
Multigrained Attention Networks for Single Image SuperResolution
Deep Convolutional Neural Networks (CNN) have drawn great attention in i...
09/26/2019 ∙ by Huapeng Wu, et al. ∙ 26 ∙ shareread it

Which Factorization Machine Modeling is Better: A Theoretical Answer with Optimal Guarantee
Factorization machine (FM) is a popular machine learning model to captur...
01/30/2019 ∙ by Ming Lin, et al. ∙ 8 ∙ shareread it

Environment Reconstruction with Hidden Confounders for Reinforcement Learning based Recommendation
Reinforcement learning aims at searching the best policy model for decis...
07/12/2019 ∙ by Wenjie Shang, et al. ∙ 4 ∙ shareread it

MultiModal Graph Interaction for MultiGraph Convolution Network in Urban Spatiotemporal Forecasting
Graph convolution network based approaches have been recently used to mo...
05/27/2019 ∙ by Xu Geng, et al. ∙ 2 ∙ shareread it

AutoSlim: An Automatic DNN Structured Pruning Framework for UltraHigh Compression Rates
Structured weight pruning is a representative model compression techniqu...
07/06/2019 ∙ by Ning Liu, et al. ∙ 2 ∙ shareread it

A Unified Neural Network Approach for Estimating Travel Time and Distance for a Taxi Trip
In building intelligent transportation systems such as taxi or rideshare...
10/12/2017 ∙ by Ishan Jindal, et al. ∙ 0 ∙ shareread it

Identifying Genetic Risk Factors via Sparse Group Lasso with Group Graph Structure
Genomewide association studies (GWA studies or GWAS) investigate the re...
09/12/2017 ∙ by Tao Yang, et al. ∙ 0 ∙ shareread it

Selfpaced Convolutional Neural Network for Computer Aided Detection in Medical Imaging Analysis
Tissue characterization has long been an important component of Computer...
07/19/2017 ∙ by Xiang Li, et al. ∙ 0 ∙ shareread it

Efficient Approximate Solutions to Mutual Information Based Global Feature Selection
Mutual Information (MI) is often used for feature selection when develop...
06/23/2017 ∙ by Hemanth Venkateswara, et al. ∙ 0 ∙ shareread it

Largescale Feature Selection of Risk Genetic Factors for Alzheimer's Disease via Distributed Group Lasso Regression
Genomewide association studies (GWAS) have achieved great success in th...
04/27/2017 ∙ by Qingyang Li, et al. ∙ 0 ∙ shareread it

Coupled Support Vector Machines for Supervised Domain Adaptation
Popular domain adaptation (DA) techniques learn a classifier for the tar...
06/22/2017 ∙ by Hemanth Venkateswara, et al. ∙ 0 ∙ shareread it

Nonconvex Onebit Singlelabel Multilabel Learning
We study an extreme scenario in multilabel learning where each training...
03/17/2017 ∙ by Shuang Qiu, et al. ∙ 0 ∙ shareread it

The Second Order Linear Model
We study a fundamental class of regression models called the second orde...
03/02/2017 ∙ by Ming Lin, et al. ∙ 0 ∙ shareread it

A Nonconvex OnePass Framework for Generalized Factorization Machine and RankOne Matrix Sensing
We develop an efficient alternating framework for learning a generalized...
08/21/2016 ∙ by Ming Lin, et al. ∙ 0 ∙ shareread it

Largescale Collaborative Imaging Genetics Studies of Risk Genetic Factors for Alzheimer's Disease Across Multiple Institutions
Genomewide association studies (GWAS) offer new opportunities to identi...
08/19/2016 ∙ by Qingyang Li, et al. ∙ 0 ∙ shareread it

Scaling Up Sparse Support Vector Machines by Simultaneous Feature and Sample Reduction
Sparse support vector machine (SVM) is a popular classification techniqu...
07/24/2016 ∙ by Weizhong Zhang, et al. ∙ 0 ∙ shareread it

Geodesic Distance Function Learning via Heat Flow on Vector Fields
Learning a distance function or metric on a given data manifold is of gr...
05/01/2014 ∙ by Binbin Lin, et al. ∙ 0 ∙ shareread it

Orthogonal RankOne Matrix Pursuit for Low Rank Matrix Completion
In this paper, we propose an efficient and scalable low rank matrix comp...
04/04/2014 ∙ by Zheng Wang, et al. ∙ 0 ∙ shareread it

Generalization Bounds for Representative Domain Adaptation
In this paper, we propose a novel framework to analyze the theoretical p...
01/02/2014 ∙ by Chao Zhang, et al. ∙ 0 ∙ shareread it

ForwardBackward Greedy Algorithms for General Convex Smooth Functions over A Cardinality Constraint
We consider forwardbackward greedy algorithms for solving sparse featur...
12/31/2013 ∙ by Ji Liu, et al. ∙ 0 ∙ shareread it

Safe Screening With Variational Inequalities and Its Application to LASSO
Sparse learning techniques have been routinely used for feature selectio...
07/29/2013 ∙ by Jun Liu, et al. ∙ 0 ∙ shareread it

Efficient MixedNorm Regularization: Algorithms and Safe Screening Methods
Sparse learning has recently received increasing attention in many areas...
07/16/2013 ∙ by Jie Wang, et al. ∙ 0 ∙ shareread it

A Safe Screening Rule for Sparse Logistic Regression
The l1regularized logistic regression (or sparse logistic regression) i...
07/16/2013 ∙ by Jie Wang, et al. ∙ 0 ∙ shareread it

Dictionary LASSO: Guaranteed Sparse Recovery under Linear Transformation
We consider the following signal recovery problem: given a measurement m...
04/30/2013 ∙ by Ji Liu, et al. ∙ 0 ∙ shareread it

