
A Review on Generative Adversarial Networks: Algorithms, Theory, and Applications
Generative adversarial networks (GANs) are a hot research topic recently...
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Multigrained Attention Networks for Single Image SuperResolution
Deep Convolutional Neural Networks (CNN) have drawn great attention in i...
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Which Factorization Machine Modeling is Better: A Theoretical Answer with Optimal Guarantee
Factorization machine (FM) is a popular machine learning model to captur...
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Environment Reconstruction with Hidden Confounders for Reinforcement Learning based Recommendation
Reinforcement learning aims at searching the best policy model for decis...
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MultiModal Graph Interaction for MultiGraph Convolution Network in Urban Spatiotemporal Forecasting
Graph convolution network based approaches have been recently used to mo...
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AutoSlim: An Automatic DNN Structured Pruning Framework for UltraHigh Compression Rates
Structured weight pruning is a representative model compression techniqu...
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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...
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Identifying Genetic Risk Factors via Sparse Group Lasso with Group Graph Structure
Genomewide association studies (GWA studies or GWAS) investigate the re...
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Selfpaced Convolutional Neural Network for Computer Aided Detection in Medical Imaging Analysis
Tissue characterization has long been an important component of Computer...
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Efficient Approximate Solutions to Mutual Information Based Global Feature Selection
Mutual Information (MI) is often used for feature selection when develop...
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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...
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Coupled Support Vector Machines for Supervised Domain Adaptation
Popular domain adaptation (DA) techniques learn a classifier for the tar...
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Nonconvex Onebit Singlelabel Multilabel Learning
We study an extreme scenario in multilabel learning where each training...
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The Second Order Linear Model
We study a fundamental class of regression models called the second orde...
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A Nonconvex OnePass Framework for Generalized Factorization Machine and RankOne Matrix Sensing
We develop an efficient alternating framework for learning a generalized...
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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...
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Scaling Up Sparse Support Vector Machines by Simultaneous Feature and Sample Reduction
Sparse support vector machine (SVM) is a popular classification techniqu...
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Geodesic Distance Function Learning via Heat Flow on Vector Fields
Learning a distance function or metric on a given data manifold is of gr...
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Orthogonal RankOne Matrix Pursuit for Low Rank Matrix Completion
In this paper, we propose an efficient and scalable low rank matrix comp...
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Generalization Bounds for Representative Domain Adaptation
In this paper, we propose a novel framework to analyze the theoretical p...
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ForwardBackward Greedy Algorithms for General Convex Smooth Functions over A Cardinality Constraint
We consider forwardbackward greedy algorithms for solving sparse featur...
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Safe Screening With Variational Inequalities and Its Application to LASSO
Sparse learning techniques have been routinely used for feature selectio...
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Efficient MixedNorm Regularization: Algorithms and Safe Screening Methods
Sparse learning has recently received increasing attention in many areas...
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A Safe Screening Rule for Sparse Logistic Regression
The l1regularized logistic regression (or sparse logistic regression) i...
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Dictionary LASSO: Guaranteed Sparse Recovery under Linear Transformation
We consider the following signal recovery problem: given a measurement m...
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A General Iterative Shrinkage and Thresholding Algorithm for Nonconvex Regularized Optimization Problems
Nonconvex sparsityinducing penalties have recently received considerab...
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Lasso Screening Rules via Dual Polytope Projection
Lasso is a widely used regression technique to find sparse representatio...
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MultiStage MultiTask Feature Learning
Multitask sparse feature learning aims to improve the generalization pe...
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Fused Multiple Graphical Lasso
In this paper, we consider the problem of estimating multiple graphical ...
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Sparse Trace Norm Regularization
We study the problem of estimating multiple predictive functions from a ...
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Efficient Sparse Group Feature Selection via Nonconvex Optimization
Sparse feature selection has been demonstrated to be effective in handli...
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Persistent Homology in Sparse Regression and Its Application to Brain Morphometry
Sparse systems are usually parameterized by a tuning parameter that dete...
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MultiTask Feature Learning Via Efficient l2,1Norm Minimization
The problem of joint feature selection across a group of related tasks h...
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Deep MultiView SpatialTemporal Network for Taxi Demand Prediction
Taxi demand prediction is an important building block to enabling intell...
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GESF: A Universal Discriminative Mapping Mechanism for Graph Representation Learning
Graph embedding is a central problem in social network analysis and many...
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Optimizing Taxi Carpool Policies via Reinforcement Learning and SpatioTemporal Mining
In this paper, we develop a reinforcement learning (RL) based system to ...
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D^2City: A LargeScale Dashcam Video Dataset of Diverse Traffic Scenarios
Driving datasets accelerate the development of intelligent driving and r...
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Object Detection in 20 Years: A Survey
Object detection, as of one the most fundamental and challenging problem...
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POI Semantic Model with a Deep Convolutional Structure
When using the electronic map, POI retrieval is the initial and importan...
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Where to Find Next Passengers on Ehailing Platforms?  A Markov Decision Process Approach
Vacant taxi drivers' passenger seeking process in a road network generat...
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Efficient Ridesharing Order Dispatching with Mean Field MultiAgent Reinforcement Learning
A fundamental question in any peertopeer ridesharing system is how to,...
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Optimizing Online Matching for RideSourcing Services with MultiAgent Deep Reinforcement Learning
Ridesourcing services are now reshaping the way people travel by effect...
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Reward Advancement: Transforming Policy under Maximum Causal Entropy Principle
Many realworld human behaviors can be characterized as a sequential dec...
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CoRide: Joint Order Dispatching and Fleet Management for MultiScale RideHailing Platforms
How to optimally dispatch orders to vehicles and how to trade off betwee...
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AutoCompress: An Automatic DNN Structured Pruning Framework for UltraHigh Compression Rates
Structured weight pruning is a representative model compression techniqu...
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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...
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Predicting origindestination ridesourcing demand with a spatiotemporal encoderdecoder residual multigraph convolutional network
With the rapid development of mobileinternet technologies, ondemand ri...
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Building Effective LargeScale Traffic State Prediction System: Traffic4cast Challenge Solution
How to build an effective largescale traffic state prediction system is...
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Deep Reinforcement Learning for MultiDriver Vehicle Dispatching and Repositioning Problem
Order dispatching and driver repositioning (also known as fleet manageme...
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An Attentionbased Graph Neural Network for Heterogeneous Structural Learning
In this paper, we focus on graph representation learning of heterogeneou...
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Jieping Ye
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VP of Didi Research at Didi Chuxing, Associate Professor at University of Michigan