Di Wu

WeNet: Production oriented Streaming and Non-streaming End-to-End Speech Recognition Toolkit

2021 · arXiv (Cornell University)

In this paper, we propose an open source, production first, and production ready speech recognition toolkit called WeNet in which a new two-pass approach is implemented to unify streaming and non-streaming end-to-end (E2E) speech recognition …

DPFed: Toward Fair Personalized Federated Learning with Fast Convergence

2022

Instead of training a single global model to fit the needs of all clients, personalized federated learning aims to train multiple client-specific models to better account for data disparities across participating clients. However, existing solutions …

Online Semi-supervised Learning with Mix-Typed Streaming Features

2023 · Proceedings of the AAAI Conference on Artificial Intelligence

Online learning with feature spaces that are not fixed but can vary over time renders a seemingly flexible learning paradigm thus has drawn much attention. Unfortunately, two restrictions prohibit a ubiquitous application of this learning …

OR-AutoRec: An Outlier-Resilient Autoencoder-based Recommendation model

2022

Deep neural network (DNN) is widely adopted to develop the recommender systems (RSs) in recent years due to its powerful non-linear representation learning ability. So far, various sophisticated DNN-based RSs have been achieved to provide …

Design and implementation of an intelligent recommendation system for product information on an e-commerce platform based on machine learning

2023

The rapid growth of e-commerce platforms has resulted in an overwhelming abundance of product information, leading to choice paralysis and information overload for users. To address these challenges and enhance the user experience, an intelligent …

GrabDAE: An Innovative Framework for Unsupervised Domain Adaptation Utilizing Grab-Mask and Denoise Auto-Encoder

2024 · arXiv (Cornell University)

Unsupervised Domain Adaptation (UDA) aims to adapt a model trained on a labeled source domain to an unlabeled target domain by addressing the domain shift. Existing Unsupervised Domain Adaptation (UDA) methods often fall short in …

A Latent Factor Analysis-Based Approach to Online Sparse Streaming Feature Selection

2021 · IEEE Transactions on Systems Man and Cybernetics Systems

Online streaming feature selection (OSFS) has attracted extensive attention during the past decades. Current approaches commonly assume that the feature space of fixed data instances dynamically increases without any missing data. However, this assumption does …