activity
20172023
most citedMed-MMHL: A Multi-Modal Dataset for Detecting Human- and LLM-Generated Misinformation in the Medical Domain

11 citations · 20 across the 7 of their papers we have counts for

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6 papers · 1 filter

cs.LG20196 cited

CONAN: Complementary Pattern Augmentation for Rare Disease Detection

Limeng Cui, Siddharth Biswal, Lucas M. Glass +3

Rare diseases affect hundreds of millions of people worldwide but are hard to detect since they have extremely low prevalence rates (varying from 1/1,000 to 1/200,000 patients) and…

cs.LG2018

GEN Model: An Alternative Approach to Deep Neural Network Models

Jiawei Zhang, Limeng Cui, Fisher B. Gouza

In this paper, we introduce an alternative approach, namely GEN (Genetic Evolution Network) Model, to the deep learning models. Instead of building one single deep model, GEN adopt…

cs.LG2018

Reconciled Polynomial Machine: A Unified Representation of Shallow and Deep Learning Models

Jiawei Zhang, Limeng Cui, Fisher B. Gouza

In this paper, we aim at introducing a new machine learning model, namely reconciled polynomial machine, which can provide a unified representation of existing shallow and deep mac…

cs.LG2018

On Deep Ensemble Learning from a Function Approximation Perspective

Jiawei Zhang, Limeng Cui, Fisher B. Gouza

In this paper, we propose to provide a general ensemble learning framework based on deep learning models. Given a group of unit models, the proposed deep ensemble learning framewor…

cs.LG2018

Deep Loopy Neural Network Model for Graph Structured Data Representation Learning

Jiawei Zhang

Existing deep learning models may encounter great challenges in handling graph structured data. In this paper, we introduce a new deep learning model for graph data specifically, n…

cs.LG2018

GADAM: Genetic-Evolutionary ADAM for Deep Neural Network Optimization

Jiawei Zhang, Fisher B. Gouza

Deep neural network learning can be formulated as a non-convex optimization problem. Existing optimization algorithms, e.g., Adam, can learn the models fast, but may get stuck in l…