Optimizing Continuous Problems Using Estimation of Distribution Algorithm Based on Histogram Model. - Nan Ding 002; Shude Zhou; Zengqi Sun (SEAL, 2006)

Reducing computational complexity of estimating multivariate histogram-based probabilistic model. - Nan Ding 002; Ji Xu; Shude Zhou; Zengqi Sun (IEEE Congress on Evolutionary Computation, 2007)

A Bayesian view on the polynomial distribution model in estimation of distribution algorithms. - Nan Ding 002; Shude Zhou; Ji Xu; Zengqi Sun (IEEE Congress on Evolutionary Computation, 2008)

Marginal probability distribution estimation in characteristic space of covariance-matrix. - Nan Ding 002; Shude Zhou; Hao Zhang; Zengqi Sun (IEEE Congress on Evolutionary Computation, 2008)

Histogram-Based Estimation of Distribution Algorithm: A Competent Method for Continuous Optimization. - Nan Ding 002; Shude Zhou; Zengqi Sun (J. Comput. Sci. Technol., 2008)

Linkages Detection in Histogram-Based Estimation of Distribution Algorithm. - Nan Ding 002; Shude Zhou (Linkage in Evolutionary Computation, 2008)

Variational nonparametric Bayesian Hidden Markov Model. - Nan Ding 002; Zhijian Ou (ICASSP, 2010)

t-logistic regression. - Nan Ding 002; S. V. N. Vishwanathan (NIPS, 2010)

Nonparametric Bayesian Matrix Factorization by Power-EP. - Nan Ding 002; Yuan (Alan) Qi; Rongjing Xiang; Ian M. Molloy; Ninghui Li (AISTATS, 2010)

t-divergence Based Approximate Inference. - Nan Ding 002; S. V. N. Vishwanathan; Yuan (Alan) Qi (NIPS, 2011)

Dependent Hierarchical Normalized Random Measures for Dynamic Topic Modeling. - Changyou Chen; Nan Ding 002; Wray L. Buntine (ICML, 2012)

Robust Classification with Adiabatic Quantum Optimization. - Vasil S. Denchev; Nan Ding 002; S. V. N. Vishwanathan; Hartmut Neven (ICML, 2012)

Theory of Dependent Hierarchical Normalized Random Measures - Changyou Chen; Wray L. Buntine; Nan Ding 002 (CoRR, 2012)

Large-Scale Object Classification Using Label Relation Graphs. - Jia Deng 001; Nan Ding 002; Yangqing Jia; Andrea Frome; Kevin Murphy 002; Samy Bengio; Yuan Li; Hartmut Neven; Hartwig Adam (ECCV (1), 2014)

Bayesian Sampling Using Stochastic Gradient Thermostats. - Nan Ding 002; Youhan Fang; Ryan Babbush; Changyou Chen; Robert D. Skeel; Hartmut Neven (NIPS, 2014)

Construction of non-convex polynomial loss functions for training a binary classifier with quantum annealing. - Ryan Babbush; Vasil S. Denchev; Nan Ding 002; Sergei Isakov; Hartmut Neven (CoRR, 2014)

Probabilistic Label Relation Graphs with Ising Models. - Nan Ding 002; Jia Deng 001; Kevin P. Murphy; Hartmut Neven (ICCV, 2015)

On the Convergence of Stochastic Gradient MCMC Algorithms with High-Order Integrators. - Changyou Chen; Nan Ding 002; Lawrence Carin (NIPS, 2015)

Embedding Inference for Structured Multilabel Prediction. - Farzaneh Mirzazadeh; Siamak Ravanbakhsh; Nan Ding 002; Dale Schuurmans (NIPS, 2015)

Totally Corrective Boosting with Cardinality Penalization. - Vasil S. Denchev; Nan Ding 002; Shin Matsushima; S. V. N. Vishwanathan; Hartmut Neven (CoRR, 2015)

Differential Topic Models. - Changyou Chen; Wray L. Buntine; Nan Ding 002; Lexing Xie; Lan Du 002 (IEEE Trans. Pattern Anal. Mach. Intell., 2015)

Stochastic Gradient MCMC with Stale Gradients. - Changyou Chen; Nan Ding 002; Chunyuan Li; Yizhe Zhang 002; Lawrence Carin (NIPS, 2016)

Understanding Image and Text Simultaneously: a Dual Vision-Language Machine Comprehension Task. - Nan Ding 002; Sebastian Goodman; Fei Sha; Radu Soricut (CoRR, 2016)

