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Di Wang

SUNY at Buffalo

Differentially Private (Gradient) Expectation Maximization Algorithm with Statistical Guarantees

Oct 22, 2020
Di Wang, Jiahao Ding, Zejun Xie, Miao Pan, Jinhui Xu

* Submiited. arXiv admin note: text overlap with arXiv:2010.09576 
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On Differentially Private Stochastic Convex Optimization with Heavy-tailed Data

Oct 21, 2020
Di Wang, Hanshen Xiao, Srini Devadas, Jinhui Xu

* Published in ICML 2020 
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Robust High Dimensional Expectation Maximization Algorithm via Trimmed Hard Thresholding

Oct 19, 2020
Di Wang, Xiangyu Guo, Shi Li, Jinhui Xu

* Accepted at Machine Learning 
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Estimating Stochastic Linear Combination of Non-linear Regressions Efficiently and Scalably

Oct 19, 2020
Di Wang, Xiangyu Guo, Chaowen Guan, Shi Li, Jinhui Xu

* This paper is a substantially extended version of our previous work appeared in AAAI'20 
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Learning Robust Algorithms for Online Allocation Problems Using Adversarial Training

Oct 16, 2020
Goran Zuzic, Di Wang, Aranyak Mehta, D. Sivakumar


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ECG Beats Fast Classification Base on Sparse Dictionaries

Sep 08, 2020
Nanyu Li, Yujuan Si, Di Wang, Tong Liu, Jinrun Yu

* 27 pages 5 figures 
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Heterogeneous Federated Learning

Aug 15, 2020
Fuxun Yu, Weishan Zhang, Zhuwei Qin, Zirui Xu, Di Wang, Chenchen Liu, Zhi Tian, Xiang Chen


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AntiDote: Attention-based Dynamic Optimization for Neural Network Runtime Efficiency

Aug 14, 2020
Fuxun Yu, Chenchen Liu, Di Wang, Yanzhi Wang, Xiang Chen

* Accepted in DATE'2020 (Best Paper Nomination) 
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Towards Assessment of Randomized Smoothing Mechanisms for Certifying Adversarial Robustness

Jun 07, 2020
Tianhang Zheng, Di Wang, Baochun Li, Jinhui Xu

* Correct the some details of the theorems and proofs 
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Towards Assessment of Randomized Mechanisms for Certifying Adversarial Robustness

May 27, 2020
Tianhang Zheng, Di Wang, Baochun Li, Jinhui Xu

* Refine the proofs, and add more theorems and experiments 
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$p$-Norm Flow Diffusion for Local Graph Clustering

May 20, 2020
Shenghao Yang, Di Wang, Kimon Fountoulakis

* 29 pages, 5 figures, 3 tables 
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Distributed Kernel Ridge Regression with Communications

Mar 27, 2020
Shao-Bo Lin, Di Wang, Ding-Xuan Zhou

* 38pages 
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Robust Feature-Based Point Registration Using Directional Mixture Model

Nov 25, 2019
Saman Fahandezh-Saadi, Di Wang, Masayoshi Tomizuka


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Unsupervised Domain Adaptation for Object Detection via Cross-Domain Semi-Supervised Learning

Nov 24, 2019
Fuxun Yu, Di Wang, Yinpeng Chen, Nikolaos Karianakis, Pei Yu, Dimitrios Lymberopoulos, Xiang Chen


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Facility Location Problem in Differential Privacy Model Revisited

Oct 26, 2019
Yunus Esencayi, Marco Gaboardi, Shi Li, Di Wang

* Accepted to NeurIPS 2019 
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Estimating Smooth GLM in Non-interactive Local Differential Privacy Model with Public Unlabeled Data

Oct 01, 2019
Di Wang, Huanyu Zhang, Marco Gaboardi, Jinhui Xu


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Knowledge-Enriched Transformer for Emotion Detection in Textual Conversations

Oct 01, 2019
Peixiang Zhong, Di Wang, Chunyan Miao

* EMNLP 2019 
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INTERACTION Dataset: An INTERnational, Adversarial and Cooperative moTION Dataset in Interactive Driving Scenarios with Semantic Maps

Sep 30, 2019
Wei Zhan, Liting Sun, Di Wang, Haojie Shi, Aubrey Clausse, Maximilian Naumann, Julius Kummerle, Hendrik Konigshof, Christoph Stiller, Arnaud de La Fortelle, Masayoshi Tomizuka


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Faster width-dependent algorithm for mixed packing and covering LPs

Sep 26, 2019
Digvijay Boob, Saurabh Sawlani, Di Wang

* Accepted for oral presentation at NeurIPS 2019 
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Heterogeneous Graph Convolutional Networks for Temporal Community Detection

Sep 23, 2019
Yaping Zheng, Shiyi Chen, Xiaofeng Zhang, Di Wang


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Distributed Equivalent Substitution Training for Large-Scale Recommender Systems

Sep 10, 2019
Haidong Rong, Yangzihao Wang, Feihu Zhou, Junjie Zhai, Haiyang Wu, Rui Lan, Fan Li, Han Zhang, Yuekui Yang, Zhenyu Guo, Di Wang

* 10 pages 
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Compact Autoregressive Network

Sep 06, 2019
Di Wang, Feiqing Huang, Jingyu Zhao, Guodong Li, Guangjian Tian


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EEG-Based Emotion Recognition Using Regularized Graph Neural Networks

Aug 26, 2019
Peixiang Zhong, Di Wang, Chunyan Miao

* 13 pages 
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Scalable Topological Data Analysis and Visualization for Evaluating Data-Driven Models in Scientific Applications

Jul 19, 2019
Shusen Liu, Di Wang, Dan Maljovec, Rushil Anirudh, Jayaraman J. Thiagarajan, Sam Ade Jacobs, Brian C. Van Essen, David Hysom, Jae-Seung Yeom, Jim Gaffney, Luc Peterson, Peter B. Robinson, Harsh Bhatia, Valerio Pascucci, Brian K. Spears, Peer-Timo Bremer


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Single-Path Mobile AutoML: Efficient ConvNet Design and NAS Hyperparameter Optimization

Jul 01, 2019
Dimitrios Stamoulis, Ruizhou Ding, Di Wang, Dimitrios Lymberopoulos, Bodhi Priyantha, Jie Liu, Diana Marculescu

* Detailed extension (journal) of the Single-Path NAS ECMLPKDD'19 paper (arXiv:1904.02877) 
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Neural Learning of Online Consumer Credit Risk

Jun 05, 2019
Di Wang, Qi Wu, Wen Zhang

* 49 pages, 11 tables, 7 figures 
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