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07/19/2023
UniMatch: A Unified User-Item Matching Framework for the Multi-purpose Merchant Marketing
When doing private domain marketing with cloud services, the merchants u...
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05/25/2023
SimHaze: game engine simulated data for real-world dehazing
Deep models have demonstrated recent success in single-image dehazing. M...
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10/20/2021
Learning Universal User Representations via Self-Supervised Lifelong Behaviors Modeling
Universal user representation is an important research topic in industry...
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09/18/2021
Interest-oriented Universal User Representation via Contrastive Learning
User representation is essential for providing high-quality commercial s...
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05/18/2021
Markdowns in E-Commerce Fresh Retail: A Counterfactual Prediction and Multi-Period Optimization Approach
In this paper, by leveraging abundant observational transaction data, we...
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01/27/2021
Adversaries in Online Learning Revisited: with applications in Robust Optimization and Adversarial training
We revisit the concept of "adversary" in online learning, motivated by s...
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08/17/2020
Multi-Agent Coverage in Urban Environments
We study multi-agent coverage algorithms for autonomous monitoring and p...
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06/12/2020
Effective Training Strategies for Deep Graph Neural Networks
Graph Neural Networks (GNNs) tend to suffer performance degradation as m...
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06/02/2020
Maximizing Cumulative User Engagement in Sequential Recommendation: An Online Optimization Perspective
To maximize cumulative user engagement (e.g. cumulative clicks) in seque...
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02/27/2020
Time Series Data Augmentation for Deep Learning: A Survey
Deep learning performs remarkably well on many time series analysis task...
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02/21/2020
RobustTAD: Robust Time Series Anomaly Detection via Decomposition and Convolutional Neural Networks
The monitoring and management of numerous and diverse time series data a...
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02/21/2020
RobustPeriod: Time-Frequency Mining for Robust Multiple Periodicities Detection
Periodicity detection is an important task in time series analysis as it...
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07/17/2019
Competing Against Equilibria in Zero-Sum Games with Evolving Payoffs
We study the problem of repeated play in a zero-sum game in which the pa...
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06/07/2019
Inductive Bias of Gradient Descent based Adversarial Training on Separable Data
Adversarial training is a principled approach for training robust neural...
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06/05/2019
Robustness and Tractability for Non-convex M-estimators
We investigate two important properties of M-estimator, namely, robustne...
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06/04/2019
Bayesian Active Learning With Abstention Feedbacks
We study pool-based active learning with abstention feedbacks where a la...
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05/25/2019
Large Scale Markov Decision Processes with Changing Rewards
We consider Markov Decision Processes (MDPs) where the rewards are unkno...
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02/22/2019
LSwarm: Efficient Collision Avoidance for Large Swarms with Coverage Constraints in Complex Urban Scenes
In this paper, we address the problem of collision avoidance for a swarm...
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02/04/2019
A Unified Framework for Marketing Budget Allocation
While marketing budget allocation has been studied for decades in tradit...
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01/27/2019
Value Propagation for Decentralized Networked Deep Multi-agent Reinforcement Learning
We consider the networked multi-agent reinforcement learning (MARL) prob...
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12/05/2018
RobustSTL: A Robust Seasonal-Trend Decomposition Algorithm for Long Time Series
Decomposing complex time series into trend, seasonality, and remainder c...
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10/01/2018
Risk-Averse Stochastic Convex Bandit
Motivated by applications in clinical trials and finance, we study the p...
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06/21/2018
Online Saddle Point Problem with Applications to Constrained Online Convex Optimization
We study an online saddle point problem where at each iteration a pair o...
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05/27/2018
Robust Hypothesis Testing Using Wasserstein Uncertainty Sets
We develop a novel computationally efficient and general framework for r...
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05/20/2018
Projection-Free Algorithms in Statistical Estimation
Frank-Wolfe algorithm (FW) and its variants have gained a surge of inter...
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05/20/2018
Communication-Efficient Projection-Free Algorithm for Distributed Optimization
Distributed optimization has gained a surge of interest in recent years....
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05/20/2018
Nonlinear Distributional Gradient Temporal-Difference Learning
We devise a distributional variant of gradient temporal-difference (TD) ...
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04/30/2018
A Multi-State Diagnosis and Prognosis Framework with Feature Learning for Tool Condition Monitoring
In this paper, a multi-state diagnosis and prognosis (MDP) framework is ...
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02/13/2018
Fast Global Convergence via Landscape of Empirical Loss
While optimizing convex objective (loss) functions has been a powerhouse...
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11/08/2017
Learning Deep Mean Field Games for Modeling Large Population Behavior
We consider the problem of representing collective behavior of large pop...
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11/08/2017
Deep Mean Field Games for Learning Optimal Behavior Policy of Large Populations
We consider the problem of representing a large population's behavior po...
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06/15/2017
Reinforcement Learning under Model Mismatch
We study reinforcement learning under model misspecification, where we d...
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05/23/2017
Bayesian Pool-based Active Learning With Abstention Feedbacks
We study pool-based active learning with abstention feedbacks, where a l...
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02/19/2017
SAGA and Restricted Strong Convexity
SAGA is a fast incremental gradient method on the finite sum problem and...
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01/26/2017
Linear convergence of SDCA in statistical estimation
In this paper, we consider stochastic dual coordinate (SDCA) without st...
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01/01/2017
Outlier Robust Online Learning
We consider the problem of learning from noisy data in practical setting...
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11/07/2016
Linear Convergence of SVRG in Statistical Estimation
SVRG and its variants are among the state of art optimization algorithms...
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07/30/2016
Online Nonnegative Matrix Factorization with General Divergences
We develop a unified and systematic framework for performing online nonn...
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05/23/2016
Accelerated Stochastic Mirror Descent Algorithms For Composite Non-strongly Convex Optimization
We consider the problem of minimizing the sum of an average function of ...
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03/30/2016
Adaptive Maximization of Pointwise Submodular Functions With Budget Constraint
We study the worst-case adaptive optimization problem with budget constr...
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02/07/2016
Ensemble Robustness and Generalization of Stochastic Deep Learning Algorithms
The question why deep learning algorithms generalize so well has attract...
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04/24/2015
Social Trust Prediction via Max-norm Constrained 1-bit Matrix Completion
Social trust prediction addresses the significant problem of exploring i...
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03/28/2015
Efficient Online Minimization for Low-Rank Subspace Clustering
Low-rank representation (LRR) has been a significant method for segmenti...
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09/21/2014
Distributed Robust Learning
We propose a framework for distributed robust statistical learning on b...
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09/05/2013
Noisy Sparse Subspace Clustering
This paper considers the problem of subspace clustering under noise. Spe...
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06/26/2013
Scaling Up Robust MDPs by Reinforcement Learning
We consider large-scale Markov decision processes (MDPs) with parameter ...
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10/11/2012
Improved Graph Clustering
Graph clustering involves the task of dividing nodes into clusters, so t...
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09/08/2011
Exact Subspace Segmentation and Outlier Detection by Low-Rank Representation
In this work, we address the following matrix recovery problem: suppose ...
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04/25/2011
Clustering Partially Observed Graphs via Convex Optimization
This paper considers the problem of clustering a partially observed unwe...
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02/10/2011