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06/12/2023
Underwater Acoustic Target Recognition based on Smoothness-inducing Regularization and Spectrogram-based Data Augmentation
Underwater acoustic target recognition is a challenging task owing to th...
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05/31/2023
Underwater-Art: Expanding Information Perspectives With Text Templates For Underwater Acoustic Target Recognition
Underwater acoustic target recognition is an intractable task due to the...
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05/31/2023
Adaptive ship-radiated noise recognition with learnable fine-grained wavelet transform
Analyzing the ocean acoustic environment is a tricky task. Background no...
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04/24/2023
Advancing underwater acoustic target recognition via adaptive data pruning and smoothness-inducing regularization
Underwater acoustic recognition for ship-radiated signals has high pract...
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01/11/2023
Determinate Node Selection for Semi-supervised Classification Oriented Graph Convolutional Networks
Graph Convolutional Networks (GCNs) have been proved successful in the f...
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08/17/2022
Semi-supervised Learning with Deterministic Labeling and Large Margin Projection
The centrality and diversity of the labeled data are very influential to...
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02/22/2022
Improving CTC-based speech recognition via knowledge transferring from pre-trained language models
Recently, end-to-end automatic speech recognition models based on connec...
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11/05/2021
Impact of the Sensing Spectrum on Signal Recovery in Generalized Linear Models
We consider a nonlinear inverse problem 𝐲= f(𝐀𝐱), where observations 𝐲∈ℝ...
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09/22/2020
On the proliferation of support vectors in high dimensions
The support vector machine (SVM) is a well-established classification me...
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06/18/2020
When Does Preconditioning Help or Hurt Generalization?
While second order optimizers such as natural gradient descent (NGD) oft...
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06/10/2020
On the Optimal Weighted ℓ_2 Regularization in Overparameterized Linear Regression
We consider the linear model 𝐲 = 𝐗β_⋆ + ϵ with 𝐗∈ℝ^n× p in the overparam...
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06/19/2019
Learning to Reconstruct and Understand Indoor Scenes from Sparse Views
This paper proposes a new method for simultaneous 3D reconstruction and ...
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06/04/2019
How many variables should be entered in a principal component regression equation?
We study least squares linear regression over N uncorrelated Gaussian fe...
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03/18/2019
Two models of double descent for weak features
The "double descent" risk curve was recently proposed to qualitatively d...
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03/06/2019
Spectral Method for Phase Retrieval: an Expectation Propagation Perspective
Phase retrieval refers to the problem of recovering a signal x_∈C^n from...
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02/05/2019
Consistent Risk Estimation in High-Dimensional Linear Regression
Risk estimation is at the core of many learning systems. The importance ...
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10/26/2018
Benefits of over-parameterization with EM
Expectation Maximization (EM) is among the most popular algorithms for m...
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06/08/2018
Approximate Message Passing for Amplitude Based Optimization
We consider an ℓ_2-regularized non-convex optimization problem for recov...
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01/03/2018
Optimization-based AMP for Phase Retrieval: The Impact of Initialization and ℓ_2-regularization
We consider an ℓ_2-regularized non-convex optimization problem for recov...
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09/25/2017
Non-iterative Label Propagation on Optimal Leading Forest
Graph based semi-supervised learning (GSSL) has intuitive representation...
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08/17/2017
An Improved Residual LSTM Architecture for Acoustic Modeling
Long Short-Term Memory (LSTM) is the primary recurrent neural networks a...
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08/26/2016
Global analysis of Expectation Maximization for mixtures of two Gaussians
Expectation Maximization (EM) is among the most popular algorithms for e...
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06/12/2015