4 papers
MoMoE: A Mixture of Expert Agent Model for Financial Sentiment Analysis
Peng Shu, Junhao Chen, Zhengliang Liu +8
We present a novel approach called Mixture of Mixture of Expert (MoMoE) that combines the strengths of Mixture-of-Experts (MoE) architectures with collaborative multi-agent framewo…
Non-Asymptotic Analysis of Online Local Private Learning with SGD
Enze Shi, Jinhan Xie, Bei Jiang +2
Differentially Private Stochastic Gradient Descent (DP-SGD) has been widely used for solving optimization problems with privacy guarantees in machine learning and statistics. Despi…
Online differentially private inference in stochastic gradient descent
Jinhan Xie, Enze Shi, Bei Jiang +2
We propose a general privacy-preserving optimization-based framework for real-time environments without requiring trusted data curators. In particular, we introduce a noisy stochas…
Deep Fair Learning: A Unified Framework for Fine-tuning Representations with Sufficient Networks
Enze Shi, Linglong Kong, Bei Jiang
Ensuring fairness in machine learning is a critical and challenging task, as biased data representations often lead to unfair predictions. To address this, we propose Deep Fair Lea…