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06/28/2023
Secure and Fast Asynchronous Vertical Federated Learning via Cascaded Hybrid Optimization
Vertical Federated Learning (VFL) attracts increasing attention because ...
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06/02/2023
FREPA: An Automated and Formal Approach to Requirement Modeling and Analysis in Aircraft Control Domain
Formal methods are promising for modeling and analyzing system requireme...
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02/28/2023
Language-Universal Adapter Learning with Knowledge Distillation for End-to-End Multilingual Speech Recognition
In this paper, we propose a language-universal adapter learning framewor...
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02/20/2023
Stability-based Generalization Analysis for Mixtures of Pointwise and Pairwise Learning
Recently, some mixture algorithms of pointwise and pairwise learning (PP...
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02/20/2023
On the Stability and Generalization of Triplet Learning
Triplet learning, i.e. learning from triplet data, has attracted much at...
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02/02/2023
Energy Efficient Training of SNN using Local Zeroth Order Method
Spiking neural networks are becoming increasingly popular for their low ...
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10/11/2022
Zeroth-Order Hard-Thresholding: Gradient Error vs. Expansivity
ℓ_0 constrained optimization is prevalent in machine learning, particula...
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10/04/2022
Zeroth-Order Negative Curvature Finding: Escaping Saddle Points without Gradients
We consider escaping saddle points of nonconvex problems where only the ...
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09/15/2022
GAGA: Deciphering Age-path of Generalized Self-paced Regularizer
Nowadays self-paced learning (SPL) is an important machine learning para...
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08/11/2022
An Accelerated Doubly Stochastic Gradient Method with Faster Explicit Model Identification
Sparsity regularized loss minimization problems play an important role i...
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07/08/2022
Balanced Self-Paced Learning for AUC Maximization
Learning to improve AUC performance is an important topic in machine lea...
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06/30/2022
Stochastic Bilevel Distributed Optimization over a Network
Bilevel optimization has been applied to a wide variety of machine learn...
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06/06/2022
Learning to Control under Time-Varying Environment
This paper investigates the problem of regret minimization in linear tim...
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03/19/2022
Desirable Companion for Vertical Federated Learning: New Zeroth-Order Gradient Based Algorithm
Vertical federated learning (VFL) attracts increasing attention due to t...
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02/26/2022
Multi-Level Contrastive Learning for Cross-Lingual Alignment
Cross-language pre-trained models such as multilingual BERT (mBERT) have...
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12/09/2021
A Fully Single Loop Algorithm for Bilevel Optimization without Hessian Inverse
In this paper, we propose a new Hessian inverse free Fully Single Loop A...
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09/26/2021
AsySQN: Faster Vertical Federated Learning Algorithms with Better Computation Resource Utilization
Vertical federated learning (VFL) is an effective paradigm of training t...
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09/18/2021
An Accelerated Variance-Reduced Conditional Gradient Sliding Algorithm for First-order and Zeroth-order Optimization
The conditional gradient algorithm (also known as the Frank-Wolfe algori...
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07/21/2021
Fast and Scalable Adversarial Training of Kernel SVM via Doubly Stochastic Gradients
Adversarial attacks by generating examples which are almost indistinguis...
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06/16/2021
Topic Classification on Spoken Documents Using Deep Acoustic and Linguistic Features
Topic classification systems on spoken documents usually consist of two ...
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04/09/2021
Learning Sampling Policy for Faster Derivative Free Optimization
Zeroth-order (ZO, also known as derivative-free) methods, which estimate...
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03/29/2021
Improved Meta-learning training for Speaker Verification
Meta-learning (ML) has recently become a research hotspot in speaker ver...
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03/01/2021
Secure Bilevel Asynchronous Vertical Federated Learning with Backward Updating
Vertical federated learning (VFL) attracts increasing attention due to t...
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02/17/2021
Optimizing Large-Scale Hyperparameters via Automated Learning Algorithm
Modern machine learning algorithms usually involve tuning multiple (from...
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09/01/2020
Improved Bilevel Model: Fast and Optimal Algorithm with Theoretical Guarantee
Due to the hierarchical structure of many machine learning problems, bil...
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08/14/2020
Privacy-Preserving Asynchronous Federated Learning Algorithms for Multi-Party Vertically Collaborative Learning
The privacy-preserving federated learning for vertically partitioned dat...
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06/29/2020
Fast OSCAR and OWL Regression via Safe Screening Rules
Ordered Weighted L_1 (OWL) regularized regression is a new regression an...
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02/06/2020
Faster On-Device Training Using New Federated Momentum Algorithm
Mobile crowdsensing has gained significant attention in recent years and...
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02/04/2020
Large Batch Training Does Not Need Warmup
Training deep neural networks using a large batch size has shown promisi...
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01/14/2020
Gaussian speaker embedding learning for text-independent speaker verification
The x-vector maps segments of arbitrary duration to vectors of fixed dim...
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01/14/2020
An Improved Deep Neural Network for Modeling Speaker Characteristics at Different Temporal Scales
This paper presents an improved deep embedding learning method based on ...
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12/24/2019
Quadruply Stochastic Gradient Method for Large Scale Nonlinear Semi-Supervised Ordinal Regression AUC Optimization
Semi-supervised ordinal regression (S^2OR) problems are ubiquitous in re...
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07/29/2019
Quadruply Stochastic Gradients for Large Scale Nonlinear Semi-Supervised AUC Optimization
Semi-supervised learning is pervasive in real-world applications, where ...
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07/26/2019
Scalable Semi-Supervised SVM via Triply Stochastic Gradients
Semi-supervised learning (SSL) plays an increasingly important role in t...
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02/16/2019
Faster Gradient-Free Proximal Stochastic Methods for Nonconvex Nonsmooth Optimization
Proximal gradient method has been playing an important role to solve man...
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07/12/2018
Training Neural Networks Using Features Replay
Training a neural network using backpropagation algorithm requires passi...
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04/27/2018