Jieping Ye

A Review on Generative Adversarial Networks: Algorithms, Theory, and Applications

Generative adversarial networks (GANs) are a hot research topic recently...
01/20/2020 ∙ by Jie Gui, et al. ∙ 75 ∙ share

read it
Multi-grained Attention Networks for Single Image Super-Resolution

Deep Convolutional Neural Networks (CNN) have drawn great attention in i...
09/26/2019 ∙ by Huapeng Wu, et al. ∙ 26 ∙ share

read 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 ∙ share

read 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 ∙ share

read it
Multi-Modal Graph Interaction for Multi-Graph 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 ∙ share

read it
AutoSlim: An Automatic DNN Structured Pruning Framework for Ultra-High Compression Rates

Structured weight pruning is a representative model compression techniqu...
07/06/2019 ∙ by Ning Liu, et al. ∙ 2 ∙ share

read 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 ∙ share

read it
Identifying Genetic Risk Factors via Sparse Group Lasso with Group Graph Structure

Genome-wide association studies (GWA studies or GWAS) investigate the re...
09/12/2017 ∙ by Tao Yang, et al. ∙ 0 ∙ share

read it
Self-paced 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 ∙ share

read 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 ∙ share

read it
Large-scale Feature Selection of Risk Genetic Factors for Alzheimer's Disease via Distributed Group Lasso Regression

Genome-wide association studies (GWAS) have achieved great success in th...
04/27/2017 ∙ by Qingyang Li, et al. ∙ 0 ∙ share

read 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 ∙ share

read it
Nonconvex One-bit Single-label Multi-label Learning

We study an extreme scenario in multi-label learning where each training...
03/17/2017 ∙ by Shuang Qiu, et al. ∙ 0 ∙ share

read 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 ∙ share

read it
A Non-convex One-Pass Framework for Generalized Factorization Machine and Rank-One Matrix Sensing

We develop an efficient alternating framework for learning a generalized...
08/21/2016 ∙ by Ming Lin, et al. ∙ 0 ∙ share

read it
Large-scale Collaborative Imaging Genetics Studies of Risk Genetic Factors for Alzheimer's Disease Across Multiple Institutions

Genome-wide association studies (GWAS) offer new opportunities to identi...
08/19/2016 ∙ by Qingyang Li, et al. ∙ 0 ∙ share

read 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 ∙ share

read 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 ∙ share

read it
Orthogonal Rank-One 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 ∙ share

read 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 ∙ share

read it
Forward-Backward Greedy Algorithms for General Convex Smooth Functions over A Cardinality Constraint

We consider forward-backward greedy algorithms for solving sparse featur...
12/31/2013 ∙ by Ji Liu, et al. ∙ 0 ∙ share

read 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 ∙ share

read it
Efficient Mixed-Norm 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 ∙ share

read it
A Safe Screening Rule for Sparse Logistic Regression

The l1-regularized logistic regression (or sparse logistic regression) i...
07/16/2013 ∙ by Jie Wang, et al. ∙ 0 ∙ share

read 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 ∙ share

read it
A General Iterative Shrinkage and Thresholding Algorithm for Non-convex Regularized Optimization Problems

Non-convex sparsity-inducing penalties have recently received considerab...
03/18/2013 ∙ by Pinghua Gong, et al. ∙ 0 ∙ share

read 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 ∙ share

read it
Multi-Stage Multi-Task Feature Learning

Multi-task sparse feature learning aims to improve the generalization pe...
10/22/2012 ∙ by Pinghua Gong, et al. ∙ 0 ∙ share

read 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 ∙ share

read 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 ∙ share

read 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 ∙ share

read 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 ∙ share

read it
Multi-Task Feature Learning Via Efficient l2,1-Norm Minimization

The problem of joint feature selection across a group of related tasks h...
05/09/2012 ∙ by Jun Liu, et al. ∙ 0 ∙ share

read it
Deep Multi-View Spatial-Temporal 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 ∙ share

read 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 ∙ share

read it
Optimizing Taxi Carpool Policies via Reinforcement Learning and Spatio-Temporal Mining

In this paper, we develop a reinforcement learning (RL) based system to ...
11/11/2018 ∙ by Ishan Jindal, et al. ∙ 0 ∙ share

read it
D^2-City: A Large-Scale 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 ∙ share

read 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 ∙ share

read 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 ∙ share

read it
Where to Find Next Passengers on E-hailing 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 ∙ share

read it
Efficient Ridesharing Order Dispatching with Mean Field Multi-Agent Reinforcement Learning

A fundamental question in any peer-to-peer ridesharing system is how to,...
01/31/2019 ∙ by Minne Li, et al. ∙ 0 ∙ share

read it
Optimizing Online Matching for Ride-Sourcing Services with Multi-Agent Deep Reinforcement Learning

Ride-sourcing services are now reshaping the way people travel by effect...
02/17/2019 ∙ by Jintao Ke, et al. ∙ 0 ∙ share

read it
Reward Advancement: Transforming Policy under Maximum Causal Entropy Principle

Many real-world human behaviors can be characterized as a sequential dec...
07/11/2019 ∙ by Guojun Wu, et al. ∙ 0 ∙ share

read it
CoRide: Joint Order Dispatching and Fleet Management for Multi-Scale Ride-Hailing Platforms

How to optimally dispatch orders to vehicles and how to trade off betwee...
05/27/2019 ∙ by Jiarui Jin, et al. ∙ 0 ∙ share

read it
AutoCompress: An Automatic DNN Structured Pruning Framework for Ultra-High Compression Rates

Structured weight pruning is a representative model compression techniqu...
07/06/2019 ∙ by Ning Liu, et al. ∙ 0 ∙ share

read 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 ∙ share

read it
Predicting origin-destination ride-sourcing demand with a spatio-temporal encoder-decoder residual multi-graph convolutional network

With the rapid development of mobile-internet technologies, on-demand ri...
10/17/2019 ∙ by Jintao Ke, et al. ∙ 0 ∙ share

read it
Building Effective Large-Scale Traffic State Prediction System: Traffic4cast Challenge Solution

How to build an effective large-scale traffic state prediction system is...
11/11/2019 ∙ by Yang Liu, et al. ∙ 0 ∙ share

read it
Deep Reinforcement Learning for Multi-Driver Vehicle Dispatching and Repositioning Problem

Order dispatching and driver repositioning (also known as fleet manageme...
11/25/2019 ∙ by John Holler, et al. ∙ 0 ∙ share

read it
An Attention-based Graph Neural Network for Heterogeneous Structural Learning

In this paper, we focus on graph representation learning of heterogeneou...
12/19/2019 ∙ by Huiting Hong, et al. ∙ 0 ∙ share

read it

Jieping Ye

Featured Co-authors