
ZOAdaMM: ZerothOrder Adaptive Momentum Method for BlackBox Optimization
The adaptive momentum method (AdaMM), which uses past gradients to updat...
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On Computation and Generalization of Generative Adversarial Imitation Learning
Generative Adversarial Imitation Learning (GAIL) is a powerful and pract...
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Overparameterized Adversarial Training: An Analysis Overcoming the Curse of Dimensionality
Adversarial training is a popular method to give neural nets robustness ...
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On Generalization Bounds of a Family of Recurrent Neural Networks
Recurrent Neural Networks (RNNs) have been widely applied to sequential ...
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On Tighter Generalization Bound for Deep Neural Networks: CNNs, ResNets, and Beyond
Our paper proposes a generalization error bound for a general family of ...
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Deep Hyperspherical Learning
Convolution as inner product has been the founding basis of convolutiona...
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Towards Blackbox Iterative Machine Teaching
In this paper, we make an important step towards the blackbox machine t...
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Near Optimal Sketching of LowRank Tensor Regression
We study the least squares regression problem _Θ∈S_ D,RAΘb_2, where S_...
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On Quadratic Convergence of DC Proximal Newton Algorithm for Nonconvex Sparse Learning in High Dimensions
We propose a DC proximal Newton algorithm for solving nonconvex regulari...
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Symmetry, Saddle Points, and Global Geometry of Nonconvex Matrix Factorization
We propose a general theory for studying the geometry of nonconvex objec...
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On Faster Convergence of Cyclic Block Coordinate Descenttype Methods for Strongly Convex Minimization
The cyclic block coordinate descenttype (CBCDtype) methods, which perf...
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A First Order Free Lunch for SQRTLasso
Many statistical machine learning techniques sacrifice convenient comput...
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Nonconvex Sparse Learning via Stochastic Optimization with Progressive Variance Reduction
We propose a stochastic variance reduced optimization algorithm for solv...
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Identifying Outliers in Large Matrices via Randomized Adaptive Compressive Sampling
This paper examines the problem of locating outlier columns in a large, ...
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On Landscape of Lagrangian Functions and Stochastic Search for Constrained Nonconvex Optimization
We study constrained nonconvex optimization problems in machine learning...
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A DictionaryBased Generalization of Robust PCA Part I: Study of Theoretical Properties
We consider the decomposition of a data matrix assumed to be a superposi...
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A Dictionary Based Generalization of Robust PCA
We analyze the decomposition of a data matrix, assumed to be a superposi...
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Targetbased Hyperspectral Demixing via Generalized Robust PCA
Localizing targets of interest in a given hyperspectral (HS) image has a...
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A DictionaryBased Generalization of Robust PCA Part II: Applications to Hyperspectral Demixing
We consider the task of localizing targets of interest in a hyperspectra...
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NOODL: Provable Online Dictionary Learning and Sparse Coding
We consider the dictionary learning problem, where the aim is to model t...
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On Recoverability of Randomly Compressed Tensors with Low CP Rank
Our interest lies in the recoverability properties of compressed tensors...
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Xingguo Li
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