Huzefa Rangwala

Federated Multi-task Hierarchical Attention Model for Sensor Analytics

2019 · arXiv (Cornell University)

Sensors are an integral part of modern Internet of Things (IoT) applications. There is a critical need for the analysis of heterogeneous multivariate temporal data obtained from the individual sensors of these systems. In this …

Asynchronous Online Federated Learning for Edge Devices.

2019 · arXiv (Cornell University)

Federated learning (FL) is a machine learning paradigm where a shared central model is learned across multiple distributed client devices while the training data remains on edge devices or local clients. Most prior work on …

Improving Zero-Shot Event Extraction via Sentence Simplification

2022

The success of sites such as ACLED and Our World in Data have demonstrated the massive utility of extracting events in structured formats from large volumes of textual data in the formof news, social media, …

OpenTab: Advancing Large Language Models as Open-domain Table Reasoners

2024 · arXiv (Cornell University)

Large Language Models (LLMs) trained on large volumes of data excel at various natural language tasks, but they cannot handle tasks requiring knowledge that has not been trained on previously. One solution is to use …