Nan Ding

According to our database, Nan Ding authored at least 44 papers between 2006 and 2025.

Collaborative distances:

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

2025

Graders should cheat: privileged information enables expert-level automated evaluations.

Jin Peng Zhou, Sébastien M. R. Arnold, Nan Ding, Kilian Q. Weinberger, Nan Hua, Fei Sha

CoRR, February, 2025

2024

CausalLM is not optimal for in-context learning.

Nan Ding, Tomer Levinboim, Jialin Wu, Sebastian Goodman, Radu Soricut

Proceedings of the Twelfth International Conference on Learning Representations, 2024

2023

PaLI: A Jointly-Scaled Multilingual Language-Image Model.

Xi Chen, Xiao Wang, Soravit Changpinyo, A. J. Piergiovanni, Piotr Padlewski, Daniel Salz, Sebastian Goodman, Adam Grycner, Basil Mustafa, Lucas Beyer, Alexander Kolesnikov, Joan Puigcerver, Nan Ding, Keran Rong, Hassan Akbari, Gaurav Mishra, Linting Xue, Ashish V. Thapliyal, James Bradbury, Weicheng Kuo

Proceedings of the Eleventh International Conference on Learning Representations, 2023

Improving Robust Generalization by Direct PAC-Bayesian Bound Minimization.

Zifan Wang, Nan Ding, Tomer Levinboim, Xi Chen, Radu Soricut

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2023

2022

PaLI: A Jointly-Scaled Multilingual Language-Image Model.

Xi Chen, Xiao Wang, Soravit Changpinyo, A. J. Piergiovanni, Piotr Padlewski, Daniel Salz, Sebastian Goodman, Adam Grycner, Basil Mustafa, Lucas Beyer, Alexander Kolesnikov, Joan Puigcerver, Nan Ding, Keran Rong, Hassan Akbari, Gaurav Mishra, Linting Xue, Ashish V. Thapliyal, James Bradbury, Weicheng Kuo, Mojtaba Seyedhosseini, Chao Jia, Burcu Karagol Ayan, Carlos Riquelme, Andreas Steiner, Anelia Angelova, Xiaohua Zhai, Neil Houlsby, Radu Soricut

CoRR, 2022

PACTran: PAC-Bayesian Metrics for Estimating the Transferability of Pretrained Models to Classification Tasks.

Nan Ding, Xi Chen, Tomer Levinboim, Beer Changpinyo, Radu Soricut

CoRR, 2022

All You May Need for VQA are Image Captions.

Soravit Changpinyo, Doron Kukliansky, Idan Szpektor, Xi Chen, Nan Ding, Radu Soricut

Proceedings of the 2022 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, 2022

PACTran: PAC-Bayesian Metrics for Estimating the Transferability of Pretrained Models to Classification Tasks.

Nan Ding, Xi Chen, Tomer Levinboim, Soravit Changpinyo, Radu Soricut

Proceedings of the Computer Vision - ECCV 2022, 2022

2021

Bridging the Gap Between Practice and PAC-Bayes Theory in Few-Shot Meta-Learning.

Nan Ding, Xi Chen, Tomer Levinboim, Sebastian Goodman, Radu Soricut

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

Do Transformer Modifications Transfer Across Implementations and Applications?

Sharan Narang, Hyung Won Chung, Yi Tay, Liam Fedus, Thibault Févry, Michael Matena, Karishma Malkan, Noah Fiedel, Noam Shazeer, Zhenzhong Lan, Yanqi Zhou, Wei Li, Nan Ding, Jake Marcus, Adam Roberts, Colin Raffel

Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing, 2021

Conceptual 12M: Pushing Web-Scale Image-Text Pre-Training To Recognize Long-Tail Visual Concepts.

Soravit Changpinyo, Piyush Sharma, Nan Ding, Radu Soricut

Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2021

2020

Attention that does not Explain Away.

Nan Ding, Xinjie Fan, Zhenzhong Lan, Dale Schuurmans, Radu Soricut

CoRR, 2020

Talking-Heads Attention.

Noam Shazeer, Zhenzhong Lan, Youlong Cheng, Nan Ding, Le Hou

CoRR, 2020

Improving Text Generation Evaluation with Batch Centering and Tempered Word Mover Distance.

Xi Chen, Nan Ding, Tomer Levinboim, Radu Soricut

Proceedings of the First Workshop on Evaluation and Comparison of NLP Systems, 2020

TeaForN: Teacher-Forcing with N-grams.

Sebastian Goodman, Nan Ding, Radu Soricut

Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing, 2020

2018

SHAPED: Shared-Private Encoder-Decoder for Text Style Adaptation.

Ye Zhang, Nan Ding, Radu Soricut

Proceedings of the 2018 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, 2018

Conceptual Captions: A Cleaned, Hypernymed, Image Alt-text Dataset For Automatic Image Captioning.

Piyush Sharma, Nan Ding, Sebastian Goodman, Radu Soricut

Proceedings of the 56th Annual Meeting of the Association for Computational Linguistics, 2018

2017

Cold-Start Reinforcement Learning with Softmax Policy Gradients.

Nan Ding, Radu Soricut

CoRR, 2017

Cold-Start Reinforcement Learning with Softmax Policy Gradient.

Nan Ding, Radu Soricut

Proceedings of the Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017, 2017

2016

Multilingual Word Embeddings using Multigraphs.

Radu Soricut, Nan Ding

CoRR, 2016

Building Large Machine Reading-Comprehension Datasets using Paragraph Vectors.

