Scalable Semantic Querying of Text

May 03, 2018

Xiaolan Wang, Aaron Feng, Behzad Golshan, Alon Halevy, George Mihaila, Hidekazu Oiwa, Wang-Chiew Tan

May 03, 2018

Xiaolan Wang, Aaron Feng, Behzad Golshan, Alon Halevy, George Mihaila, Hidekazu Oiwa, Wang-Chiew Tan

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Learning to Draw Samples with Amortized Stein Variational Gradient Descent

Oct 30, 2017

Yihao Feng, Dilin Wang, Qiang Liu

We propose a simple algorithm to train stochastic neural networks to draw samples from given target distributions for probabilistic inference. Our method is based on iteratively adjusting the neural network parameters so that the output changes along a Stein variational gradient direction (Liu & Wang, 2016) that maximally decreases the KL divergence with the target distribution. Our method works for any target distribution specified by their unnormalized density function, and can train any black-box architectures that are differentiable in terms of the parameters we want to adapt. We demonstrate our method with a number of applications, including variational autoencoder (VAE) with expressive encoders to model complex latent space structures, and hyper-parameter learning of MCMC samplers that allows Bayesian inference to adaptively improve itself when seeing more data.
Oct 30, 2017

Yihao Feng, Dilin Wang, Qiang Liu

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Towards Scalable Spectral Clustering via Spectrum-Preserving Sparsification

Oct 11, 2018

Yongyu Wang, Zhuo Feng

Oct 11, 2018

Yongyu Wang, Zhuo Feng

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VoxSegNet: Volumetric CNNs for Semantic Part Segmentation of 3D Shapes

Sep 01, 2018

Zongji Wang, Feng Lu

Sep 01, 2018

Zongji Wang, Feng Lu

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Given two possible treatments, there may exist subgroups who benefit greater from one treatment than the other. This problem is relevant to the field of marketing, where treatments may correspond to different ways of selling a product. It is similarly relevant to the field of public policy, where treatments may correspond to specific government programs. And finally, personalized medicine is a field wholly devoted to understanding which subgroups of individuals will benefit from particular medical treatments. We present a computationally fast tree-based method, ABtree, for treatment effect differentiation. Unlike other methods, ABtree specifically produces decision rules for optimal treatment assignment on a per-individual basis. The treatment choices are selected for maximizing the overall occurrence of a desired binary outcome, conditional on a set of covariates. In this poster, we present the methodology on tree growth and pruning, and show performance results when applied to simulated data as well as real data.

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Offshore Wind Farm Layout Optimization Using Adapted Genetic Algorithm: A different perspective

Mar 27, 2014

Feng Liu, Zhifang Wang

Mar 27, 2014

Feng Liu, Zhifang Wang

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Cooperative Group Optimization with Ants (CGO-AS): Leverage Optimization with Mixed Individual and Social Learning

Aug 01, 2018

Xiao-Feng Xie, Zun-Jing Wang

Aug 01, 2018

Xiao-Feng Xie, Zun-Jing Wang

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A Novel ECOC Algorithm with Centroid Distance Based Soft Coding Scheme

Jun 22, 2018

Kaijie Feng, Kunhong Liu, Beizhan Wang

Jun 22, 2018

Kaijie Feng, Kunhong Liu, Beizhan Wang

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Pruning Random Forests for Prediction on a Budget

Jun 16, 2016

Feng Nan, Joseph Wang, Venkatesh Saligrama

Jun 16, 2016

Feng Nan, Joseph Wang, Venkatesh Saligrama

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Survey on the attention based RNN model and its applications in computer vision

Jan 25, 2016

Feng Wang, David M. J. Tax

Jan 25, 2016

Feng Wang, David M. J. Tax

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Optimally Pruning Decision Tree Ensembles With Feature Cost

Jan 05, 2016

Feng Nan, Joseph Wang, Venkatesh Saligrama

Jan 05, 2016

Feng Nan, Joseph Wang, Venkatesh Saligrama

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Max-Cost Discrete Function Evaluation Problem under a Budget

Jan 12, 2015

Feng Nan, Joseph Wang, Venkatesh Saligrama

Jan 12, 2015

Feng Nan, Joseph Wang, Venkatesh Saligrama

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Constructing Hierarchical Image-tags Bimodal Representations for Word Tags Alternative Choice

Jul 04, 2013

Fangxiang Feng, Ruifan Li, Xiaojie Wang

Jul 04, 2013

Fangxiang Feng, Ruifan Li, Xiaojie Wang

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Cascaded Mutual Modulation for Visual Reasoning

Sep 06, 2018

Yiqun Yao, Jiaming Xu, Feng Wang, Bo Xu

Sep 06, 2018

Yiqun Yao, Jiaming Xu, Feng Wang, Bo Xu

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Fine-grained visual recognition with salient feature detection

Aug 14, 2018

Hui Feng, Shanshan Wang, Shuzhi Sam Ge

Aug 14, 2018

Hui Feng, Shanshan Wang, Shuzhi Sam Ge

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Fast L1-Minimization Algorithm for Sparse Approximation Based on an Improved LPNN-LCA framework

May 30, 2018

Hao Wang, Ruibin Feng, Chi-Sing Leung

May 30, 2018

Hao Wang, Ruibin Feng, Chi-Sing Leung

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Additive Margin Softmax for Face Verification

May 30, 2018

Feng Wang, Weiyang Liu, Haijun Liu, Jian Cheng

May 30, 2018

Feng Wang, Weiyang Liu, Haijun Liu, Jian Cheng

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