18 citations · 18 across the 8 of their papers we have counts for
8 papers
6.5% of the Neuro-Symbolic Literature Can Be Reproduced from Its Published Artifacts, a Six-Stage Audit Framework and First Instantiation
Brandon Colelough, Vladimir Martirosyan, Ishan Tamrakar +6
We present a six-stage framework for auditing the reproducibility of scientific claims across a research literature within the computer science domain, and instantiate our framewor…
Cost of Structural Learning Under Censored Feedback: A Threshold-Bandit Approach
Michael Ledford, William Regli
In many multi-agent applications, tasks yield rewards only when executed by a coalition meeting an unknown size threshold; otherwise, feedback is fully censored. This censorship cr…
The Imperative for Grand Challenges in Computing
William Regli, Rajmohan Rajaraman, Daniel Lopresti +5
Computing is an indispensable component of nearly all technologies and is ubiquitous for vast segments of society. It is also essential to discoveries and innovations in most disci…
Learning to Coordinate Under Threshold Rewards: A Cooperative Multi-Agent Bandit Framework
Michael Ledford, William Regli
Cooperative multi-agent systems often face tasks that require coordinated actions under uncertainty. While multi-armed bandit (MAB) problems provide a powerful framework for decent…
Now More Than Ever, Foundational AI Research and Infrastructure Depends on the Federal Government
Michela Taufer, Rada Mihalcea, Matthew Turk +13
Leadership in the field of AI is vital for our nation's economy and security. Maintaining this leadership requires investments by the federal government. The federal investment in…
Reclaiming the Future: American Information Technology Leadership in an Era of Global Competition
Alex Aiken, David Jensen, Catherine Gill +5
The United States risks losing its global leadership in information technology research due to declining basic research funding, challenges in attracting talent, and tensions betwe…
Neuro-Symbolic AI in 2024: A Systematic Review
Brandon C. Colelough, William Regli
Background: The field of Artificial Intelligence has undergone cyclical periods of growth and decline, known as AI summers and winters. Currently, we are in the third AI summer, ch…
Accelerating the Operation of Complex Workflows through Standard Data Interfaces
Taylor Paul, William Regli
In this position paper we argue for standardizing how we share and process data in scientific workflows at the network-level to maximize step re-use and workflow portability across…