Radu Soricut, Nan Ding

CoRR, 2016

Understanding Image and Text Simultaneously: a Dual Vision-Language Machine Comprehension Task.

Nan Ding, Sebastian Goodman, Fei Sha, Radu Soricut

CoRR, 2016

Stochastic Gradient MCMC with Stale Gradients.

Changyou Chen, Nan Ding, Chunyuan Li, Yizhe Zhang, Lawrence Carin

Proceedings of the Advances in Neural Information Processing Systems 29: Annual Conference on Neural Information Processing Systems 2016, 2016

2015

Differential Topic Models.

Changyou Chen, Wray L. Buntine, Nan Ding, Lexing Xie, Lan Du

IEEE Trans. Pattern Anal. Mach. Intell., 2015

Totally Corrective Boosting with Cardinality Penalization.

Vasil S. Denchev, Nan Ding, Shin Matsushima, S. V. N. Vishwanathan, Hartmut Neven

CoRR, 2015

Embedding Inference for Structured Multilabel Prediction.

Farzaneh Mirzazadeh, Siamak Ravanbakhsh, Nan Ding, Dale Schuurmans

Proceedings of the Advances in Neural Information Processing Systems 28: Annual Conference on Neural Information Processing Systems 2015, 2015

On the Convergence of Stochastic Gradient MCMC Algorithms with High-Order Integrators.

Changyou Chen, Nan Ding, Lawrence Carin

Proceedings of the Advances in Neural Information Processing Systems 28: Annual Conference on Neural Information Processing Systems 2015, 2015

Probabilistic Label Relation Graphs with Ising Models.

Nan Ding, Jia Deng, Kevin P. Murphy, Hartmut Neven

Proceedings of the 2015 IEEE International Conference on Computer Vision, 2015

2014

Construction of non-convex polynomial loss functions for training a binary classifier with quantum annealing.

Ryan Babbush, Vasil S. Denchev, Nan Ding, Sergei Isakov, Hartmut Neven

CoRR, 2014

Bayesian Sampling Using Stochastic Gradient Thermostats.

Nan Ding, Youhan Fang, Ryan Babbush, Changyou Chen, Robert D. Skeel, Hartmut Neven

Proceedings of the Advances in Neural Information Processing Systems 27: Annual Conference on Neural Information Processing Systems 2014, 2014

Large-Scale Object Classification Using Label Relation Graphs.

Jia Deng, Nan Ding, Yangqing Jia, Andrea Frome, Kevin Murphy, Samy Bengio, Yuan Li, Hartmut Neven, Hartwig Adam

Proceedings of the Computer Vision - ECCV 2014, 2014

2012

Theory of Dependent Hierarchical Normalized Random Measures

Changyou Chen, Wray L. Buntine, Nan Ding

CoRR, 2012

Robust Classification with Adiabatic Quantum Optimization.

Vasil S. Denchev, Nan Ding, S. V. N. Vishwanathan, Hartmut Neven

Proceedings of the 29th International Conference on Machine Learning, 2012

Dependent Hierarchical Normalized Random Measures for Dynamic Topic Modeling.

Changyou Chen, Nan Ding, Wray L. Buntine

Proceedings of the 29th International Conference on Machine Learning, 2012

2011

t-divergence Based Approximate Inference.

Nan Ding, S. V. N. Vishwanathan, Yuan (Alan) Qi

Proceedings of the Advances in Neural Information Processing Systems 24: 25th Annual Conference on Neural Information Processing Systems 2011. Proceedings of a meeting held 12-14 December 2011, 2011

2010

Nonparametric Bayesian Matrix Factorization by Power-EP.

Nan Ding, Yuan (Alan) Qi, Rongjing Xiang, Ian M. Molloy, Ninghui Li

Proceedings of the Thirteenth International Conference on Artificial Intelligence and Statistics, 2010

t-logistic regression.

Nan Ding, S. V. N. Vishwanathan

Proceedings of the Advances in Neural Information Processing Systems 23: 24th Annual Conference on Neural Information Processing Systems 2010. Proceedings of a meeting held 6-9 December 2010, 2010

Variational nonparametric Bayesian Hidden Markov Model.

Nan Ding, Zhijian Ou

Proceedings of the IEEE International Conference on Acoustics, 2010

2008

Linkages Detection in Histogram-Based Estimation of Distribution Algorithm.

Nan Ding, Shude Zhou

Proceedings of the Linkage in Evolutionary Computation, 2008

Histogram-Based Estimation of Distribution Algorithm: A Competent Method for Continuous Optimization.

Nan Ding, Shude Zhou, Zengqi Sun

J. Comput. Sci. Technol., 2008

Marginal probability distribution estimation in characteristic space of covariance-matrix.

Nan Ding, Shude Zhou, Hao Zhang, Zengqi Sun

Proceedings of the IEEE Congress on Evolutionary Computation, 2008

A Bayesian view on the polynomial distribution model in estimation of distribution algorithms.

Nan Ding, Shude Zhou, Ji Xu, Zengqi Sun

Proceedings of the IEEE Congress on Evolutionary Computation, 2008

2007

Reducing computational complexity of estimating multivariate histogram-based probabilistic model.

Nan Ding, Ji Xu, Shude Zhou, Zengqi Sun

Proceedings of the IEEE Congress on Evolutionary Computation, 2007

2006

Optimizing Continuous Problems Using Estimation of Distribution Algorithm Based on Histogram Model.

Nan Ding, Shude Zhou, Zengqi Sun

Proceedings of the Simulated Evolution and Learning, 6th International Conference, 2006