activity
20122024
most citedClass-Incremental Learning via Knowledge Amalgamation

5 citations · 6 across the 5 of their papers we have counts for

collaborators

5 papers

cs.CV2024

Dual Expert Distillation Network for Generalized Zero-Shot Learning

Zhijie Rao, Jingcai Guo, Xiaocheng Lu +5

Zero-shot learning has consistently yielded remarkable progress via modeling nuanced one-to-one visual-attribute correlation. Existing studies resort to refining a uniform mapping…

cs.CR2023

Segue: Side-information Guided Generative Unlearnable Examples for Facial Privacy Protection in Real World

Zhiling Zhang, Jie Zhang, Kui Zhang +3

The widespread use of face recognition technology has given rise to privacy concerns, as many individuals are worried about the collection and utilization of their facial data. To…

cs.AI2023

IntentDial: An Intent Graph based Multi-Turn Dialogue System with Reasoning Path Visualization

Zengguang Hao, Jie Zhang, Binxia Xu +3

Intent detection and identification from multi-turn dialogue has become a widely explored technique in conversational agents, for example, voice assistants and intelligent customer…

cs.LG20225 cited

Class-Incremental Learning via Knowledge Amalgamation

Marcus de Carvalho, Mahardhika Pratama, Jie Zhang +1

Catastrophic forgetting has been a significant problem hindering the deployment of deep learning algorithms in the continual learning setting. Numerous methods have been proposed t…

cs.NI20121 cited

A note on the bivariate distribution representation of two perfectly correlated random variables by Dirac's -function

Andrés Alayón Glazunov, Jie Zhang

In this paper we discuss the representation of the joint probability density function of perfectly correlated continuous random variables, i.e., with correlation coefficients $ρ=pm…