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08/12/2023
Distributionally Robust Optimization and Invariant Representation Learning for Addressing Subgroup Underrepresentation: Mechanisms and Limitations
Spurious correlation caused by subgroup underrepresentation has received...
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07/27/2023
The Marginal Value of Momentum for Small Learning Rate SGD
Momentum is known to accelerate the convergence of gradient descent in s...
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07/27/2023
Exploring Annotation-free Image Captioning with Retrieval-augmented Pseudo Sentence Generation
Training an image captioner without annotated image-sentence pairs has g...
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07/22/2023
Prototype-Driven and Multi-Expert Integrated Multi-Modal MR Brain Tumor Image Segmentation
For multi-modal magnetic resonance (MR) brain tumor image segmentation, ...
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07/20/2023
Sharpness Minimization Algorithms Do Not Only Minimize Sharpness To Achieve Better Generalization
Despite extensive studies, the underlying reason as to why overparameter...
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06/22/2023
The Inductive Bias of Flatness Regularization for Deep Matrix Factorization
Recent works on over-parameterized neural networks have shown that the s...
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05/23/2023
Sophia: A Scalable Stochastic Second-order Optimizer for Language Model Pre-training
Given the massive cost of language model pre-training, a non-trivial imp...
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04/16/2023
Learning Empirical Bregman Divergence for Uncertain Distance Representation
Deep metric learning techniques have been used for visual representation...
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02/20/2023
A Novel Collaborative Self-Supervised Learning Method for Radiomic Data
The computer-aided disease diagnosis from radiomic data is important in ...
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01/31/2023
Learning Generalized Hybrid Proximity Representation for Image Recognition
Recently, deep metric learning techniques received attention, as the lea...
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01/27/2023
Understanding Incremental Learning of Gradient Descent: A Fine-grained Analysis of Matrix Sensing
It is believed that Gradient Descent (GD) induces an implicit bias towar...
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11/10/2022
How Does Sharpness-Aware Minimization Minimize Sharpness?
Sharpness-Aware Minimization (SAM) is a highly effective regularization ...
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11/02/2022
Interpretable Modeling and Reduction of Unknown Errors in Mechanistic Operators
Prior knowledge about the imaging physics provides a mechanistic forward...
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10/25/2022
Same Pre-training Loss, Better Downstream: Implicit Bias Matters for Language Models
Language modeling on large-scale datasets leads to impressive performanc...
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10/06/2022
Few-shot Generation of Personalized Neural Surrogates for Cardiac Simulation via Bayesian Meta-Learning
Clinical adoption of personalized virtual heart simulations faces challe...
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07/08/2022
Implicit Bias of Gradient Descent on Reparametrized Models: On Equivalence to Mirror Descent
As part of the effort to understand implicit bias of gradient descent in...
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06/14/2022
Understanding the Generalization Benefit of Normalization Layers: Sharpness Reduction
Normalization layers (e.g., Batch Normalization, Layer Normalization) we...
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05/19/2022
Understanding Gradient Descent on Edge of Stability in Deep Learning
Deep learning experiments in Cohen et al. (2021) using deterministic Gra...
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05/16/2022
Peridynamic modeling for impact failure of wet concrete considering the influence of saturation
In this paper, a modified intermediately homogenized peridynamic (IH-PD)...
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03/24/2022
Interpretability of Neural Network With Physiological Mechanisms
Deep learning continues to play as a powerful state-of-art technique tha...
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02/08/2022
A Novel Ontology-guided Attribute Partitioning Ensemble Learning Model for Early Prediction of Cognitive Deficits using Quantitative Structural MRI in Very Preterm Infants
Structural magnetic resonance imaging studies have shown that brain anat...
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02/02/2022
Robust Training of Neural Networks using Scale Invariant Architectures
In contrast to SGD, adaptive gradient methods like Adam allow robust tra...
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11/25/2021
An inverse problem of determining fractional orders in a fractal solute transport model
A fractal mobile-immobile (MIM in short) solute transport model in porou...
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10/26/2021
Gradient Descent on Two-layer Nets: Margin Maximization and Simplicity Bias
The generalization mystery of overparametrized deep nets has motivated e...
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10/13/2021
What Happens after SGD Reaches Zero Loss? –A Mathematical Framework
Understanding the implicit bias of Stochastic Gradient Descent (SGD) is ...
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08/20/2021
DeFRCN: Decoupled Faster R-CNN for Few-Shot Object Detection
Few-shot object detection, which aims at detecting novel objects rapidly...
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08/18/2021
A reduced model for compressible viscous heat-conducting multicomponent flows
In the present paper we propose a reduced temperature non-equilibrium mo...
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03/25/2021
Risk Bounds and Rademacher Complexity in Batch Reinforcement Learning
This paper considers batch Reinforcement Learning (RL) with general valu...
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03/24/2021
A Two-Stage Variable Selection Approach for Correlated High Dimensional Predictors
When fitting statistical models, some predictors are often found to be c...
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02/24/2021
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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12/17/2020
Towards Resolving the Implicit Bias of Gradient Descent for Matrix Factorization: Greedy Low-Rank Learning
Matrix factorization is a simple and natural test-bed to investigate the...
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10/16/2020
Why Are Convolutional Nets More Sample-Efficient than Fully-Connected Nets?
Convolutional neural networks often dominate fully-connected counterpart...
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10/06/2020
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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07/18/2020
Learning Geometry-Dependent and Physics-Based Inverse Image Reconstruction
Deep neural networks have shown great potential in image reconstruction ...
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06/10/2020
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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05/22/2020
Semi-supervised Medical Image Classification with Global Latent Mixing
Computer-aided diagnosis via deep learning relies on large-scale annotat...
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02/24/2020
Progressive Learning and Disentanglement of Hierarchical Representations
Learning rich representation from data is an important task for deep gen...
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11/18/2019
Implicit Regularization of Normalization Methods
Normalization methods such as batch normalization are commonly used in o...
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11/03/2019
Enhanced Convolutional Neural Tangent Kernels
Recent research shows that for training with ℓ_2 loss, convolutional neu...
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10/16/2019
An Exponential Learning Rate Schedule for Deep Learning
Intriguing empirical evidence exists that deep learning can work well wi...
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10/03/2019
Harnessing the Power of Infinitely Wide Deep Nets on Small-data Tasks
Recent research shows that the following two models are equivalent: (a) ...
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09/03/2019
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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07/22/2019
Semi-Supervised Learning by Disentangling and Self-Ensembling Over Stochastic Latent Space
The success of deep learning in medical imaging is mostly achieved at th...
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06/14/2019
Explaining Landscape Connectivity of Low-cost Solutions for Multilayer Nets
Mode connectivity is a surprising phenomenon in the loss landscape of de...
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06/06/2019
Feature-level and Model-level Audiovisual Fusion for Emotion Recognition in the Wild
Emotion recognition plays an important role in human-computer interactio...
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05/27/2019
Understanding Generalization of Deep Neural Networks Trained with Noisy Labels
Over-parameterized deep neural networks trained by simple first-order me...
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04/26/2019
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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03/19/2019
Identity-Free Facial Expression Recognition using conditional Generative Adversarial Network
In this paper, we proposed a novel Identity-free conditional Generative ...
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01/24/2019
Fine-Grained Analysis of Optimization and Generalization for Overparameterized Two-Layer Neural Networks
Recent works have cast some light on the mystery of why deep nets fit an...
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12/17/2018
