang

Sci. China Inf. Sci., 2020

A Span-Based Distantly Supervised NER with Self-learning.

Hongli Mao, Hanlin Tang, Wen Zhang, Heyan Huang, Xian-Ling Mao

Proceedings of the Natural Language Processing and Chinese Computing, 2020

ATRW: A Benchmark for Amur Tiger Re-identification in the Wild.

Shuyuan Li, Jianguo Li, Hanlin Tang, Rui Qian, Weiyao Lin

Proceedings of the MM '20: The 28th ACM International Conference on Multimedia, 2020

MLPerf Training Benchmark.

Peter Mattson, Christine Cheng, Gregory F. Diamos, Cody Coleman, Paulius Micikevicius, David A. Patterson, Hanlin Tang, Gu-Yeon Wei, Peter Bailis, Victor Bittorf, David Brooks, Dehao Chen, Debo Dutta, Udit Gupta, Kim M. Hazelwood, Andy Hock, Xinyuan Huang, Daniel Kang, David Kanter, Naveen Kumar, Jeffery Liao, Deepak Narayanan, Tayo Oguntebi, Gennady Pekhimenko, Lillian Pentecost, Vijay Janapa Reddi, Taylor Robie, Tom St. John, Carole-Jean Wu, Lingjie Xu, Cliff Young, Matei Zaharia

Proceedings of Machine Learning and Systems 2020, 2020

MLPerf Inference Benchmark.

Vijay Janapa Reddi, Christine Cheng, David Kanter, Peter Mattson, Guenther Schmuelling, Carole-Jean Wu, Brian Anderson, Maximilien Breughe, Mark Charlebois, William Chou, Ramesh Chukka, Cody Coleman, Sam Davis, Pan Deng, Greg Diamos, Jared Duke, Dave Fick, J. Scott Gardner, Itay Hubara, Sachin Idgunji, Thomas B. Jablin, Jeff Jiao, Tom St. John, Pankaj Kanwar, David Lee, Jeffery Liao, Anton Lokhmotov, Francisco Massa, Peng Meng, Paulius Micikevicius, Colin Osborne, Gennady Pekhimenko, Arun Tejusve Raghunath Rajan, Dilip Sequeira, Ashish Sirasao, Fei Sun, Hanlin Tang, Michael Thomson, Frank Wei, Ephrem Wu, Lingjie Xu, Koichi Yamada, Bing Yu, George Yuan, Aaron Zhong, Peizhao Zhang, Yuchen Zhou

Proceedings of the 47th ACM/IEEE Annual International Symposium on Computer Architecture, 2020

Emergence of Separable Manifolds in Deep Language Representations.

Jonathan Mamou, Hang Le, Miguel Del Rio, Cory Stephenson, Hanlin Tang, Yoon Kim, SueYeon Chung

Proceedings of the 37th International Conference on Machine Learning, 2020

Shifted and Squeezed 8-bit Floating Point format for Low-Precision Training of Deep Neural Networks.

Léopold Cambier, Anahita Bhiwandiwalla, Ting Gong, Oguz H. Elibol, Mehran Nekuii, Hanlin Tang

Proceedings of the 8th International Conference on Learning Representations, 2020

Mimic The Raw Domain: Accelerating Action Recognition in the Compressed Domain.

Barak Battash, Haim Barad, Hanlin Tang, Amit Bleiweiss

Proceedings of the 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2020

2019

Central Server Free Federated Learning over Single-sided Trust Social Networks.

Chaoyang He, Conghui Tan, Hanlin Tang, Shuang Qiu, Ji Liu

CoRR, 2019

MLPerf Training Benchmark.

Peter Mattson, Christine Cheng, Cody Coleman, Greg Diamos, Paulius Micikevicius, David A. Patterson, Hanlin Tang, Gu-Yeon Wei, Peter Bailis, Victor Bittorf, David Brooks, Dehao Chen, Debojyoti Dutta, Udit Gupta, Kim M. Hazelwood, Andrew Hock, Xinyuan Huang, Bill Jia, Daniel Kang, David Kanter, Naveen Kumar, Jeffery Liao, Guokai Ma, Deepak Narayanan, Tayo Oguntebi, Gennady Pekhimenko, Lillian Pentecost, Vijay Janapa Reddi, Taylor Robie, Tom St. John, Carole-Jean Wu, Lingjie Xu, Cliff Young, Matei Zaharia

CoRR, 2019

Using Image Priors to Improve Scene Understanding.