A General Iterative Shrinkage and Thresholding Algorithm for Nonconvex Regularized Optimization Problems
Nonconvex sparsityinducing penalties have recently received considerab...
03/18/2013 ∙ by Pinghua Gong, et al. ∙ 0 ∙ shareread it

Lasso Screening Rules via Dual Polytope Projection
Lasso is a widely used regression technique to find sparse representatio...
11/16/2012 ∙ by Jie Wang, et al. ∙ 0 ∙ shareread it

MultiStage MultiTask Feature Learning
Multitask sparse feature learning aims to improve the generalization pe...
10/22/2012 ∙ by Pinghua Gong, et al. ∙ 0 ∙ shareread it

Fused Multiple Graphical Lasso
In this paper, we consider the problem of estimating multiple graphical ...
09/10/2012 ∙ by Sen Yang, et al. ∙ 0 ∙ shareread it

Sparse Trace Norm Regularization
We study the problem of estimating multiple predictive functions from a ...
06/02/2012 ∙ by Jianhui Chen, et al. ∙ 0 ∙ shareread it

Efficient Sparse Group Feature Selection via Nonconvex Optimization
Sparse feature selection has been demonstrated to be effective in handli...
05/23/2012 ∙ by Shuo Xiang, et al. ∙ 0 ∙ shareread it

Persistent Homology in Sparse Regression and Its Application to Brain Morphometry
Sparse systems are usually parameterized by a tuning parameter that dete...
08/31/2014 ∙ by Moo K. Chung, et al. ∙ 0 ∙ shareread it

MultiTask Feature Learning Via Efficient l2,1Norm Minimization
The problem of joint feature selection across a group of related tasks h...
05/09/2012 ∙ by Jun Liu, et al. ∙ 0 ∙ shareread it

Deep MultiView SpatialTemporal Network for Taxi Demand Prediction
Taxi demand prediction is an important building block to enabling intell...
02/23/2018 ∙ by Huaxiu Yao, et al. ∙ 0 ∙ shareread it

GESF: A Universal Discriminative Mapping Mechanism for Graph Representation Learning
Graph embedding is a central problem in social network analysis and many...
05/28/2018 ∙ by Shupeng Gui, et al. ∙ 0 ∙ shareread it

Optimizing Taxi Carpool Policies via Reinforcement Learning and SpatioTemporal Mining
In this paper, we develop a reinforcement learning (RL) based system to ...
11/11/2018 ∙ by Ishan Jindal, et al. ∙ 0 ∙ shareread it

D^2City: A LargeScale Dashcam Video Dataset of Diverse Traffic Scenarios
Driving datasets accelerate the development of intelligent driving and r...
04/03/2019 ∙ by Zhengping Che, et al. ∙ 0 ∙ shareread it

Object Detection in 20 Years: A Survey
Object detection, as of one the most fundamental and challenging problem...
05/13/2019 ∙ by Zhengxia Zou, et al. ∙ 0 ∙ shareread it

POI Semantic Model with a Deep Convolutional Structure
When using the electronic map, POI retrieval is the initial and importan...
03/18/2019 ∙ by Ji Zhao, et al. ∙ 0 ∙ shareread it

Where to Find Next Passengers on Ehailing Platforms?  A Markov Decision Process Approach
Vacant taxi drivers' passenger seeking process in a road network generat...
05/23/2019 ∙ by Zhenyu Shou, et al. ∙ 0 ∙ shareread it

Efficient Ridesharing Order Dispatching with Mean Field MultiAgent Reinforcement Learning
A fundamental question in any peertopeer ridesharing system is how to,...
01/31/2019 ∙ by Minne Li, et al. ∙ 0 ∙ shareread it

Optimizing Online Matching for RideSourcing Services with MultiAgent Deep Reinforcement Learning
Ridesourcing services are now reshaping the way people travel by effect...
02/17/2019 ∙ by Jintao Ke, et al. ∙ 0 ∙ shareread it

Reward Advancement: Transforming Policy under Maximum Causal Entropy Principle
Many realworld human behaviors can be characterized as a sequential dec...
07/11/2019 ∙ by Guojun Wu, et al. ∙ 0 ∙ shareread it

CoRide: Joint Order Dispatching and Fleet Management for MultiScale RideHailing Platforms
How to optimally dispatch orders to vehicles and how to trade off betwee...
05/27/2019 ∙ by Jiarui Jin, et al. ∙ 0 ∙ shareread it

AutoCompress: An Automatic DNN Structured Pruning Framework for UltraHigh Compression Rates
Structured weight pruning is a representative model compression techniqu...
07/06/2019 ∙ by Ning Liu, et al. ∙ 0 ∙ shareread it

PINE: Universal Deep Embedding for Graph Nodes via Partial Permutation Invariant Set Functions
Graph node embedding aims at learning a vector representation for all no...
09/25/2019 ∙ by Shupeng Gui, et al. ∙ 0 ∙ shareread it

Predicting origindestination ridesourcing demand with a spatiotemporal encoderdecoder residual multigraph convolutional network
With the rapid development of mobileinternet technologies, ondemand ri...
10/17/2019 ∙ by Jintao Ke, et al. ∙ 0 ∙ shareread it

Building Effective LargeScale Traffic State Prediction System: Traffic4cast Challenge Solution
How to build an effective largescale traffic state prediction system is...
11/11/2019 ∙ by Yang Liu, et al. ∙ 0 ∙ shareread it

MultiAgent Reinforcement Learning for Orderdispatching via OrderVehicle Distribution Matching
Improving the efficiency of dispatching orders to vehicles is a research...
10/07/2019 ∙ by Ming Zhou, et al. ∙ 0 ∙ shareread it
Jieping Ye
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VP of Didi Research at Didi Chuxing, Associate Professor at University of Michigan