activity
20202022
most citedIBM Federated Learning: an Enterprise Framework White Paper V0.1

112 citations · 126 across the 6 of their papers we have counts for

collaborators

6 papers

cs.LG2022

SimPO: Simultaneous Prediction and Optimization

Bing Zhang, Yuya Jeremy Ong, Taiga Nakamura

Many machine learning (ML) models are integrated within the context of a larger system as part of a key component for decision making processes. Concretely, predictive models are o…

cs.CY20221 cited

Towards a New Science of Disinformation

Claudio S. Pinhanez, German H. Flores, Marisa A. Vasconcelos +4

How can we best address the dangerous impact that deep learning-generated fake audios, photographs, and videos (a.k.a. deepfakes) may have in personal and societal life? We foresee…

cs.LG2021

Predicting Loss Risks for B2B Tendering Processes

Eelaaf Zahid, Yuya Jeremy Ong, Aly Megahed +1

Sellers and executives who maintain a bidding pipeline of sales engagements with multiple clients for many opportunities significantly benefit from data-driven insight into the hea…

cs.LG202013 cited

Adaptive Histogram-Based Gradient Boosted Trees for Federated Learning

Yuya Jeremy Ong, Yi Zhou, Nathalie Baracaldo +1

Federated Learning (FL) is an approach to collaboratively train a model across multiple parties without sharing data between parties or an aggregator. It is used both in the consum…

cs.LG2020112 cited

IBM Federated Learning: an Enterprise Framework White Paper V0.1

Heiko Ludwig, Nathalie Baracaldo, Gegi Thomas +21

Federated Learning (FL) is an approach to conduct machine learning without centralizing training data in a single place, for reasons of privacy, confidentiality or data volume. How…

cs.LG2020

Temporal Tensor Transformation Network for Multivariate Time Series Prediction

Yuya Jeremy Ong, Mu Qiao, Divyesh Jadav

Multivariate time series prediction has applications in a wide variety of domains and is considered to be a very challenging task, especially when the variables have correlations a…