Building Large Machine Reading-Comprehension Datasets using Paragraph Vectors. - Radu Soricut; Nan Ding 002 (CoRR, 2016)

Multilingual Word Embeddings using Multigraphs. - Radu Soricut; Nan Ding 002 (CoRR, 2016)

Cold-Start Reinforcement Learning with Softmax Policy Gradient. - Nan Ding 002; Radu Soricut (NIPS, 2017)

Cold-Start Reinforcement Learning with Softmax Policy Gradients. - Nan Ding 002; Radu Soricut (CoRR, 2017)

Conceptual Captions: A Cleaned, Hypernymed, Image Alt-text Dataset For Automatic Image Captioning. - Piyush Sharma; Nan Ding 002; Sebastian Goodman; Radu Soricut (ACL (1), 2018)

SHAPED: Shared-Private Encoder-Decoder for Text Style Adaptation. - Ye Zhang; Nan Ding 002; Radu Soricut (NAACL-HLT, 2018)

TeaForN: Teacher-Forcing with N-grams. - Sebastian Goodman; Nan Ding 002; Radu Soricut (EMNLP (1), 2020)

Improving Text Generation Evaluation with Batch Centering and Tempered Word Mover Distance. - Xi Chen 071; Nan Ding 002; Tomer Levinboim; Radu Soricut (Eval4NLP, 2020)

Talking-Heads Attention. - Noam Shazeer; Zhenzhong Lan; Youlong Cheng; Nan Ding 002; Le Hou (CoRR, 2020)

Attention that does not Explain Away. - Nan Ding 002; Xinjie Fan; Zhenzhong Lan; Dale Schuurmans; Radu Soricut (CoRR, 2020)

Conceptual 12M: Pushing Web-Scale Image-Text Pre-Training To Recognize Long-Tail Visual Concepts. - Soravit Changpinyo; Piyush Sharma; Nan Ding 002; Radu Soricut (CVPR, 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 133; et al. (EMNLP (1), 2021)

Bridging the Gap Between Practice and PAC-Bayes Theory in Few-Shot Meta-Learning. - Nan Ding 002; Xi Chen 071; Tomer Levinboim; Sebastian Goodman; Radu Soricut (NeurIPS, 2021)

PACTran: PAC-Bayesian Metrics for Estimating the Transferability of Pretrained Models to Classification Tasks. - Nan Ding 002; Xi Chen 071; Tomer Levinboim; Soravit Changpinyo; Radu Soricut (ECCV (34), 2022)

All You May Need for VQA are Image Captions. - Soravit Changpinyo; Doron Kukliansky; Idan Szpektor; Xi Chen 071; Nan Ding 002; Radu Soricut (NAACL-HLT, 2022)

PACTran: PAC-Bayesian Metrics for Estimating the Transferability of Pretrained Models to Classification Tasks. - Nan Ding 002; Xi Chen 071; Tomer Levinboim; Beer Changpinyo; Radu Soricut (CoRR, 2022)

PaLI: A Jointly-Scaled Multilingual Language-Image Model. - Xi Chen 071; Xiao Wang 038; Soravit Changpinyo; A. J. Piergiovanni; Piotr Padlewski; Daniel Salz; Sebastian Goodman; Adam Grycner; Basil Mustafa; Lucas Beyer; Alexander Kolesnikov 003; Joan Puigcerver; et al. (CoRR, 2022)

Improving Robust Generalization by Direct PAC-Bayesian Bound Minimization. - Zifan Wang 001; Nan Ding 002; Tomer Levinboim; Xi Chen 071; Radu Soricut (CVPR, 2023)

PaLI: A Jointly-Scaled Multilingual Language-Image Model. - Xi Chen 071; Xiao Wang 038; Soravit Changpinyo; A. J. Piergiovanni; Piotr Padlewski; Daniel Salz; Sebastian Goodman; Adam Grycner; Basil Mustafa; Lucas Beyer; Alexander Kolesnikov 003; Joan Puigcerver; et al. (ICLR, 2023)

CausalLM is not optimal for in-context learning. - Nan Ding 002; Tomer Levinboim; Jialin Wu; Sebastian Goodman; Radu Soricut (ICLR, 2024)

Graders should cheat: privileged information enables expert-level automated evaluations. - Jin Peng Zhou; Sébastien M. R. Arnold; Nan Ding 002; Kilian Q. Weinberger; Nan Hua; Fei Sha (CoRR, 2025)