It's Not What Machines Can Learn, It's What We Cannot Teach

21 February 2020

Papers citing "It's Not What Machines Can Learn, It's What We Cannot Teach"

8 / 8 papers shown

Title
Optimizing Job Allocation using Reinforcement Learning with Graph Neural Networks Lars C.P.M. Quaedvlieg 63 0 0 31 Jan 2025
Graph Neural Networks for the Offline Nanosatellite Task Scheduling Problem Bruno Machado Pacheco L. O. Seman C. A. Rigo E. Camponogara E. Bezerra L. Coelho 33 1 0 24 Mar 2023
HardSATGEN: Understanding the Difficulty of Hard SAT Formula Generation and A Strong Structure-Hardness-Aware Baseline Yicong Li Xinyan Chen Wenxuan Guo Xijun Li Wanqian Luo Jun Huang Hui-Ling Zhen M. Yuan Junchi Yan 29 17 0 04 Feb 2023
The CLRS Algorithmic Reasoning Benchmark Petar Velivcković Adria Puigdomenech Badia David Budden Razvan Pascanu Andrea Banino Mikhail Dashevskiy R. Hadsell Charles Blundell 161 88 0 31 May 2022
Combinatorial Optimization with Physics-Inspired Graph Neural Networks M. Schuetz J. K. Brubaker H. Katzgraber AI4CE 20 177 0 02 Jul 2021
Combinatorial optimization and reasoning with graph neural networks Quentin Cappart Didier Chételat Elias Boutros Khalil Andrea Lodi Christopher Morris Petar Velickovic AI4CE 32 347 0 18 Feb 2021
On Learning Paradigms for the Travelling Salesman Problem Chaitanya K. Joshi T. Laurent Xavier Bresson 73 33 0 16 Oct 2019
A Survey on Bias and Fairness in Machine Learning Ninareh Mehrabi Fred Morstatter N. Saxena Kristina Lerman Aram Galstyan SyDa FaML 323 4,212 0 23 Aug 2019