Bias reformulation for one-shot function induction

By Dianhuan Lin, Eyal Dechter, Kevin Ellis, Josh Tenenbaum, Stephen H. Muggleton. 2014

103 citations recorded by the source corpus.

National Science Foundation (U.S.) (STC Center for Brains, Minds and Machines Award CCF-1231216)

Subfields: Artificial Intelligence, Mechanical Engineering, Statistical and Nonlinear Physics, Meta & Continual Learning, Code Generation & Program Synthesis

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Artificial Intelligence

1. Denny Zhou
2. Yura N. Perov
3. Jiayuan Mao
4. Tarek R. Besold
5. Stephen H. Muggleton
6. Ute Schmid
7. Tian Lin
8. Chong Wang

In Mechanical Engineering

1. Yura N. Perov
2. Lihong Li

In Statistical and Nonlinear Physics

1. Yura N. Perov
2. Lihong Li
3. Denny Zhou

In Meta & Continual Learning

1. Yura N. Perov
2. Lihong Li

In Code Generation & Program Synthesis

1. Yura N. Perov
2. Stephen H. Muggleton
3. Ute Schmid
4. Denny Zhou
5. Emanuel Kitzelmann

Citations in the corpus

• Neural Logic Machines (2019, background): “However, due to an exponentially large searching space of the compositional rules, it is difficult for ILP to scale beyond small-sized rule sets (Dantsin et al., 2001; Lin et al., 2014; Evans & Grefenstette, 2018).”
• How Does Predicate Invention Affect Human Comprehensibility? (2016, methodology): “Given renewed interest within ILP in the use of predicate invention [11, 12, 7, 1, 2] this paper explores the effects on comprehensibility of using anonymous definitions within logic programs.”
• Neural-Guided Deductive Search for Real-Time Program Synthesis from Examples (2018, unknown): “Most approaches employ either bottom-up enumerative search (Udupa et al., 2013), constraint solving (Torlak & Bodik, 2013), or inductive logic programming (Lin et al., 2014), and thus scale poorly to real-world industrial applications (e.g. data wrangling applications).”
• Applications of Probabilistic Programming (Master's thesis, 2015) (2016, methodology): “Approaches to program synthesis include work in inductive logic programming (Muggleton, 1996; Kersting, 2005; Raedt et al., 2008; Lin et al., 2014), evolutionary programming (Koza, 1992), inference over grammars (Olsson, 1995), and functional programming (Schmid and Wysotzki, 1998).”