
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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MultiAgent Coverage in Urban Environments
We study multiagent coverage algorithms for autonomous monitoring and p...
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Effective Training Strategies for Deep Graph Neural Networks
Graph Neural Networks (GNNs) tend to suffer performance degradation as m...
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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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Time Series Data Augmentation for Deep Learning: A Survey
Deep learning performs remarkably well on many time series analysis task...
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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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RobustPeriod: TimeFrequency Mining for Robust Multiple Periodicities Detection
Periodicity detection is an important task in time series analysis as it...
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Competing Against Equilibria in ZeroSum Games with Evolving Payoffs
We study the problem of repeated play in a zerosum game in which the pa...
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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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Robustness and Tractability for Nonconvex Mestimators
We investigate two important properties of Mestimator, namely, robustne...
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Bayesian Active Learning With Abstention Feedbacks
We study poolbased active learning with abstention feedbacks where a la...
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Large Scale Markov Decision Processes with Changing Rewards
We consider Markov Decision Processes (MDPs) where the rewards are unkno...
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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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A Unified Framework for Marketing Budget Allocation
While marketing budget allocation has been studied for decades in tradit...
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Value Propagation for Decentralized Networked Deep Multiagent Reinforcement Learning
We consider the networked multiagent reinforcement learning (MARL) prob...
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RobustSTL: A Robust SeasonalTrend Decomposition Algorithm for Long Time Series
Decomposing complex time series into trend, seasonality, and remainder c...
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RiskAverse Stochastic Convex Bandit
Motivated by applications in clinical trials and finance, we study the p...
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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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Robust Hypothesis Testing Using Wasserstein Uncertainty Sets
We develop a novel computationally efficient and general framework for r...
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ProjectionFree Algorithms in Statistical Estimation
FrankWolfe algorithm (FW) and its variants have gained a surge of inter...
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CommunicationEfficient ProjectionFree Algorithm for Distributed Optimization
Distributed optimization has gained a surge of interest in recent years....
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Nonlinear Distributional Gradient TemporalDifference Learning
We devise a distributional variant of gradient temporaldifference (TD) ...
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A MultiState Diagnosis and Prognosis Framework with Feature Learning for Tool Condition Monitoring
In this paper, a multistate diagnosis and prognosis (MDP) framework is ...
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Fast Global Convergence via Landscape of Empirical Loss
While optimizing convex objective (loss) functions has been a powerhouse...
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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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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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Reinforcement Learning under Model Mismatch
We study reinforcement learning under model misspecification, where we d...
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Bayesian Poolbased Active Learning With Abstention Feedbacks
We study poolbased active learning with abstention feedbacks, where a l...
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SAGA and Restricted Strong Convexity
SAGA is a fast incremental gradient method on the finite sum problem and...
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Linear convergence of SDCA in statistical estimation
In this paper, we consider stochastic dual coordinate (SDCA) without st...
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Outlier Robust Online Learning
We consider the problem of learning from noisy data in practical setting...
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Linear Convergence of SVRG in Statistical Estimation
SVRG and its variants are among the state of art optimization algorithms...
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Online Nonnegative Matrix Factorization with General Divergences
We develop a unified and systematic framework for performing online nonn...
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Accelerated Stochastic Mirror Descent Algorithms For Composite Nonstrongly Convex Optimization
We consider the problem of minimizing the sum of an average function of ...
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Adaptive Maximization of Pointwise Submodular Functions With Budget Constraint
We study the worstcase adaptive optimization problem with budget constr...
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Ensemble Robustness and Generalization of Stochastic Deep Learning Algorithms
The question why deep learning algorithms generalize so well has attract...
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Social Trust Prediction via Maxnorm Constrained 1bit Matrix Completion
Social trust prediction addresses the significant problem of exploring i...
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Efficient Online Minimization for LowRank Subspace Clustering
Lowrank representation (LRR) has been a significant method for segmenti...
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Distributed Robust Learning
We propose a framework for distributed robust statistical learning on b...
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Noisy Sparse Subspace Clustering
This paper considers the problem of subspace clustering under noise. Spe...
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Scaling Up Robust MDPs by Reinforcement Learning
We consider largescale Markov decision processes (MDPs) with parameter ...
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Improved Graph Clustering
Graph clustering involves the task of dividing nodes into clusters, so t...
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Exact Subspace Segmentation and Outlier Detection by LowRank Representation
In this work, we address the following matrix recovery problem: suppose ...
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Clustering Partially Observed Graphs via Convex Optimization
This paper considers the problem of clustering a partially observed unwe...
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Matrix completion with column manipulation: Nearoptimal samplerobustnessrank tradeoffs
This paper considers the problem of matrix completion when some number o...
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Robust PCA via Outlier Pursuit
Singular Value Decomposition (and Principal Component Analysis) is one o...
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