Brigit Schroeder, Hanlin Tang, Alexandre Alahi

CoRR, 2019

DeepSqueeze: Parallel Stochastic Gradient Descent with Double-Pass Error-Compensated Compression.

Hanlin Tang, Xiangru Lian, Shuang Qiu, Lei Yuan, Ce Zhang, Tong Zhang, Ji Liu

CoRR, 2019

Generalization to Novel Objects using Prior Relational Knowledge.

Varun Kumar Vijay, Abhinav Ganesh, Hanlin Tang, Arjun K. Bansal

CoRR, 2019

Amur Tiger Re-identification in the Wild.

Shuyuan Li, Jianguo Li, Weiyao Lin, Hanlin Tang

CoRR, 2019

DoubleSqueeze: Parallel Stochastic Gradient Descent with Double-Pass Error-Compensated Compression.

Hanlin Tang, Xiangru Lian, Tong Zhang, Ji Liu

CoRR, 2019

Using Scene Graph Context to Improve Image Generation.

Subarna Tripathi, Anahita Bhiwandiwalla, Alexei Bastidas, Hanlin Tang

CoRR, 2019

Untangling in Invariant Speech Recognition.

Cory Stephenson, Jenelle Feather, Suchismita Padhy, Oguz H. Elibol, Hanlin Tang, Josh H. McDermott, SueYeon Chung

Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

Distributed Learning over Unreliable Networks.

Chen Yu, Hanlin Tang, Cédric Renggli, Simon Kassing, Ankit Singla, Dan Alistarh, Ce Zhang, Ji Liu

Proceedings of the 36th International Conference on Machine Learning, 2019

DoubleSqueeze: Parallel Stochastic Gradient Descent with Double-pass Error-Compensated Compression.

Hanlin Tang, Chen Yu, Xiangru Lian, Tong Zhang, Ji Liu

Proceedings of the 36th International Conference on Machine Learning, 2019

Triplet-Aware Scene Graph Embeddings.

Brigit Schroeder, Subarna Tripathi, Hanlin Tang

Proceedings of the 2019 IEEE/CVF International Conference on Computer Vision Workshops, 2019

SpaceNet MVOI: A Multi-View Overhead Imagery Dataset.

Nicholas Weir, David Lindenbaum, Alexei Bastidas, Adam Van Etten, Varun Kumar Vijay, Sean McPherson, Jacob Shermeyer, Hanlin Tang

Proceedings of the 2019 IEEE/CVF International Conference on Computer Vision, 2019

Compact Scene Graphs for Layout Composition and Patch Retrieval.

Subarna Tripathi, Sharath Nittur Sridhar, Sairam Sundaresan, Hanlin Tang

Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition Workshops, 2019

Channel Attention Networks.

Alexei Bastidas, Hanlin Tang

Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition Workshops, 2019

2018

Decentralization Meets Quantization.

Hanlin Tang, Ce Zhang, Shaoduo Gan, Tong Zhang, Ji Liu

CoRR, 2018

Communication Compression for Decentralized Training.

Hanlin Tang, Shaoduo Gan, Ce Zhang, Tong Zhang, Ji Liu

Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018

D²: Decentralized Training over Decentralized Data.

Hanlin Tang, Xiangru Lian, Ming Yan, Ce Zhang, Ji Liu

Proceedings of the 35th International Conference on Machine Learning, 2018

Analysis on Convergence of Stochastic Processes in Cloud Computing Models.

Junhong Nie, Hanlin Tang, Jingxuan Wei

Proceedings of the 14th International Conference on Computational Intelligence and Security, 2018

2017

Recurrent computations for visual pattern completion.

Hanlin Tang, Bill Lotter, Martin Schrimpf, Ana Paredes, Josue Ortega Caro, Walter Hardesty, David D. Cox, Gabriel Kreiman

CoRR, 2017

2016

A machine learning approach to predict episodic memory formation.

Hanlin Tang, Jedediah Singer, Matias Ison, Gnel Pivazyan, Melissa Romaine, Elizabeth Meller, Victoria Perron, Marlise Arlellano, Gabriel Kreiman, Adriana Boulin, Rosa Frias, James Carroll, Sarah Dowcett

Proceedings of the 2016 Annual Conference on Information Science and Systems, 2016