Nan Ding

Publication Activity (10 Years)

Years Active: 2006-2024
Publications (10 Years): 31

Top Topics

Reinforcement Learning

Stochastic Gradient

Top Venues

Publications

Nan Ding, Tomer Levinboim, Jialin Wu, Sebastian Goodman, Radu Soricut
CausalLM is not optimal for in-context learning. ICLR (2024)
Zifan Wang, Nan Ding, Tomer Levinboim, Xi Chen, Radu Soricut
Improving Robust Generalization by Direct PAC-Bayesian Bound Minimization. CVPR (2023)
Nan Ding, Tomer Levinboim, Jialin Wu, Sebastian Goodman, Radu Soricut
CausalLM is not optimal for in-context learning. CoRR (2023)
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
PaLI: A Jointly-Scaled Multilingual Language-Image Model. ICLR (2023)
Soravit Changpinyo, Doron Kukliansky, Idan Szpektor, Xi Chen, Nan Ding, Radu Soricut
All You May Need for VQA are Image Captions. CoRR (2022)
Nan Ding, Xi Chen, Tomer Levinboim, Beer Changpinyo, Radu Soricut
PACTran: PAC-Bayesian Metrics for Estimating the Transferability of Pretrained Models to Classification Tasks. CoRR (2022)
Soravit Changpinyo, Doron Kukliansy, Idan Szpektor, Xi Chen, Nan Ding, Radu Soricut
All You May Need for VQA are Image Captions. NAACL-HLT (2022)
Zifan Wang, Nan Ding, Tomer Levinboim, Xi Chen, Radu Soricut
Improving Robust Generalization by Direct PAC-Bayesian Bound Minimization. CoRR (2022)
Nan Ding, Xi Chen, Tomer Levinboim, Soravit Changpinyo, Radu Soricut
PACTran: PAC-Bayesian Metrics for Estimating the Transferability of Pretrained Models to Classification Tasks. ECCV (34) (2022)
Soravit Changpinyo, Piyush Sharma, Nan Ding, Radu Soricut
Conceptual 12M: Pushing Web-Scale Image-Text Pre-Training To Recognize Long-Tail Visual Concepts. CoRR (2021)
Nan Ding, Xi Chen, Tomer Levinboim, Sebastian Goodman, Radu Soricut
Bridging the Gap Between Practice and PAC-Bayes Theory in Few-Shot Meta-Learning. CoRR (2021)
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
Do Transformer Modifications Transfer Across Implementations and Applications? EMNLP (1) (2021)
Sharan Narang, Hyung Won Chung, Yi Tay, William 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
Do Transformer Modifications Transfer Across Implementations and Applications? CoRR (2021)
Nan Ding, Xi Chen, Tomer Levinboim, Sebastian Goodman, Radu Soricut
Bridging the Gap Between Practice and PAC-Bayes Theory in Few-Shot Meta-Learning. NeurIPS (2021)
Soravit Changpinyo, Piyush Sharma, Nan Ding, Radu Soricut
Conceptual 12M: Pushing Web-Scale Image-Text Pre-Training To Recognize Long-Tail Visual Concepts. CVPR (2021)
Sebastian Goodman, Nan Ding, Radu Soricut
TeaForN: Teacher-Forcing with N-grams. CoRR (2020)
Xi Chen, Nan Ding, Tomer Levinboim, Radu Soricut
Improving Text Generation Evaluation with Batch Centering and Tempered Word Mover Distance. CoRR (2020)
Sebastian Goodman, Nan Ding, Radu Soricut
TeaForN: Teacher-Forcing with N-grams. EMNLP (1) (2020)
Nan Ding, Xinjie Fan, Zhenzhong Lan, Dale Schuurmans, Radu Soricut
Attention that does not Explain Away. CoRR (2020)
Noam Shazeer, Zhenzhong Lan, Youlong Cheng, Nan Ding, Le Hou
Talking-Heads Attention. CoRR (2020)
Xi Chen, Nan Ding, Tomer Levinboim, Radu Soricut
Improving Text Generation Evaluation with Batch Centering and Tempered Word Mover Distance. Eval4NLP (2020)
Piyush Sharma, Nan Ding, Sebastian Goodman, Radu Soricut
Conceptual Captions: A Cleaned, Hypernymed, Image Alt-text Dataset For Automatic Image Captioning. ACL (1) (2018)
Ye Zhang, Nan Ding, Radu Soricut
SHAPED: Shared-Private Encoder-Decoder for Text Style Adaptation. CoRR (2018)
Ye Zhang, Nan Ding, Radu Soricut
SHAPED: Shared-Private Encoder-Decoder for Text Style Adaptation. NAACL-HLT (2018)
Nan Ding, Radu Soricut
Cold-Start Reinforcement Learning with Softmax Policy Gradients. CoRR (2017)
Nan Ding, Radu Soricut
