
Risk Bounds and Rademacher Complexity in Batch Reinforcement Learning
This paper considers batch Reinforcement Learning (RL) with general valu...
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A TwoStage Variable Selection Approach for Correlated High Dimensional Predictors
When fitting statistical models, some predictors are often found to be c...
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On the Validity of Modeling SGD with Stochastic Differential Equations (SDEs)
It is generally recognized that finite learning rate (LR), in contrast t...
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Towards Resolving the Implicit Bias of Gradient Descent for Matrix Factorization: Greedy LowRank Learning
Matrix factorization is a simple and natural testbed to investigate the...
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Why Are Convolutional Nets More SampleEfficient than FullyConnected Nets?
Convolutional neural networks often dominate fullyconnected counterpart...
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Reconciling Modern Deep Learning with Traditional Optimization Analyses: The Intrinsic Learning Rate
Recent works (e.g., (Li and Arora, 2020)) suggest that the use of popula...
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Learning GeometryDependent and PhysicsBased Inverse Image Reconstruction
Deep neural networks have shown great potential in image reconstruction ...
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When is Particle Filtering Efficient for POMDP Sequential Planning?
Particle filtering is a popular method for inferring latent states in st...
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Semisupervised Medical Image Classification with Global Latent Mixing
Computeraided diagnosis via deep learning relies on largescale annotat...
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Progressive Learning and Disentanglement of Hierarchical Representations
Learning rich representation from data is an important task for deep gen...
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Implicit Regularization of Normalization Methods
Normalization methods such as batch normalization are commonly used in o...
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Enhanced Convolutional Neural Tangent Kernels
Recent research shows that for training with ℓ_2 loss, convolutional neu...
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An Exponential Learning Rate Schedule for Deep Learning
Intriguing empirical evidence exists that deep learning can work well wi...
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Harnessing the Power of Infinitely Wide Deep Nets on Smalldata Tasks
Recent research shows that the following two models are equivalent: (a) ...
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Improving Disentangled Representation Learning with the Beta Bernoulli Process
To improve the ability of VAE to disentangle in the latent space, existi...
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SemiSupervised Learning by Disentangling and SelfEnsembling Over Stochastic Latent Space
The success of deep learning in medical imaging is mostly achieved at th...
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Explaining Landscape Connectivity of Lowcost Solutions for Multilayer Nets
Mode connectivity is a surprising phenomenon in the loss landscape of de...
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Featurelevel and Modellevel Audiovisual Fusion for Emotion Recognition in the Wild
Emotion recognition plays an important role in humancomputer interactio...
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Understanding Generalization of Deep Neural Networks Trained with Noisy Labels
Overparameterized deep neural networks trained by simple firstorder me...
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On Exact Computation with an Infinitely Wide Neural Net
How well does a classic deep net architecture like AlexNet or VGG19 clas...
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IdentityFree Facial Expression Recognition using conditional Generative Adversarial Network
In this paper, we proposed a novel Identityfree conditional Generative ...
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FineGrained Analysis of Optimization and Generalization for Overparameterized TwoLayer Neural Networks
Recent works have cast some light on the mystery of why deep nets fit an...
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Probabilistic Attribute Tree in Convolutional Neural Networks for Facial Expression Recognition
In this paper, we proposed a novel Probabilistic Attribute TreeCNN (PAT...
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Theoretical Analysis of Auto RateTuning by Batch Normalization
Batch Normalization (BN) has become a cornerstone of deep learning acros...
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Deep Template Matching for Offline Handwritten Chinese Character Recognition
Just like its remarkable achievements in many computer vision tasks, the...
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Towards Understanding the Role of OverParametrization in Generalization of Neural Networks
Despite existing work on ensuring generalization of neural networks in t...
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Online Improper Learning with an Approximation Oracle
We revisit the question of reducing online learning to approximate optim...
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Building Efficient CNN Architecture for Offline Handwritten Chinese Character Recognition
Deep convolutional networks based methods have brought great breakthroug...
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Island Loss for Learning Discriminative Features in Facial Expression Recognition
Over the past few years, Convolutional Neural Networks (CNNs) have shown...
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Optimizing Filter Size in Convolutional Neural Networks for Facial Action Unit Recognition
Recognizing facial action units (AUs) during spontaneous facial displays...
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Solving Marginal MAP Problems with NP Oracles and Parity Constraints
Arising from many applications at the intersection of decision making an...
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Zhiyuan Li
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