Dehua Cheng

According to our database, Dehua Cheng authored at least 17 papers between 2014 and 2023.

Collaborative distances:

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

2023

Rankitect: Ranking Architecture Search Battling World-class Engineers at Meta Scale.

Wei Wen, Kuang-Hung Liu, Igor Fedorov, Xin Zhang, Hang Yin, Weiwei Chu, Kaveh Hassani, Mengying Sun, Jiang Liu, Xu Wang, Lin Jiang, Yuxin Chen, Buyun Zhang, Xi Liu, Dehua Cheng, Zhengxing Chen, Guang Zhao, Fangqiu Han, Jiyan Yang, Yuchen Hao, Liang Xiong, Wen-Yen Chen

CoRR, 2023

NASRec: Weight Sharing Neural Architecture Search for Recommender Systems.

Tunhou Zhang, Dehua Cheng, Yuchen He, Zhengxing Chen, Xiaoliang Dai, Liang Xiong, Feng Yan, Hai Li, Yiran Chen, Wei Wen

Proceedings of the ACM Web Conference 2023, 2023

2020

Towards Automated Neural Interaction Discovery for Click-Through Rate Prediction.

Qingquan Song, Dehua Cheng, Hanning Zhou, Jiyan Yang, Yuandong Tian, Xia Hu

Proceedings of the KDD '20: The 26th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2020

Feature Interaction Interpretability: A Case for Explaining Ad-Recommendation Systems via Neural Interaction Detection.

Michael Tsang, Dehua Cheng, Hanpeng Liu, Xue Feng, Eric Zhou, Yan Liu

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

2019

Variational Training for Large-Scale Noisy-OR Bayesian Networks.

Geng Ji, Dehua Cheng, Huazhong Ning, Changhe Yuan, Hanning Zhou, Liang Xiong, Erik B. Sudderth

Proceedings of the Thirty-Fifth Conference on Uncertainty in Artificial Intelligence, 2019

2018

Detecting Statistical Interactions from Neural Network Weights.

Michael Tsang, Dehua Cheng, Yan Liu

Proceedings of the 6th International Conference on Learning Representations, 2018

Matrix completability analysis via graph k-connectivity.

Dehua Cheng, Natali Ruchansky, Yan Liu

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2018

2016

On Bochner's and Polya's Characterizations of Positive-Definite Kernels and the Respective Random Feature Maps.

Jie Chen, Dehua Cheng, Yan Liu

CoRR, 2016

SPALS: Fast Alternating Least Squares via Implicit Leverage Scores Sampling.

Dehua Cheng, Richard Peng, Yan Liu, Ioakeim Perros

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

2015

Spectral Sparsification of Random-Walk Matrix Polynomials.

Dehua Cheng, Yu Cheng, Yan Liu, Richard Peng, Shang-Hua Teng

CoRR, 2015

Accelerated Online Low Rank Tensor Learning for Multivariate Spatiotemporal Streams.

Rose Yu, Dehua Cheng, Yan Liu

Proceedings of the 32nd International Conference on Machine Learning, 2015

Efficient Sampling for Gaussian Graphical Models via Spectral Sparsification.

Dehua Cheng, Yu Cheng, Yan Liu, Richard Peng, Shang-Hua Teng

Proceedings of The 28th Conference on Learning Theory, 2015

Model Selection for Topic Models via Spectral Decomposition.

Dehua Cheng, Xinran He, Yan Liu

Proceedings of the Eighteenth International Conference on Artificial Intelligence and Statistics, 2015

2014

Analyzing the Number of Latent Topics via Spectral Decomposition.

Dehua Cheng, Xinran He, Yan Liu

CoRR, 2014

Scalable Parallel Factorizations of SDD Matrices and Efficient Sampling for Gaussian Graphical Models.

Dehua Cheng, Yu Cheng, Yan Liu, Richard Peng, Shang-Hua Teng

CoRR, 2014

Parallel gibbs sampling for hierarchical dirichlet processes via gamma processes equivalence.

Dehua Cheng, Yan Liu

Proceedings of the 20th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2014

FBLG: a simple and effective approach for temporal dependence discovery from time series data.

Dehua Cheng, Mohammad Taha Bahadori, Yan Liu

Proceedings of the 20th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2014