Cold-Start Reinforcement Learning with Softmax Policy Gradient. NIPS (2017)
Radu Soricut, Nan Ding
Building Large Machine Reading-Comprehension Datasets using Paragraph Vectors. CoRR (2016)
Changyou Chen, Nan Ding, Chunyuan Li, Yizhe Zhang, Lawrence Carin
Stochastic Gradient MCMC with Stale Gradients. NIPS (2016)
Nan Ding, Sebastian Goodman, Fei Sha, Radu Soricut
Understanding Image and Text Simultaneously: a Dual Vision-Language Machine Comprehension Task. CoRR (2016)
Changyou Chen, Nan Ding, Chunyuan Li, Yizhe Zhang, Lawrence Carin
Stochastic Gradient MCMC with Stale Gradients. CoRR (2016)
Radu Soricut, Nan Ding
Multilingual Word Embeddings using Multigraphs. CoRR (2016)
Nan Ding, Jia Deng, Kevin Murphy, Hartmut Neven
Probabilistic Label Relation Graphs with Ising Models. CoRR (2015)
Vasil S. Denchev, Nan Ding, Shin Matsushima, S. V. N. Vishwanathan, Hartmut Neven
Totally Corrective Boosting with Cardinality Penalization. CoRR (2015)
Nan Ding, Jia Deng, Kevin P. Murphy, Hartmut Neven
Probabilistic Label Relation Graphs with Ising Models. ICCV (2015)
Changyou Chen, Wray L. Buntine, Nan Ding, Lexing Xie, Lan Du
Differential Topic Models. IEEE Trans. Pattern Anal. Mach. Intell. 37 (2) (2015)
Changyou Chen, Nan Ding, Lawrence Carin
On the Convergence of Stochastic Gradient MCMC Algorithms with High-Order Integrators. NIPS (2015)
Farzaneh Mirzazadeh, Siamak Ravanbakhsh, Nan Ding, Dale Schuurmans
Embedding Inference for Structured Multilabel Prediction. NIPS (2015)
Ryan Babbush, Vasil S. Denchev, Nan Ding, Sergei Isakov, Hartmut Neven
Construction of non-convex polynomial loss functions for training a binary classifier with quantum annealing. CoRR (2014)
Nan Ding, Youhan Fang, Ryan Babbush, Changyou Chen, Robert D. Skeel, Hartmut Neven
Bayesian Sampling Using Stochastic Gradient Thermostats. NIPS (2014)
Jia Deng, Nan Ding, Yangqing Jia, Andrea Frome, Kevin Murphy, Samy Bengio, Yuan Li, Hartmut Neven, Hartwig Adam
Large-Scale Object Classification Using Label Relation Graphs. ECCV (1) (2014)
Changyou Chen, Wray L. Buntine, Nan Ding
Theory of Dependent Hierarchical Normalized Random Measures CoRR (2012)
Vasil S. Denchev, Nan Ding, S. V. N. Vishwanathan, Hartmut Neven
Robust Classification with Adiabatic Quantum Optimization. ICML (2012)
Changyou Chen, Nan Ding, Wray L. Buntine
Dependent Hierarchical Normalized Random Measures for Dynamic Topic Modeling CoRR (2012)
Changyou Chen, Nan Ding, Wray L. Buntine
Dependent Hierarchical Normalized Random Measures for Dynamic Topic Modeling. ICML (2012)
Nan Ding, S. V. N. Vishwanathan, Yuan (Alan) Qi
t-divergence Based Approximate Inference. NIPS (2011)
Nan Ding, S. V. N. Vishwanathan
t-logistic regression. NIPS (2010)
Nan Ding, Yuan (Alan) Qi, Rongjing Xiang, Ian M. Molloy, Ninghui Li
Nonparametric Bayesian Matrix Factorization by Power-EP. AISTATS (2010)
Nan Ding, Zhijian Ou
Variational nonparametric Bayesian Hidden Markov Model. ICASSP (2010)
Nan Ding, Shude Zhou, Hao Zhang, Zengqi Sun
Marginal probability distribution estimation in characteristic space of covariance-matrix. IEEE Congress on Evolutionary Computation (2008)
Nan Ding, Shude Zhou, Zengqi Sun
Histogram-Based Estimation of Distribution Algorithm: A Competent Method for Continuous Optimization. J. Comput. Sci. Technol. 23 (1) (2008)
Nan Ding, Shude Zhou, Ji Xu, Zengqi Sun
A Bayesian view on the polynomial distribution model in estimation of distribution algorithms. IEEE Congress on Evolutionary Computation (2008)
Nan Ding, Ji Xu, Shude Zhou, Zengqi Sun
Reducing computational complexity of estimating multivariate histogram-based probabilistic model. IEEE Congress on Evolutionary Computation (2007)
Nan Ding, Shude Zhou, Zengqi Sun
Optimizing Continuous Problems Using Estimation of Distribution Algorithm Based on Histogram Model. SEAL (2006)