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Dehua Cheng
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2020 – today
- 2024
- [c13]Wei Wen
, Kuang-Hung Liu
Rankitect: Ranking Architecture Search Battling World-class Engineers at Meta Scale. WWW (Companion Volume) 2024: 73-82 - 2023
- [c12]Tunhou Zhang
NASRec: Weight Sharing Neural Architecture Search for Recommender Systems. WWW 2023: 1199-1207 - [i9]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:
Rankitect: Ranking Architecture Search Battling World-class Engineers at Meta Scale. CoRR abs/2311.08430 (2023) - 2022
- [i8]Tunhou Zhang, Dehua Cheng, Yuchen He, Zhengxing Chen, Xiaoliang Dai, Liang Xiong, Feng Yan, Hai Li, Yiran Chen, Wei Wen:
NASRec: Weight Sharing Neural Architecture Search for Recommender Systems. CoRR abs/2207.07187 (2022) - 2020
- [c11]Michael Tsang, Dehua Cheng, Hanpeng Liu, Xue Feng, Eric Zhou, Yan Liu:
Feature Interaction Interpretability: A Case for Explaining Ad-Recommendation Systems via Neural Interaction Detection. ICLR 2020 - [c10]Qingquan Song, Dehua Cheng, Hanning Zhou, Jiyan Yang, Yuandong Tian, Xia Hu:
Towards Automated Neural Interaction Discovery for Click-Through Rate Prediction. KDD 2020: 945-955 - [i7]Michael Tsang, Dehua Cheng, Hanpeng Liu, Xue Feng, Eric Zhou, Yan Liu:
Feature Interaction Interpretability: A Case for Explaining Ad-Recommendation Systems via Neural Interaction Detection. CoRR abs/2006.10966 (2020) - [i6]Qingquan Song, Dehua Cheng, Hanning Zhou, Jiyan Yang, Yuandong Tian, Xia Hu:
Towards Automated Neural Interaction Discovery for Click-Through Rate Prediction. CoRR abs/2007.06434 (2020)
2010 – 2019
- 2019
- [c9]Geng Ji, Dehua Cheng, Huazhong Ning, Changhe Yuan, Hanning Zhou, Liang Xiong, Erik B. Sudderth:
Variational Training for Large-Scale Noisy-OR Bayesian Networks. UAI 2019: 873-882 - 2018
- [c8]Dehua Cheng, Natali Ruchansky, Yan Liu:
Matrix completability analysis via graph k-connectivity. AISTATS 2018: 395-403 - [c7]Michael Tsang, Dehua Cheng, Yan Liu:
Detecting Statistical Interactions from Neural Network Weights. ICLR (Poster) 2018 - 2017
- [i5]Michael Tsang, Dehua Cheng, Yan Liu:
Detecting Statistical Interactions from Neural Network Weights. CoRR abs/1705.04977 (2017) - 2016
- [c6]Dehua Cheng, Richard Peng, Yan Liu, Ioakeim Perros:
SPALS: Fast Alternating Least Squares via Implicit Leverage Scores Sampling. NIPS 2016: 721-729 - [i4]Jie Chen, Dehua Cheng, Yan Liu:
On Bochner's and Polya's Characterizations of Positive-Definite Kernels and the Respective Random Feature Maps. CoRR abs/1610.08861 (2016) - 2015
- [c5]Dehua Cheng, Xinran He, Yan Liu:
Model Selection for Topic Models via Spectral Decomposition. AISTATS 2015 - [c4]Dehua Cheng, Yu Cheng, Yan Liu, Richard Peng, Shang-Hua Teng:
Efficient Sampling for Gaussian Graphical Models via Spectral Sparsification. COLT 2015: 364-390 - [c3]Rose Yu, Dehua Cheng, Yan Liu:
Accelerated Online Low Rank Tensor Learning for Multivariate Spatiotemporal Streams. ICML 2015: 238-247 - [i3]Dehua Cheng, Yu Cheng, Yan Liu, Richard Peng, Shang-Hua Teng:
Spectral Sparsification of Random-Walk Matrix Polynomials. CoRR abs/1502.03496 (2015) - 2014
- [c2]Dehua Cheng, Mohammad Taha Bahadori, Yan Liu:
FBLG: a simple and effective approach for temporal dependence discovery from time series data. KDD 2014: 382-391 - [c1]Dehua Cheng, Yan Liu:
Parallel gibbs sampling for hierarchical dirichlet processes via gamma processes equivalence. KDD 2014: 562-571 - [i2]Dehua Cheng, Yu Cheng, Yan Liu, Richard Peng, Shang-Hua Teng:
Scalable Parallel Factorizations of SDD Matrices and Efficient Sampling for Gaussian Graphical Models. CoRR abs/1410.5392 (2014) - [i1]Dehua Cheng, Xinran He, Yan Liu:
Analyzing the Number of Latent Topics via Spectral Decomposition. CoRR abs/1410.6466 (2014)
Coauthor Index
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last updated on 2024-08-21 21:30 CEST by the dblp team
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