Non-Volatile Memory Accelerated Geometric Multi-Scale Resolution Analysis

no code implementations • 21 Feb 2022 • Andrew Wood, Moshik Hershcovitch, Daniel Waddington, Sarel Cohen, Meredith Wolf, Hongjun Suh, Weiyu Zong, Peter Chin

Dimensionality reduction algorithms are frequently used to augment downstream tasks such as machine learning, data science, and also are exploratory methods for understanding complex phenomena.

Dimensionality Reduction

Non-Volatile Memory Accelerated Posterior Estimation

no code implementations • 21 Feb 2022 • Andrew Wood, Moshik Hershcovitch, Daniel Waddington, Sarel Cohen, Peter Chin

Bayesian inference allows machine learning models to express uncertainty.

Bayesian Inference BIG-bench Machine Learning

What is Learned in Knowledge Graph Embeddings?

no code implementations • 19 Oct 2021 • Michael R. Douglas, Michael Simkin, Omri Ben-Eliezer, Tianqi Wu, Peter Chin, Trung V. Dang, Andrew Wood

Their relative success is often credited in the literature to their ability to learn logical rules between the relations.

Knowledge Graph Embeddings

GymFG: A Framework with a Gym Interface for FlightGear

no code implementations • 26 Apr 2020 • Andrew Wood, Ali Sydney, Peter Chin, Bishal Thapa, Ryan Ross

As a result, we have developed GymFG: GymFG couples and extends a high fidelity, open-source flight simulator and a robust agent learning framework to facilitate learning of more complex tasks.

Imitation Learning

Detecting Speech Act Types in Developer Question/Answer Conversations During Bug Repair

no code implementations • 13 Jun 2018 • Andrew Wood, Paige Rodeghero, Ameer Armaly, Collin McMillan

This paper targets the problem of speech act detection in conversations about bug repair.